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USER GUIDE TO HISTORICAL DATA BASE ON
INDIVIDUAL GOVERNMENT FINANCES (INDFIN)
Table of Contents
CLICK ON ANY LINE BELOW TO GO DIRECTLY TO THAT TOPIC:
Preface and Acknowledgements
1. Available Years of Data and SAS Dataset Names
2. Annotated Guide to Variables in the Historical Finance Data Base
3. Latest Version Number for Each Year
4. Guide to Reference Tables in the Data Base (ALLIds and IDxWalk)
5. Important Data User Notes
6. Sample SAS Programs for Querying the IndFin Data Base
7. SAS Formulas for Deriving "Calculable" Variables
8. Using the SAS Query Application to Extract Data from the Historical Finance Data Base
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Preface
The data base that is subject of this user guide represents the Census
a time series of historically-consistent data on finances of individual
it contains have been released previously, they were provided in the
current. Moreover, the data were presented under the classification
were in effect at that time.
The data base includes the following features:
- In its initial release, the data base provides nearly three decades o
fiscal years 1967 and 1970 through 1999. Additional years will be
- It contains over one million individual local government records, in
special districts, and independent school districts.
- It provides over 500 variables on government revenues, expenditu
- These variables comprise individual finance codes as well as dozen
- The data base is in SAS software format. Also available is a special
requires little or no knowledge of the software itself.
- The data base frees the researcher from the arduous task of recon
and other data-related changes that have occurred over the last 3
This data base is the latest member of the historical finance data bas
Federal, state, and local government finances aggregated by state an
national level data for years going back to 1902.
U.
Go
Go
Se
Acknowledgements
This data base was developed in the Governments Division by the Pr
Robert McArthur under the general supervision of Mitchell Trager, A
and Information Systems. John Curry was lead researcher for the pro
This project could not have been completed without the cooperation
Systems Technology Branch, converted many of the data files used in
mainframe format. Daniel Pflum's impressive memory and filing syst
resolutions regarding files from the mainframe era. Donna Hirsch pa
requests. Former assistant division chief Karl Kindel was a major sup
Leonard Thompson, Administrative and Customer Services Division, a
National Archives and Records Administration.
Valuable advice and assistance were also provided by George Beaven
Chamberlain, Diana Cull (retired), Robert Junghans, Gerard Keffer, W
Lawrence, Lawrence MacDonald, Sharon Meade, Stephen Owens, an
Kudos need to be awarded to the computer staff at both the Census
for their care in preserving the original data files. The inability to rea
Most of all, grateful acknowledgement is due to thousands of govern
information over the last three decades, data that are now encapsula
"It is a capital mistake to theorize b
Sherlock Holmes, "A Scandal in
(Sir Arthur Conan Doy
Go to Contents
Preface
The data base that is subject of this user guide represents the Census Bureau's first effort to provide
a time series of historically-consistent data on finances of individual governments. Although most data
it contains have been released previously, they were provided in the format and medium that were then
current. Moreover, the data were presented under the classification scheme and coding system that
were in effect at that time.
The data base includes the following features:
- In its initial release, the data base provides nearly three decades of government finance data, spanning
fiscal years 1967 and 1970 through 1999. Additional years will be added when available.
- It contains over one million individual local government records, including counties, cities, townships,
special districts, and independent school districts.
- It provides over 500 variables on government revenues, expenditures, debt, and cash and security holdings.
- These variables comprise individual finance codes as well as dozens of totals and subtotals.
- The data base is in SAS software format. Also available is a special application for extracting data that
requires little or no knowledge of the software itself.
- The data base frees the researcher from the arduous task of reconciling the many technical, classification,
and other data-related changes that have occurred over the last 30 years.
This data base is the latest member of the historical finance data base series. This series includes data on
Federal, state, and local government finances aggregated by state and type of government as well as
national level data for years going back to 1902.
U.S. Bureau of the Census
Governments Division
Gordon W. Green, Chief
September 2000
Acknowledgements
This data base was developed in the Governments Division by the Program Evaluation Branch, headed by
Robert McArthur under the general supervision of Mitchell Trager, Assistant Division Chief for Evaluation
and Information Systems. John Curry was lead researcher for the project.
This project could not have been completed without the cooperation of other staff members. James Maier,
Systems Technology Branch, converted many of the data files used in this project from their original esoteric
mainframe format. Daniel Pflum's impressive memory and filing system provided many insights and problem
resolutions regarding files from the mainframe era. Donna Hirsch patiently endured numerous questions and
requests. Former assistant division chief Karl Kindel was a major supporter and proponent of this project.
Leonard Thompson, Administrative and Customer Services Division, aided the retrieval of files from the
National Archives and Records Administration.
Valuable advice and assistance were also provided by George Beaven (retired), Warren Besore, Kathy
Chamberlain, Diana Cull (retired), Robert Junghans, Gerard Keffer, William Kehm, David Kellerman, Elizabeth
Lawrence, Lawrence MacDonald, Sharon Meade, Stephen Owens, and Henry Wulf.
Kudos need to be awarded to the computer staff at both the Census Bureau and the National Archives
for their care in preserving the original data files. The inability to read files was a rare problem.
Most of all, grateful acknowledgement is due to thousands of government officials who provided the original
information over the last three decades, data that are now encapsulated in this data base.
"It is a capital mistake to theorize before one has data."
Sherlock Holmes, "A Scandal in Bohemia"
(Sir Arthur Conan Doyle )
Go to Contents
1. Available Years of Data and SAS Dataset Names
As of: 16-July-2001
Number of local government records
SAS Special School
Survey Dataset Total Counties Cities Townships Districts Districts
Year Name Records (1) (2) (3) (4) (5)
Data Files:
1999 IndFin99 22,854 1,564 3,447 884 3,414 13,545
1998 IndFin98 22,939 1,566 3,439 893 3,401 13,640
1997 IndFin97 87,453 3,043 19,372 16,629 34,683 13,726
1996 IndFin96 13,346 1,568 3,399 885 3,391 4,103
1995 IndFin95 12,884 1,570 3,387 884 2,987 4,056
1994 IndFin94 12,862 1,570 3,356 881 3,034 4,021
1993 IndFin93 12,892 1,569 3,302 880 3,037 4,104
1992 IndFin92 84,955 3,043 19,279 16,656 31,555 14,422
1991 IndFin91 32,154 2,178 6,523 5,034 6,157 12,262
1990 IndFin90 34,915 2,248 6,771 5,048 6,227 14,621
1989 IndFin89 34,015 2,260 7,416 5,676 6,454 12,209
1988 IndFin88 36,127 2,372 8,944 6,939 5,619 12,253
1987 IndFin87 83,148 3,042 19,217 16,695 29,427 14,767
1986 IndFin86 53,083 2,898 16,434 15,555 5,674 12,522
1985 IndFin85 54,579 2,991 17,711 15,732 5,814 12,331
1984 IndFin84 54,359 2,967 17,441 15,824 5,758 12,369
1983 IndFin83 33,125 2,436 6,910 4,031 7,542 12,206
1982 IndFin82 82,566 3,041 19,086 16,761 28,721 14,957
1981 IndFin81 53,442 2,969 17,715 15,926 4,783 12,049
1980 IndFin80 29,548 2,100 4,832 2,630 4,875 15,111
1979 IndFin79 56,154 3,003 17,718 15,632 4,822 14,979
1978 IndFin78 19,505 1,714 4,050 1,478 2,867 9,396
1977 IndFin77 79,832 3,042 18,861 16,821 25,987 15,121
1976 IndFin76 15,971 1,715 4,049 1,492 3,081 5,634
1975 IndFin75 15,956 1,715 4,048 1,492 3,073 5,628
1974 IndFin74 15,940 1,715 4,044 1,492 3,039 5,650
1973 IndFin73 16,145 1,856 3,777 1,224 3,177 6,111
1972 IndFin72 78,216 3,044 18,517 16,991 23,885 15,779
1971 IndFin71 16,177 1,856 3,779 1,224 3,194 6,124
1970 IndFin70 16,177 1,856 3,779 1,224 3,194 6,124
1967 IndFin67 16,107 1,857 3,765 1,224 3,088 6,173
Reference Files (click on dataset name to view more information about it):
ALLids Lists all the unique IDs in the data base plus basic information on the years reported.
IDxWalk Lists all known governments whose ID numbers have changed since 1967.
Notes:
- Although 1967 is a census of governments year, the dataset contains only sample units (no census file
has been found).
- The number of records available for each year varies for different reasons. 1972, 1977, 1982, 1987,
1992, and 1997 cover a census of governments; some years are strictly the sample for that year
(including 1967); and others are sample units plus nonsample records in central collection states.
Click here to see the User Notes on this subject.
- The "IndFin" files include over 42,000 records with no data. That is, the value for every finance variable
in the data base is zero. These records have a ZeroFlag code of '1'.
Click here to see the User Notes on this subject.
- Suggested SAS Libname statement:
LibName IndFin '\\Govs05\PEB\Historical Data\Finance\Individual Units';
UserGuide.Xls (1. Years) 1/5/2013
Go to: Contents Revenues Debt
Top of page Expend Assets
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
GUIDE TO USING THIS CHART:
Col. A: Variable number for reference purposes. Also represents SAS position number for variable.
Col. B: The finance code for that item (if any). DDD, T--, -26, 41-, etc. indicate totals or subtotals of codes.
Col. C: The component number of the variable in the former System 2000 (S2K) finance estimates data base.
Col. D: SAS default "label" for variable. Also serves as dBase field name when exported to DBF format.
Col. E: SAS variable name.
Notes: SAS variable names begin with a letter and have maximum of 8 characters.
Since SAS variable names can not begin with a number, SAS name for many debt codes are preceded by an underscore ("_").
Examples: _19H _24T _39F _44X _64V
SAS is case in sensitive to variable names (i.e., you can write the variable called "ID" in any of these forms: ID, id, or Id).
Variables without SAS names are not stored in the data base but must be calculated.
Col. F: Indicates type of variable, as follows--- C = Character N = Numeric F = Formula (not actually stored in data base but can be derived using formula shown)
Note: When creating SAS "Where" and "IF" statements that refer to character fields, be sure to put values inside single-quote marks.
Examples: Where type = '1' and JackFlag = '1'; IF Cen_Reg = '2' and POP GT 100000;
Col. G: Full description of variable.
Cols. H and I: Indicate whether the variable is physically stored in the data base or if it must be computed:
Col. H: An "X" in this column indicates a variable that is stored in the data base.
Col. I: A formula in this column indicates that the variable must be computed and provides the proper formula to use.
TIPS: Copy individual formulas from this page and paste into the SAS Program Editor. To copy/paste groups of formulas, use the "Formulas" page of this guide.
Click here to go to the SAS formulas page.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 9 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
The SAS Query Application allows you to specify these formula variables using special "keywords."
Click here to go to the guide on using the SAS query application.
Cols. J - N: Indicate the particular type or group(s) of governments for which data were collected--
"." denotes that data were collected for that variable
"N" denotes that data were not collected for that variable
Col. J : DC District of Columbia.
Col. K: Jacket Jacket units (other than District of Columbia).
Col. L: Other GenP All other general purpose local governments (types 1 - 3).
Col. M: Spec Dist. Special districts (type 4).
Col. N: Sch Dist. Independent school districts (type 5).
This information is often called the "impossible code list." Although based on the 1989 finance data dictionary, it has changed little in subsequent years.
It may be less accurate, however, for previous years, especially before fiscal year 1988 when major revisions were made to the classification system. For
example, prior to fiscal year 1977 the function Toll Highways (-45) was combined with Regular Highways (-44).
Col. O (not shown in print version): This column provides additional information about data collection coverage for individual years. Each of the subcolumns
represents a survey year. The code in each column represents the number of governments reporting data for that variable in that survey year:
0 = No governments reported data for that variable.
1 = Between 1 and 100 governments reported data for that variable.
2 = Over 100 governments reported data for that variable.
Col. P (not shown in print version): This column provides extended historical annotations about the data variable.
OTHER NOTES:
- These data files are stored on the Historical Data Server (\\Govs05\PEB).
Suggested LIBNAME statement: LibName IndFIn '\\Govs05\PEB\Historical Data\Finance\Individual Units';
TIP: Add the above LIBNAME statement to your "AutoExec.SAS" file.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 10 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
- All finance data are in thousands of dollars ($000). Population and enrollment data are in whole numbers.
*** GENERAL AND REFERENCE VARIABLES ***
1 C60 SurveyYear SurveyYr N Survey Year (67, 77, 88, 90, 96, etc)............................................................................…
X . . . .
2 C1 ID ID C Current GOVS Identification Number (9-digit)........................................................… X . . . .
3 IDChanged IDChged N Indicates how many times ID number has changed since 1967…………………… X . . . .
Value indicates number of times ID has changed
All previous IDs are listed in the "IDxWalk" dataset
This variable is same as IDxWalk's "TotIDChg" variable
Click here to see the User Notes on this subject.
4 C3 StateCode State C 2-Digit GOVS State Code (01, 02, 21, 36, 50, etc.)...............................................… X . . . .
5 C4 TypeCode Type C 1-Digit Type of Government Code.....................................................................… X . . . .
1 = County 4 = Special district
2 = City 5 = School district (independent only)
3 = Township
6 County County C 3-Digit GOVS County Code (001, 002, etc.).........................................................… X . . . .
F 3-Digit GOVS Unit Code (001, 302, 905, etc.).......................................................… Unit=Substr(ID,7,3); . . . .
7 C2 Name Name C Name of Government (in CAPS)..........................................................................… X . . . .
8 C11 CensusReg Cen_Reg C Census Region Code.......................................................................................… X . . . .
1 = Northeast 3 = South
2 = Midwest 4 = West
9 C7 FIPS_State FIPS_ST C FIPS State Code (01, 02, 21, 36, 56, etc.)...............................................………… X . . . .
10 Weight Weight N Statistical weight (10000 = certainty; 0 = nonsample)............................................… X . . . .
Not available for FY 67, 70, 71, and 73. Weights for these years are 1.
Click here to see the User Notes on this subject.
11 FYEndDate FYEnd C Fiscal year ending date (e.g., 1231, 0630)..........................................................… X . . . .
Values like '0', '0000', or 'BBBB' indicate not available
'BBBB' indicates field in source file was blank or unusable
For some years only the ending month is available (e.g., 6)
Note: Reliability of data not verified. Caveat emptor!
12 YearData YrData C Actual year of data reported (e.g., 90, 87, or one of these codes:).........................… X . . . .
BB = Field in source file was blank (or not usable)
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 11 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
CC = Data pulled from previous census of governments
DD = Data provided by government (i.e., not imputed)
GG = Data from census of governments' directory survey
II = Data were imputed
NN = Not available
For 1997 and later surveys, a suffix of "G", "P", or "Q" may be appended
to the year indicating that the data were imputed using various methods
based on the data for the year cited.
Examples: 92G, 97Q, 98P
13 YearPop YrPop C Year of Population/Enrollment Data (not available before FY 1987)........................…X . . . N
BB = Field in source file was blank or 0 (applies to FY 1987 and later years)
For school districts, represents fall enrollment for year cited.
Click here to see the User Notes on this subject.
14 YearDepSch YrDepSch C Year of Dependent School Data (not available before FY 87 or after FY 92).....… X . . . N
BB = Field in source file was blank (applies to FY 1987 and later years)
TIP: This field flags governments that operate dependent school systems
15 YearRetire YrRet C Year of Retirement Data......................................................……………………………… X . . . .
Not available prior to 1987 except for records whose retirement data were
missing and replaced with prior year data (applies to 1970, 1971, and
1973-76 only). Not available after FY 1992 (except for FY 1997).
BB = Field in source file was blank (applies to FY 1987 and later years)
Click here to see the User Notes on this subject.
16 SchLevCode SchLvCod C School Level Code (School districts only)....................……………………………….. X N N N N
Not available before FY 1987 or for FY 1993, 1995, and 1996.
01 = Elementary school system only
02 = Secondary school system only
03 = Elementary-secondary school system
04 = College-grade school system
05 = Vocational or special education school system
06 = Nonoperating school system
07 = Educational service agency (ESA). Excluded from this data base.
BB = Field in source file was blank (applies to FY 1987 and later years)
17 Version Version C Data Base Version (Initial release is A).................................……………………………X . . . .
18 ReviseDate RevDate C Date of Last Revision to Data Base (see "User Notes")...........................................…X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 12 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
19 Data_Flag DataFlag C Data Flag (provides additional information about record)……………..……………. X . . . .
A = All data (entire record) replaced with public-use file's (FY 1983 only)
C = Cash and securities data replaced with public-use file's*
D = Debt data replaced with public-use file's*
E = Expenditure data replaced with public-use file's*
F = Reserved from employment historical data base
G = Missing population, function code, or enrollment data replaced with
data from employment file ("IndEmp")
K = Keying and/or outlier error revised
L = Missing employee retirement data (or detail) replaced with current year
data from publication#
M = Missing employee retirement data replaced with prior year data (FY
1970, 1971, and 1973-1976 only)@
N = Negative value found in source file; data revised
O = Overflow flag found in source file; data revised
P = Publication table correction not applied to source file; data revised
Q = Q11 extracted from M12 using school finance file (95 and 96 only)
R = Revenue data replaced with public-use file's*
S = Salary & wages (Z00) data replaced with public-use file's but not any
other expenditure data (FY 1983 only)
X = Errata notice revision not applied to source file; data revised
Z = Data revision for reasons NEC
* Applies only to FY 1981 and 1983.
# Applies to FY 1973-1976 jacket units only. Includes cases where record
was missing employee-retirement detail.
@ May include jacket units if publication data unavailable.
Click here to see the User Notes on this subject.
20 JacketUnit JackFlag C Jacket Unit Flag…..………………………………………………………………………. X . . N N
1 = Unit was jacket unit for that survey year
0 = Unit was not a jacket unit for that survey year
Click here to see the User Notes on this subject.
21 ZeroData ZeroFlag C Blank (Zero-Filled) Record Flag………………………………………………………… X . . . .
1 = All finance variables equal zero
2 = All four major totals equal zero but at least 1 finance variable not in
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 13 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
these totals has data (e.g., salaries and wages exhibit, code Z00)
0 = All other records
Click here to see the User Notes on this subject.
22 C62 Population Pop N Population/Enrollment/Function Code (in whole numbers)......................................… X . . . .
Original population as found in source file (i.e., not updated)
School districts enrollment data for FY 1974-76 and 1978 were taken from
employment files ("IndEmp")
Click here to see the User Notes on this subject.
Function codes for special districts:
0 - Not available (value in source file missing or bad)
Single function districts:
1 - Air transportation 79 - Public welfare institutions
2 - Cemeteries 80 - Sewerage
9 - School building auth. 81 - Solid waste management
24 - Fire protection 86 - Reclamation
32 - Health 87 - Water transport & terminals
40 - Hospitals 88 - Soil & water conservation
41 - Industrial development 89 - Other single-function
42 - Mortgage credit districts
44 - Highways 91 - Water supply utility
45 - Toll highways* 92 - Electric power utility
50 - Housing & community dev. 93 - Gas supply utility
51 - Drainage 94 - Mass transit system utility
52 - Libraries Multi-function districts:
59 - Other natural resources 96 - Fire protection & water supply
60 - Parking facilities 97 - Nat. resources & water supply
61 - Parks & recreation 98 - Sewerage & water supply
63 - Flood control 99 - Other multi-function
64 - Irrigation districts
* Now obsolete; subsumed into code 44 (which previously designated
regular highways) in FY 1977.
*** REVENUES ***
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2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
23 DDD C101 TotRev C101 N Total Revenue.....................................................................................................… X . . . .
24 DDD C102 TotRev_Own C102 N Total Revenue from Own Sources......................................................................… X . . . .
25 DDD C103 GenRev C103 N General Revenue....................................................................................................… X . . . .
26 DDD C104 GenRev_Own C104 N General Revenue from Own Sources..................................................................… X . . . .
Taxes:
27 T-- C105 TotTaxes C105 N Total Taxes...........................................................................................................… X . . . .
28 T01 C106 PropTax T01 N Property Tax.......................................................................................................… X . . . .
29 DDD C107 TotSaleTax C107 N Total Sales and Gross Receipts Taxes.........................................................................................…
X . . . .
30 T09 C108 GenSaleTax T09 N General Sales Tax (includes T08 for Federal Government)..........................................................… X . . . .
31 DDD C109 TotSelTax C109 N Total Selective Sales Taxes...............................................................................… X . . . .
32 T10 C110 AlcoBevTax T10 N Alcoholic beverage tax..................................................................................… X . . . .
33 T12 C112 InsPremTax T12 N Insurance premium tax...................................................................................… X . N N N
34 T13 C113 MotFuelTax T13 N Motor fuels tax...............................................................................................… X . . . .
35 T15 C115 PubUtilTax T15 N Public utilities tax.............................................................................................… X . . . .
36 T16 C116 TobaccoTax T16 N Tobacco tax....................................................................................................… X . . . .
37 T19 C117 OthSelTax T19 N Other selective sales tax.............................................................................… X . . . .
38 DDD C118 TotLicTax C118 N Total License Taxes..........................................................................................… X . . . N
39 T20 C119 AlcoBevLic T20 N Alcoholic beverage licenses...............................................................................… X . N N N
40 T22 C121 CorpLic T22 N Corporation licenses............................................................................................… X . N N N
DDD C123 TotMVehLic F Motor vehicle-related licenses...........................................................................… C123=T24+T25; . . . N
41 T24 C124 MtVehLic T24 N Motor vehicle licenses.................................................................................… X . . . N
42 T25 C125 MtVehOpLic T25 N Motor vehicle operator licenses.......................................................................… X . N N N
43 T28 C127 OccuBusLic T28 N Occupation and business licenses, NEC..........................................................… X . N N N
44 T29 C128 OthLicTax T29 N Other licenses......................................................................................................… X . N N N
45 DDD C129 TotIncTax C129 N Total Income Taxes..............................................................................................… X . . . N
46 T40 C130 IndIncTax T40 N Individual income tax (includes code T49)........................................................… X . . . N
47 T41 C131 CorpIncTax T41 N Corporation net income tax.............................................................................… X . . N N
48 T50 C133 DthGiftTax T50 N Death and Gift Tax................................................................................................… X . N N N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 15 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
49 T51 C134 DocumTax T51 N Documentary and Stock Transfer Tax..............................................................… X . N N N
50 T99 C137 TaxNEC T99 N Taxes NEC............................................................................................................… X . . . .
Intergovernmental Revenue:
51 DDD C138 TotIGR C138 N Total Intergovernmental Revenue..........................................................................… X . . . .
52 B-- C139 TotFedIGR C139 N Intergovernmental Revenue from Federal Government, Total................................… X . . . .
53 B01 C140 FIGR_Airp B01 N Air transportation (airports)...............................................................................… X . . N .
54 B21 C141 FIGR_Educ B21 N Education...........................................................................................................… X . . . .
55 B22 C142 FIGR_EmSec B22 N Employment security (social insurance) administration.....................................… X . N N N
DDD C143 FIGR_TotGS F General support.................................................................................................… C143=B27+B30; . . . N
56 B27 C144 FIGR_GRS B27 N General revenue sharing (obsolete after FY 1987)..........................................… X N N N N
57 B30 C146 FIGR_GenSp B30 N Other general support.......................................................................................… X . . . N
58 B42 C147 FIGR_HltHo B42 N Health and hospitals........................................................................................… X . . . .
59 B46 C148 FIGR_Hwys B46 N Highways..........................................................................................................… X . . . .
60 B47 C149 FIGR_TrnSb B47 N Transit subsidies (includes B94)............................................................………….. X N . . .
61 B50 C150 FIGR_HoCD B50 N Housing and community development................................................................… X . . . .
62 B59 C3018 FIGR_NatRs B59 N Natural resources (includes any B54).................................................................… X N N N .
63 B79 C153 FIGR_PuWel B79 N Public welfare.....................................................................................................… X . . . .
64 B80 C154 FIGR_Sewer B80 N Sewerage............................................................................................................… X . . N .
65 B89 C155 FIGR_Other B89 N Other (includes B91, B92, and B93)..........................................................…….. X . . . .
66 C-- C156 TotStaIGR C156 N Intergovernmental Revenue from State Government, Total...................................…X N . . .
67 C21 C157 SIGR_Educ C21 N Education...........................................................................................................… X N . . .
DDD C158 SIGR_TotGS F General local government support, total...........................................................… C158=C28+C30; N . . N
68 C28 C159 SIGR_TaxRe C28 N Tax relief (Note: Obsolete code after FY 87).................................................… X N N N N
69 C30 C160 SIGR_GenSp C30 N Other general support....................................................................................… X N . . N
70 C42 C161 SIGR_HltHo C42 N Health and hospitals...........................................................................................… X N . . .
71 C46 C162 SIGR_Hwys C46 N Highways..........................................................................................................… X N . . .
72 C47 C163 SIGR_TrnSb C47 N Transit subsidies (includes C94)............................................................………….. X N . . .
73 C50 C164 SIGR_HoCD C50 N Housing and community development...............................................................… X N . . .
74 C79 C165 SIGR_PuWel C79 N Public welfare...................................................................................................… X N . . .
75 C80 C166 SIGR_Sewer C80 N Sewerage.........................................................................................................… X N . N .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 16 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
76 C89 C167 SIGR_Other C89 N Other (includes C91, C92, and C93)...........................................................……. X N . . .
77 D-- C168 TotLocIGR C168 N Intergovernmental Revenue from Local Governments, Total................................… X . . . .
Education:
78 D11 C170 LIGR_InSch D11 N From other school systems (applies to type 5's only)......................................… X N N N N
79 D21 C171 LIGR_Educ D21 N All other local education aid............................................................................… X . . . .
80 D30 C174 LIGR_GenSp D30 N General government support............................................................................… X . . . N
81 D42 C175 LIGR_HltHo D42 N Health and hospitals........................................................................................… X . . . .
82 D46 C176 LIGR_Hwys D46 N Highways..........................................................................................................… X . . . .
83 D47 C177 LIGR_TrnSb D47 N Transit subsidies (includes D94)............................................................………. X N . . .
84 D50 C178 LIGR_HoCD D50 N Housing and community development...............................................................… X . . . .
85 D79 C179 LIGR_PuWel D79 N Public welfare...................................................................................................… X . . . .
86 D80 C180 LIGR_Sewer D80 N Sewerage........................................................................................................… X . . N .
87 D89 C181 LIGR_Other D89 N Other (includes D91, D92, and D93)...........................................................……. X . . . .
General Charges and Miscellaneous General Revenue:
88 DDD C182 TotChgMisc C182 N Total Charges and Miscellaneous General Revenue...............................................… X . . . .
89 A-- C183 TotGenChgs C183 N General Charges, Total........................................................................................… X . . . .
90 A01 C184 Chg_Airp A01 N Air transportation (airports)..............................................................................… X . . . .
91 A03 C185 Chg_MisCom A03 N Miscellaneous commercial activities..................................................................… X . . . N
92 DDD C186 Chg_TotEd C186 N Education, total (includes A21, if any)..............................................................… X . . . N
DDD C187 Chg_TotES F Elementary-secondary education, total...........................................................… C187=A09+A10+A12; . . . N
93 A09 C188 Chg_ES_Lun A09 N School Lunch................................................................................................… X . . . N
94 A10 C189 Chg_ES_Tui A10 N Tuition...........................................................................................................… X . . . N
95 A12 C190 Chg_ES_NEC A12 N Other.............................................................................................................… X . . . N
96 DDD C191 Chg_HiEd C191 N Higher Education (includes A16 and A18).....................................................… X . . . N
97 A36 C195 Chg_Hosp A36 N Hospitals..............................................................................................................… X . . . .
DDD C196 Chg_TotHwy F Highways.........................................................................................................… C196=A44+A45; . . . .
98 A44 C197 Chg_RegHwy A44 N Regular Highways (includes A45 before FY 1977)........................................… X . . . .
99 A45 C198 Chg_TolHwy A45 N Toll highways (not available before FY 1977)...............................................................… X . . . N
100 A50 C199 Chg_HoCD A50 N Housing and community development...............................................................… X . . . .
101 A59 C200 Chg_NatRes A59 N Natural resources (includes any A54, A56, and A59).....................................… X N N N .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 17 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
102 A60 C204 Chg_Parkg A60 N Parking facilities.................................................................................................… X . . . .
103 A61 C205 Chg_PrkRec A61 N Parks and recreation........................................................................................… X . . . .
104 A80 C207 Chg_Sewer A80 N Sewerage..........................................................................................................… X . . . .
105 A81 C208 Chg_SWMgmt A81 N Solid waste management...................................................................................… X . . . .
106 A87 C209 Chg_WatTrn A87 N Water transport and terminals..........................................................................… X . . . .
107 A89 C210 Chg_OthNEC A89 N All other general charges, NEC........................................................................… X . . . .
108 U-- C211 MiscGenRev C211 N Miscellaneous General Revenue, Total..................................................................…X . . . .
109 U01 C212 SpecAssess U01 N Special assessments...........................................................................................… X . . . .
U1- C213 TotPropSal F Sale of property, total.........................................................................................… C213=U10+U11; . . . .
110 U10 C214 Prop_HoCD U10 N Housing and community development...........................................................… X . . N N
111 U11 C215 Prop_Other U11 N Other property.................................................................................................… X . . . .
112 U20 C216 InterstRev U20 N Interest earnings on investments......................................................................… X . . . .
113 U30 C217 Fines_Forf U30 N Fines and forfeits.............................................................................................… X . . N N
114 U4- C218 Rents_Royl C218 N Rents and royalties (includes U40 and U41).....................................................… X . . . N
115 U95 C222 NetLotRev U95 N Net lottery revenue, after prizes & admin expenses (Washington DC only)....… X . N N N
116 U99 C223 MiscGenNEC U99 N Other miscellaneous general revenue...............................................................… X . . . .
LIQUOR STORES AND UTILITIES:
117 A90 C224 LiqStorRev A90 N Liquor Stores Revenue.........................................................................................… X N . . N
118 A9- C225 TotUtilRev C225 N Total Utility Charges....................................................................…………………… X . . . .
119 A91 C226 WatUtilRev A91 N Water supply utility charges.................................................................................… X . . . .
120 A92 C228 EleUtilRev A92 N Electric power utility charges...............................................................................… X N . . .
121 A93 C229 GasUtilRev A93 N Gas supply utility charges...................................................................................… X N . . .
122 A94 C230 TrnUtilRev A94 N Transit systems utility charges..........................................................................… X N . . .
INSURANCE TRUST REVENUE:
123 DDD C231 TotInsRev C231 N Total Insurance Trust Revenue (includes systems not listed separately)...........................................…
X . . . .
124 DDD C232 TotInsCtrb C232 N Total insurance trust contributions......................................................................… X . . . .
125 DDD C233 TotInsInv C233 N Total insurance trust earnings on investments.................................................… X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 18 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
Employee Retirement:
126 DDD C234 TotEmpRRev C234 N Total revenue......................................................................................................… X . . . .
127 DDD C235 EmpR_TotCb C235 N Total contributions (Note: Not sum of detail below).............................................… X . . . .
128 X01 C236 EmpR_EmpCb X01 N Contributions from employees (includes any X02)...........................................… X . . . .
129 X04 C238 EmpR_LocLo X04 N Local government contribution to local system (intragovernmental transfer)...… X . . . .
130 X05 C239 EmpR_OthGv X05 N Contribution from other governments..............................................................… X . . . .
131 X06 C240 EmpR_StaSt X06 N State government contribution to own system (sic).................................................… X . . . .
132 X08 C242 EmpR_IntRv X08 N Interest on investments.......................................................................................… X . . . .
133 X09 C243 EmpR_OthEr X09 N Other investment earnings...............................................................................… X . . . .
Unemployment Compensation (Washington DC only for local governments):
134 DDD C244 TotUnemRev C244 N Total revenue.....................................................................................................… X . N N N
135 Y01 C245 Unem_PyTax Y01 N Contributions from employers (payroll taxes)....................................................… X . N N N
136 Y02 C246 Unem_IntRv Y02 N Interest credited by Federal Government............................................................… X . N N N
137 Y04 C248 Unem_FedAv Y04 N Advances and contributions from Federal Government....................................… X . N N N
Note: Can be a negative number
*** EXPENDITURES ***
138 DDD C301 TotExpend C301 N Total Expenditure......................................................................................................…X . . . .
139 DDD C302 TotIGExp C302 N Total Intergovernmental Expenditure......................................................................… X . . . .
140 DDD C303 TotDirExp C303 N Direct Expenditure...................................................................................................… X . . . .
141 DDD C304 TotCurrExp C304 N Total Current Expenditure (= C301 - C307).................................................................… X . . . .
142 E-- C305 TotCurrOp C305 N Total Current Operations........................................................................................… X . . . .
143 DDD C307 TotCapOut C307 N Total Capital Outlays...............................................................................................… X . . . .
144 F-- C308 TotConstr C308 N Construction Only..............................................................................................… X . . . .
G-- C309 TotOthCap F Other Capital Outlays..........................................................................................… C309=C307-C308; . . . .
145 DDD C311 TotAssist C311 N Total Assistance And Subsidies............................................................................… X . . . N
146 I-- C312 TotIntExp C312 N Total Interest On Debt...............................................................................................…X . . . .
147 DDD C313 TotInsTExp C313 N Total Insurance Trust Benefits (includes systems not listed separately below)........................................ X . . . .
148 Z00 C314 Sal_Wages Z00 N Exhibit: Total Salaries And Wages.........................................................................… X . . . .
149 DDD C315 GenExpend C315 N General Expenditure...........................................................................................… X . . . .
Intergovernmental expenditure detail--
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 19 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
150 L-- C316 IGE_ToSta C316 N To State Governments......................................................................................… X N . . .
151 DDD C317 IGE_ToLoc C317 N To Local Governments.................................................................................… X . . . .
152 S-- C324 IGE_ToFed C324 N To Federal Government.........................................................................................…X . . N N
153 DDD C325 GenDirExp C325 N Direct General Expenditure..................................................................................… X . . . .
154 DDD C326 GenCurrExp C326 N General Current Expenditure (= C315 - C329)......................................................… X . . . .
155 E-- C327 GenCurrOp C327 N General Current Operations...............................................................................… X . . . .
156 DDD C329 GenCapOut C329 N General Capital Outlays.......................................................................................… X . . . .
157 F-- C330 GenConstr C330 N General Construction........................................................................................… X . . . .
G-- C331 GenOthCap F General Other Capital Outlays.............................................................................… C331=C329-C330; . . . .
Functional Expenditures:
158 -01 C350 Airp_Tot C350 N Air Transportation, Total..........................................................................................… X . . . .
DDD C351 Airp_IGE F Total intergovernmental.........................................................................................… C351=C350-C352; . . . .
159 -01 C352 Airp_Dir C352 N Direct expenditure..............................................................................................… X . . . .
E01 C353 Airp_Opr F Current operations.............................................................................................… E01=C352-C354; . . . .
160 DDD C354 Airp_Cap C354 N Capital outlays....................................................................................................… X . . . .
161 F01 C355 Airp_Con F01 N Construction...................................................................................................… X . . . .
G01 C356 Airp_OCp F Other capital outlays.......................................................................................… G01=C354-F01; . . . .
Intergovernmental detail--
162 L01 C358 Airp_IGS L01 N To state government........................................................................................… X N . . .
163 M01 C359 Airp_IGL M01 N To local governments, total (includes N01, O01, P01, and R01).........................… X . . . .
164 -03 C365 MisCom_Tot C365 N Miscellaneous Commercial Activities, Total..........................................................… X . . . N
E03 C366 MisCom_Opr F Current operations................................................................................................… E03=C365-C367; . . . N
165 DDD C367 MisCom_Cap C367 N Capital outlays....................................................................................................… X . . . N
166 F03 C368 MisCom_Con F03 N Construction.......................................................................................................… X . . . N
G03 C369 MisCom_OCp F Other capital outlays........................................................................................… G03=C367-F03; . . . N
167 -05 C391 Correc_Tot C391 N Corrections, Total (includes -04).......................................................................… X . . . N
DDD C392 Correc_IGE F Total intergovernmental..................................................................................………. C392=C391-C393; . . . N
168 -05 C393 Correc_Dir C393 N Direct expenditure..........................................................................................…… X . . . N
E05 C394 Correc_Opr F Current operations...........................................................................................… E05=C393-C395; . . . N
169 DDD C395 Correc_Cap C395 N Capital outlays.................................................................................................… X . . . N
170 F05 C396 Correc_Con F05 N Construction......................................................................................................… X . . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 20 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
G05 C397 Correc_OCp F Other capital outlays........................................................................................… G05=C395-F05; . . . N
Intergovernmental detail--
171 L05 C399 Correc_IGS L05 N To state government..........................................................................................… X N . . N
172 M05 C400 Correc_IGL M05 N To local governments, total (includes N05, O05, P05, and R05).........................… X . . . N
173 DDD C406 TotEd_Tot C406 N Total Education, Total...................................................................................................................
X . . . .
DDD C407 TotEd_IGE F Total intergovernmental.......................................................................................… C407=C406-C408; . . . .
174 DDD C408 TotEd_Dir C408 N Direct Expenditure...............................................................................................… X . . . .
DDD C409 TotEd_Opr F Current operations...........................................................................................… C409=C408-C410; . . . .
175 DDD C410 TotEd_Cap C410 N Capital outlays............................................................................................…… X . . . .
176 -12 C412 ElSEd_Tot C412 N Elementary and Secondary Education, Total..........................................................… X . . . .
DDD C413 ElSEd_IGE F Total intergovernmental..........................................................................................… C413=C412-C414; . . . .
177 -12 C414 ElSEd_Dir C414 N Direct expenditure.........................................................................................…… X . . . .
E12 C415 ElSEd_Opr F Current operations............................................................................................… E12=C414-C416; . . . .
178 DDD C416 ElSEd_Cap C416 N Capital outlays.................................................................................................… X . . . .
179 F12 C417 ElSEd_Con F12 N Construction....................................................................................................… X . . . .
G12 C418 ElSEd_OCp F Other capital outlays..........................................................................................… G12=C416-F12; . . . .
Intergovernmental detail--
180 L12 C420 ElSEd_IGS L12 N To state government............................................................................................… X N . . N
181 M12 C421 ElSEd_IGL M12 N To local governments NEC (includes N12, O12, P12, Q12, and R12).........................… X . . . .
182 Q11 C411 ElSEd_IGSc Q11 N Interschool District Transfers..........................................................................................
X N N N N
183 -18 C438 HiEd_Tot C438 N Higher Education, Total (includes -16)........................................................…….. X . . . N
DDD C439 HiEd_IGE F Total intergovernmental.............................................................................................................C439=C438-C440; . . . N
184 -18 C440 HiEd_Dir C440 N Direct expenditure..................................................................................................................
X . . . N
E18 C441 HiEd_Opr F Current operations................................................................................................................
E18=C440-C442; . . . N
185 DDD C442 HiEd_Cap C442 N Capital outlays...................................................................................................................
X . . . N
186 F18 C443 HiEd_Con F18 N Construction....................................................................................................................
X . . . N
G18 C444 HiEd_OCp F Other capital outlays...................................................................................… G18=C442-F18; . . . N
Intergovernmental detail--
187 L18 C446 HiEd_IGS L18 N To state government....................................................................................… X N . . N
188 M18 C447 HiEd_IGL M18 N To local governments, total (includes N18, O18, P18, Q18, and R18).........................… X . . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 21 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
189 -21 C456 OthEd_Tot C456 N Education, NEC, Total (includes any E19)................................................................…X . . . .
DDD C457 OthEd_IGE F Total intergovernmental.............................................................................................................C457=C456-C458; . . . .
190 -21 C458 OthEd_Dir C458 N Direct expenditure (includes any E19)......................................................................… X . . . .
E21 C459 OthEd_Opr F Current operations (includes any E19)................................................................................… E21=C458-C460; . . . .
191 DDD C460 OthEd_Cap C460 N Capital outlays...................................................................................................................
X . . . .
192 F21 C461 OthEd_Con F21 N Construction....................................................................................................................
X . . . .
G21 C462 OthEd_OCp F Other capital outlays........................................................................................… G21=C460-F21; . . . .
Intergovernmental detail--
193 L21 C464 OthEd_IGS L21 N To state government.......................................................................................… X N . . .
194 M21 C465 OthEd_IGL M21 N To local governments, total (includes N21, O21, P21, Q21, and R21).........................… X . . . .
195 -22 C472 EmpSec_Tot C472 N Employment Security Administration, Total............................................................… X . N N N
E22 C473 EmpSec_Opr F Current operations................................................................................................… E22=C472-C474; . N N N
196 DDD C474 EmpSec_Cap C474 N Capital outlays....................................................................................................… X . N N N
197 F22 C475 EmpSec_Con F22 N Construction.......................................................................................................… X . N N N
G22 C476 EmpSec_OCp F Other capital outlays........................................................................................… G22=C474-F22; . N N N
198 -23 C478 FinAdm_Tot C478 N Financial Administration, Total................................................................................… X . . . N
DDD C479 FinAdm_IGE F Total intergovernmental.............................................................................................................
C479=C478-C480; . . . N
199 -23 C480 FinAdm_Dir C480 N Direct expenditure..................................................................................................................
X . . . N
E23 C481 FinAdm_Opr F Current operations.........................................................................................… E23=C480-C482; . . . N
200 DDD C482 FinAdm_Cap C482 N Capital outlays...................................................................................................................
X . . . N
201 F23 C483 FinAdm_Con F23 N Construction....................................................................................................................
X . . . N
G23 C484 FinAdm_OCp F Other capital outlays.......................................................................................… G23=C482-F23; . . . N
Intergovernmental detail--
202 L23 C486 FinAdm_IGS L23 N To state government....................................................................................................................
X N . . N
203 M23 C487 FinAdm_IGL M23 N To local governments, total (includes N23, O23, P23, and R23).........................… X . . . N
204 -24 C493 Fire_Tot C493 N Fire Protection, Total.....................................................................................................................
X . . . .
DDD C494 Fire_IGE F Total intergovernmental..................................................................................................................
C494=C493-C495; . . . .
205 -24 C495 Fire_Dir C495 N Direct expenditure.......................................................................................................................
X . . . .
E24 C496 Fire_Opr F Current operations.....................................................................................................................
E24=C495-C497; . . . .
206 DDD C497 Fire_Cap C497 N Capital outlays........................................................................................................................
X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 22 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
207 F24 C498 Fire_Con F24 N Construction.........................................................................................................................
X . . . .
G24 C499 Fire_OCp F Other capital outlays................................................................................................................
G24=C497-F24; . . . .
Intergovernmental detail--
208 L24 C501 Fire_IGS L24 N To state government....................................................................................................................
X N . . .
209 M24 C502 Fire_IGL M24 N To local governments, total (includes N24, O24, P24, and R24).........................… X . . . .
210 -25 C508 Judic_Tot C508 N Judicial and Legal, Total.............................................................................................… X . . . N
DDD C509 Judic_IGE F Total intergovernmental..................................................................................................................
C509=C508-C510; . . . N
211 -25 C510 Judic_Dir C510 N Direct expenditure.......................................................................................................................
X . . . N
E25 C511 Judic_Opr F Current operations.............................................................................................… E25=C510-C512; . . . N
212 DDD C512 Judic_Cap C512 N Capital outlays........................................................................................................................
X . . . N
213 F25 C513 Judic_Con F25 N Construction.........................................................................................................................
X . . . N
G25 C514 Judic_OCp F Other capital outlays................................................................................................................
G25=C512-F25; . . . N
Intergovernmental detail--
214 L25 C516 Judic_IGS L25 N To state government....................................................................................................................
X N . . N
215 M25 C517 Judic_IGL M25 N To local governments, total (includes N25, O25, P25, and R25).........................… X . . . N
216 -29 C529 CStaff_Tot C529 N Central Staff Services, Total (includes any Legislative Activities, code -26)............................................ X . . . N
DDD C530 CStaff_IGE F Total intergovernmental..................................................................................................................
C530=C529-C531; . . . N
217 -29 C531 CStaff_Dir C531 N Direct expenditure.......................................................................................................................
X . . . N
E29 C532 CStaff_Opr F Current operations...........................................................................................… E29=C531-C533; . . . N
218 DDD C533 CStaff_Cap C533 N Capital outlays........................................................................................................................
X . . . N
219 F29 C534 CStaff_Con F29 N Construction.........................................................................................................................
X . . . N
G29 C535 CStaff_OCp F Other capital outlays................................................................................................................
G29=C533-F29; . . . N
Intergovernmental detail--
220 L29 C537 CStaff_IGS L29 N To state government....................................................................................................................
X N . . N
221 M29 C538 CStaff_IGL M29 N To local governments, total (includes N29, O29, P29, and R29).........................… X . . . N
222 -31 C551 GenBld_Tot C551 N General Public Buildings, Total..............................................................................… X . . . N
E31 C552 GenBld_Opr F Current operations.............................................................................................................E31=C551-C553; . . . N
223 DDD C553 GenBld_Cap C553 N Capital outlays...................................................................................................... X . . . N
224 F31 C554 GenBld_Con F31 N Construction....................................................................................................... X . . . N
G31 C555 GenBld_OCp F Other capital outlays........................................................................................................ G31=C553-F31; . . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 23 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
DDD C557 TotHltHosp F Health and Hospitals, Total.....................................................................................................C557=C562+C577; . . . .
DDD C559 DirHltHosp F Direct Expenditure............................................................................................................. C559=C564+C578; . . . .
DDD C561 HltHospCap F Capital outlays.............................................................................................................. C561=C566+C580; . . . .
225 -32 C562 Health_Tot C562 N Health, Total...........................................................................................................................
X . . . .
DDD C563 Health_IGE F Total intergovernmental........................................................................................................ C563=C562-C564; . . . .
226 -32 C564 Health_Dir C564 N Direct expenditure.............................................................................................................
X . . . .
E32 C565 Health_Opr F Current operations.................................................................................................… E32=C564-C566; . . . .
227 DDD C566 Health_Cap C566 N Capital outlays..............................................................................................................
X . . . .
228 F32 C567 Health_Con F32 N Construction...............................................................................................................
X . . . .
G32 C568 Health_OCp F Other capital outlays......................................................................................................G32=C566-F32; . . . .
Intergovernmental detail--
229 L32 C570 Health_IGS L32 N To state government..........................................................................................................
X N . . .
230 M32 C571 Health_IGL M32 N To local governments, total (includes N32, O32, P32, and R32).........................… X . . . .
231 DDD C577 Hosp_Tot C577 N Total Hospitals, Total.............................................................................................................
X . . . .
DDD C589 OthHos_IGE F Total intergovernmental (same as C589 below).......................................................… C589=C577-C578; . . . .
232 DDD C578 Hosp_Dir C578 N Direct expenditure.............................................................................................................
X . . . .
DDD C579 Hosp_Opr F Current operations.................................................................................................................
C579=C578-C580; . . . .
233 DDD C580 Hosp_Cap C580 N Capital Outlays..............................................................................................................
X . . . .
234 -36 C582 OwnHos_Tot C582 N Own Hospitals, Total.............................................................................................. X . . . .
E36 C583 OwnHos_Opr F Current operations.................................................................................................… E36=C582-C584; . . . .
235 DDD C584 OwnHos_Cap C584 N Capital outlays...................................................................................................... X . . . .
236 F36 C585 OwnHos_Con F36 N Construction....................................................................................................... X . . . .
G36 C586 OwnHos_OCp F Other capital outlays........................................................................................................ G36=C584-F36; . . . .
237 -38 C588 OthHos_Tot C588 N Other Hospitals, Total................................................................................................................
X . . . .
DDD C589 OthHos_IGE F Total intergovernmental........................................................................................................ C589=C588-C590; . . . .
238 -38 C590 OthHos_Dir C590 N Direct expenditure.............................................................................................................
X . . . N
E38 C591 OthHos_Opr F Current operations...............................................................................................… E38=C590-C592; . . . N
239 DDD C592 OthHos_Cap C592 N Capital outlays..............................................................................................................
X . . . N
240 F38 C593 OthHos_Con F38 N Construction...............................................................................................................
X . . . N
G38 C594 OthHos_OCp F Other capital outlays......................................................................................................G38=C592-F38; . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 24 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
Intergovernmental detail--.....................................................................................................
241 L38 C596 OthHos_IGS L38 N To state government..........................................................................................................
X N . . .
242 M38 C597 OthHos_IGL M38 N To local governments, total (includes N38, O38, P38, and R38).........................… X . . . .
243 DDD C603 TotHwy_Tot C603 N Total Highways, Total............................................................................................................
X . . . .
DDD C604 TotHwy_IGE F Total intergovernmental........................................................................................................ C604=C603-C605; . . . .
244 DDD C605 TotHwy_Dir C605 N Direct Expenditure.............................................................................................................
X . . . .
DDD C606 TotHwy_Opr F Current operations.............................................................................................… C606=C605-C607; . . . .
245 DDD C607 TotHwy_Cap C607 N Capital outlays..............................................................................................................
X . . . .
246 -44 C608 RegHwy_Tot C608 N Regular Highways, Total (includes Toll Highways prior to FY 1977).................................… X . . . .
DDD C609 RegHwy_IGE F Total intergovernmental........................................................................................................ C609=C608-C610; . . . .
247 -44 C610 RegHwy_Dir C610 N Direct expenditure.............................................................................................................
X . . . .
E44 C611 RegHwy_Opr F Current operations.......................................................................................… E44=C610-C612; . . . .
248 DDD C612 RegHwy_Cap C612 N Capital outlays..............................................................................................................
X . . . .
249 F44 C613 RegHwy_Con F44 N Construction...............................................................................................................
X . . . .
G44 C614 RegHwy_OCp F Other capital outlays......................................................................................................G44=C612-F44; . . . .
Intergovernmental detail--
250 L44 C616 RegHwy_IGS L44 N To state government.......................................................................................................…
X N . . .
251 M44 C617 RegHwy_IGL M44 N To local governments, total (includes N44, O44, P44, and R44).........................… X . . . .
252 -45 C623 TolHwy_Tot C623 N Toll Highways, Total (included in Regular Highways prior to FY 1977).................… X . . . N
E45 C626 TolHwy_Opr F Current operations...........................................................................................................E45=C623-C627; . . . N
253 DDD C627 TolHwy_Cap C627 N Capital outlays..............................................................................................................
X . . . N
254 F45 C628 TolHwy_Con F45 N Construction...............................................................................................................
X . . . N
G45 C629 TolHwy_OCp F Other capital outlays......................................................................................................G45=C627-F45; . . . N
255 -47 C650 TranSb_Tot C650 N Transit Subsidies, Total.........................................................................................................
X . . . .
DDD C651 TranSb_IGE C651=C650-E47;
F Total intergovernmental............................................................................................................... . . . .
256 E47 C652 TranSb_Dir E47 N Direct subsidies to private transit companies......................................................… X . . . .
Intergovernmental detail--
257 L47 C653 TranSb_IGS L47 N To state government (includes L94)..........................................................................… X N . . .
258 M47 C654 TranSb_IGL M47 N To local governments, total (includes N47, O47, P47, R47, and M94)......................… X . . . .
259 Z61 C659 TranSb_Own Z61 N Exhibit: Contribution to own transit system.........................................................… X N . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 25 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
260 -50 C660 HoCD_Tot C660 N Housing and Community Development, Total....................................................… X . . . .
DDD C661 HoCD_IGE F Total intergovernmental........................................................................................................ C661=C660-C662; . . . .
261 -50 C662 HoCD_Dir C662 N Direct expenditure.............................................................................................................
X . . . .
E50 C663 HoCD_Opr F Current operations...........................................................................................… E50=C662-C664; . . . .
262 DDD C664 HoCD_Cap C664 N Capital outlays..............................................................................................................
X . . . .
263 F50 C665 HoCD_Con F50 N Construction...............................................................................................................
X . . . .
G50 C666 HoCD_OCp F Other capital outlays......................................................................................................G50=C664-F50; . . . .
Intergovernmental detail--
264 L50 C668 HoCD_IGS L50 N To state government..........................................................................................................
X N . . .
265 M50 C669 HoCD_IGL M50 N To local governments, total (includes N50, O50, P50, and R50).........................… X . . . .
266 -52 C675 Libry_Tot C675 N Libraries, Total....................................................................................................... X . . . .
DDD C676 Libry_IGE F Total intergovernmental........................................................................................................ C676=C675-C677; . . . .
267 -52 C677 Libry_Dir C677 N Direct expenditure.............................................................................................................
X . . . .
E52 C678 Libry_Opr F Current operations.............................................................................................… E52=C677-C679; . . . .
268 DDD C679 Libry_Cap C679 N Capital outlays..............................................................................................................
X . . . .
269 F52 C680 Libry_Con F52 N Construction...............................................................................................................
X . . . .
G52 C681 Libry_OCp F Other capital outlays......................................................................................................G52=C679-F52; . . . .
Intergovernmental detail--
270 L52 C683 Libry_IGS L52 N To state government..........................................................................................................
X N . . .
271 M52 C684 Libry_IGL M52 N To local governments, total (includes N52, O52, P52, and R52).........................… X . . . .
. . .
272 -59 C740 NatRes_Tot C740 N Natural Resources, Total...................................................................................… X . . . .
DDD C741 NatRes_IGE F Total intergovernmental........................................................................................................ C741=C740-C742; . . . .
273 -59 C742 NatRes_Dir C742 N Direct expenditure.............................................................................................................
X . . . .
E59 C743 NatRes_Opr F Current operations.................................................................................................................
E59=C742-C744; . . . .
274 DDD C744 NatRes_Cap C744 N Capital outlays..............................................................................................................
X . . . .
275 F59 C745 NatRes_Con F59 N Construction...............................................................................................................
X . . . .
G59 C746 NatRes_OCp F Other capital outlays......................................................................................................G59=C744-F59; . . . .
Intergovernmental detail--
276 L59 C748 NatRes_IGS L59 N To state government..........................................................................................................
X N . . .
277 M59 C749 NatRes_IGL M59 N To local governments, total (includes N59, O59, P59, and R59).........................… X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 26 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
278 -60 C755 Parkg_Tot C755 N Parking Facilities, Total........................................................................................................
X . . . .
DDD C756 Parkg_IGE F Total intergovernmental........................................................................................................ C756=C755-C757; . . . .
279 -60 C757 Parkg_Dir C757 N Direct expenditure.............................................................................................................
X . . . .
E60 C758 Parkg_Opr F Current operations...........................................................................................................E60=C757-C759; . . . .
280 DDD C759 Parkg_Cap C759 N Capital outlays..............................................................................................................
X . . . .
281 F60 C760 Parkg_Con F60 N Construction...............................................................................................................
X . . . .
G60 C761 Parkg_OCp F Other capital outlays......................................................................................................G60=C759-F60; . . . .
Intergovernmental detail--
282 L60 C763 Parkg_IGS L60 N To state government..........................................................................................................
X N . . .
283 M60 C764 Parkg_IGL M60 N To local governments, total (includes N60, O60, P60, and R60).........................… X . . . .
284 -61 C770 PrkRec_Tot C770 N Parks and Recreation, Total......................................................................................................
X . . . .
DDD C771 PrkRec_IGE F Total intergovernmental........................................................................................................ C771=C770-C772; . . . .
285 -61 C772 PrkRec_Dir C772 N Direct expenditure.............................................................................................................
X . . . .
E61 C773 PrkRec_Opr F Current operations.............................................................................................… E61=C772-C774; . . . .
286 DDD C774 PrkRec_Cap C774 N Capital outlays..............................................................................................................
X . . . .
287 F61 C775 PrkRec_Con F61 N Construction...............................................................................................................
X . . . .
G61 C776 PrkRec_OCp F Other capital outlays......................................................................................................G61=C774-F61; . . . .
Intergovernmental detail--
288 L61 C778 PrkRec_IGS L61 N To state government..........................................................................................................
X N . . .
289 M61 C779 PrkRec_IGL M61 N To local governments, total (includes N61, O61, P61, and R61).........................… X . . . .
290 -62 C785 Police_Tot C785 N Police Protection, Total.........................................................................................................
X . . . N
DDD C786 Police_IGE F Total intergovernmental........................................................................................................ C786=C785-C787; . . . N
291 -62 C787 Police_Dir C787 N Direct expenditure.............................................................................................................
X . . . N
E62 C788 Police_Opr F Current operations...............................................................................................… E62=C787-C789; . . . N
292 DDD C789 Police_Cap C789 N Capital outlays..............................................................................................................
X . . . N
293 F62 C790 Police_Con F62 N Construction...............................................................................................................
X . . . N
G62 C791 Police_OCp F Other capital outlays......................................................................................................G62=C789-F62; . . . N
Intergovernmental detail--
294 L62 C793 Police_IGS L62 N To state government..........................................................................................................
X N . . N
295 M62 C794 Police_IGL M62 N To local governments, total (includes N62, O62, P62, and R62).........................… X . . . N
296 -66 C800 ProtRg_Tot C800 N Protective Inspection and Regulation, NEC..............................................................…X . . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 27 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
DDD C801 ProtRg_IGE F Total intergovernmental........................................................................................................ C801=C800-C802; . . . N
297 -66 C802 ProtRg_Dir C802 N Direct expenditure.............................................................................................................
X . . . N
E66 C803 ProtRg_Opr F Current operations...........................................................................................................E66=C802-C804; . . . N
298 DDD C804 ProtRg_Cap C804 N Capital outlays..............................................................................................................
X . . . N
299 F66 C805 ProtRg_Con F66 N Construction...............................................................................................................
X . . . N
G66 C806 ProtRg_OCp F Other capital outlays......................................................................................................G66=C804-F66; . . . N
Intergovernmental detail--
300 L66 C808 ProtRg_IGS L66 N To state government..........................................................................................................
X N . . N
301 M66 C809 ProtRg_IGL M66 N To local governments, total (includes N66, O66, P66, and R66).........................… X . . . N
302 DDD C815 Welf_Tot C815 N Public Welfare, Total............................................................................................................
X . . . .
DDD C816 Welf_IGE F Total intergovernmental........................................................................................................ C816=C815-C817; . . . .
303 DDD C817 Welf_Dir C817 N Direct Expenditure.............................................................................................................
X . . . .
DDD C818 Welf_Opr F Current operations...........................................................................................................C818=C817-C819-C820; . . . .
304 DDD C819 Welf_Asst C819 N Cash assistance payments................................................................................… X . . . .
305 DDD C820 Welf_Cap C820 N Capital outlays..............................................................................................................
X . . . .
306 -67 C821 Wel_Ct_Tot C821 N Public Welfare-Categorical Assistance Programs, Total..........................................…X . . . N
DDD C822 Wel_Ct_IGE C822=C821-E67;
F Total intergovernmental........................................................................................................ . . . N
307 E67 C823 Wel_Ct_AS E67 N Cash assistance payments.....................................................................................…X . . . N
Intergovernmental detail--
308 L67 C824 Wel_Ct_IGS L67 N To state government..........................................................................................................
X N . . N
309 M67 C825 Wel_Ct_IGL M67 N To local governments, total (includes N67, O67, P67, and R67).........................… X . . . N
S67 C830 Wel_Ct_Fed F To Federal Government........................................................................................................
S67=C821-E67-L67-M67; . . N N
310 -68 C831 Wel_Cs_Tot C831 N Public Welfare-Other Assistance Programs, Total.......................................................… X . . . N
DDD C832 Wel_Cs_IGE F Total intergovernmental (same as M68)..............................................................… C832=C831-E68; . . . N
311 E68 C833 Wel_Cs_AS E68 N Cash assistance payments.......................................................................................................
X . . . N
Intergovernmental detail--
312 M68 C835 Wel_Cs_IGL M68 N To local governments, total (includes N68, O68, P68, and R68).........................… X . . . N
DDD C3027 TotVendPmt C3027=E74+E75;
F Total Vendor Payments............................................................................................................ . . . N
313 E74 C841 Wel_Vn_Med E74 X
N For medical care............................................................................................................... . . . N
314 E75 C842 Wel_Vn_NEC E75 X
N For other purposes............................................................................................................. . . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 28 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
315 -77 C843 Wel_In_Tot C843 N Public Welfare-Institutions, Total............................................................................… X . . . N
E77 C846 Wel_In_Opr F Current operations...........................................................................................................E77=C843-C847; . . . N
316 DDD C847 Wel_In_Cap C847 N Capital outlays..............................................................................................................
X . . . N
317 F77 C848 Wel_In_Con F77 N Construction...............................................................................................................
X . . . N
G77 C849 Wel_In_OCp F Other capital outlays......................................................................................................G77=C847-F77; . . . N
318 -79 C858 OthWel_Tot C858 N Public Welfare-NEC, Total........................................................................................................
X . . . .
DDD C859 OthWel_IGE F Total intergovernmental........................................................................................................ C859=C858-C860; . . . .
319 -79 C860 OthWel_Dir C860 N Direct expenditure.............................................................................................................
X . . . .
E79 C861 OthWel_Opr F Current operations............................................................................................… E79=C860-C862; . . . .
320 DDD C862 OthWel_Cap C862 N Capital outlays..............................................................................................................
X . . . .
321 F79 C863 OthWel_Con F79 N Construction...............................................................................................................
X . . . .
G79 C864 OthWel_OCp F Other capital outlays......................................................................................................G79=C862-F79; . . . .
Intergovernmental detail--
322 L79 C866 OthWel_IGS L79 N To state government..........................................................................................................
X N . . .
323 M79 C867 OthWel_IGL M79 N To local governments, total (includes N79, O79, P79, and R79).........................… X . . . .
324 -80 C878 Sewer_Tot C878 N Sewerage, Total.............................................................................................................X . . . .
DDD C879 Sewer_IGE F Total intergovernmental........................................................................................................ C879=C878-C880; . . . .
325 -80 C880 Sewer_Dir C880 N Direct expenditure.............................................................................................................
X . . . .
E80 C881 Sewer_Opr F Current operations...........................................................................................................E80=C880-C882; . . . .
326 DDD C882 Sewer_Cap C882 N Capital outlays..............................................................................................................
X . . . .
327 F80 C883 Sewer_Con F80 N Construction...............................................................................................................
X . . . .
G80 C884 Sewer_OCp F Other capital outlays......................................................................................................G80=C882-F80; . . . .
Intergovernmental detail--
328 L80 C886 Sewer_IGS L80 N To state government..........................................................................................................
X N . . .
329 M80 C887 Sewer_IGL M80 N To local governments, total (includes N80, O80, P80, and R80).........................… X . . . .
330 -81 C893 SWMgmt_Tot C893 N Solid Waste Management, Total...................................................................................… X . . . .
DDD C894 SWMgmt_IGE F Total intergovernmental........................................................................................................ C894=C893-C895; . . . .
331 -81 C895 SWMgmt_Dir C895 N Direct expenditure.............................................................................................................
X . . . .
E81 C896 SWMgmt_Opr F Current operations...........................................................................................................E81=C895-C897; . . . .
332 DDD C897 SWMgmt_Cap C897 N Capital outlays..............................................................................................................
X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 29 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
333 F81 C898 SWMgmt_Con F81 N Construction...............................................................................................................
X . . . .
G81 C899 SWMgmt_OCp F Other capital outlays......................................................................................................G81=C897-F81; . . . .
Intergovernmental detail--
334 L81 C901 SWMgmt_IGS L81 N To state government..........................................................................................................
X N . . .
335 M81 C902 SWMgmt_IGL M81 N To local governments, total (includes N81, O81, P81, and R81).........................… X . . . .
336 -87 C916 WatTrn_Tot C916 N Water Transport and Terminals, Total........................................................................… X . . . .
DDD C917 WatTrn_IGE F Total intergovernmental........................................................................................................ C917=C916-C918; . . . .
337 -87 C918 WatTrn_Dir C918 N Direct expenditure.............................................................................................................
X . . . .
E87 C919 WatTrn_Opr F Current operations............................................................................................… E87=C918-C920; . . . .
338 DDD C920 WatTrn_Cap C920 N Capital outlays..............................................................................................................
X . . . .
339 F87 C921 WatTrn_Con F87 N Construction...............................................................................................................
X . . . .
G87 C922 WatTrn_OCp F Other capital outlays......................................................................................................G87=C920-F87; . . . .
Intergovernmental detail--
340 L87 C924 WatTrn_IGS L87 N To state government..........................................................................................................
X N . . .
341 M87 C925 WatTrn_IGL M87 N To local governments, total (includes N87, O87, P87, and R87).........................… X . . . .
342 I89 C932 GenIntExp I89 N Interest on General Debt.........................................................................................................
X . . . .
343 -89 C938 GenNEC_Tot C938 N General Expenditure NEC, Total (includes any amounts for codes -84 & -85)...................................... X . . . .
DDD C939 GenNEC_IGE F Total intergovernmental........................................................................................................ C939=C938-C940; . . . .
344 -89 C940 GenNEC_Dir C940 N Direct expenditure.............................................................................................................
X . . . .
E89 C941 GenNEC_Opr F Current operations (includes any amounts for code E84)......................................................… E89=C940-C942; . . . .
345 DDD C942 GenNEC_Cap C942 N Capital outlays..............................................................................................................
X . . . .
346 F89 C943 GenNEC_Con F89 N Construction...............................................................................................................
X . . . .
G89 C944 GenNEC_OCp F Other capital outlays......................................................................................................G89=C942-F89; . . . .
Intergovernmental detail--
347 L89 C946 GenNEC_IGS L89 N To state government (includes L91, L92, and L93)..........................................… X N . . .
348 M89 C947 GenNEC_IGL M89 N To local governments, total (incl N89, O89, P89, R89, M91, M92, and M93).........................… X . . . .
349 S89 C952 GenNEC_IGF S89 N To Federal Government........................................................................................................
X . . N N
LIQUOR STORES AND UTILITIES EXPENDITURES:
350 -90 C953 LiqStr_Tot C953 N Liquor Stores, Total..................................................................................................… X N . . N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 30 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
E90 C954 LiqStr_Opr F Current operations................................................................................................… E90=C953-C955; N . . N
351 DDD C955 LiqStr_Cap C955 N Capital outlays......................................................................................................… X N . . N
352 F90 C956 LiqStr_Con F90 N Construction....................................................................................................... X N . . N
G90 C957 LiqStr_OCp F Other capital outlays........................................................................................................ G90=C955-F90; N . . N
353 DDD C959 Util_Tot C959 N Total Utilities, Total...........................................................................................................
X . . . .
354 DDD C960 Util_Int C960 N Interest on debt...............................................................................................................
X . . . .
DDD C961 Util_Opr F Current operations.............................................................................................................C961=C959-C960-C962; . . . .
355 DDD C962 Util_Cap C962 N Capital outlays...................................................................................................... X . . . .
356 DDD C963 Util_Con C963 N Construction....................................................................................................... X . . . .
DDD C964 Util_OCp F Other capital outlays........................................................................................................ C964=C962-C963; . . . .
357 -91 C965 WatUtl_Tot C965 N Water Supply Utilities, Total...................................................................................… X . . . .
358 I91 C966 WatUtl_Int I91 N Interest on debt...............................................................................................................
X . . . .
E91 C967 WatUtl_Opr F Current operations.............................................................................................................E91=C965-I91-C968; . . . .
359 DDD C968 WatUtl_Cap C968 N Capital outlays...................................................................................................... X . . . .
360 F91 C969 WatUtl_Con F91 N Construction....................................................................................................... X . . . .
G91 C970 WatUtl_OCp F Other capital outlays........................................................................................................ G91=C968-F91; . . . .
361 -92 C974 EleUtl_Tot C974 N Electric Power Utilities, Total.................................................................................… X N . . .
362 I92 C975 EleUtl_Int I92 N Interest on debt...............................................................................................................
X N . . .
E92 C976 EleUtl_Opr F Current operations.............................................................................................................E92=C974-I92-C977; N . . .
363 DDD C977 EleUtl_Cap C977 N Capital outlays...................................................................................................... X N . . .
364 F92 C978 EleUtl_Con F92 N Construction....................................................................................................... X N . . .
G92 C979 EleUtl_OCp F Other capital outlays........................................................................................................ G92=C977-F92; N . . .
365 -93 C981 GasUtl_Tot C981 N Gas Supply Utilities, Total.......................................................................................… X N . . .
366 I93 C982 GasUtl_Int I93 N Interest on debt...............................................................................................................
X N . . .
E93 C983 GasUtl_Opr F Current operations.............................................................................................................E93=C981-I93-C984; N . . .
367 DDD C984 GasUtl_Cap C984 N Capital outlays...................................................................................................... X N . . .
368 F93 C985 GasUtl_Con F93 N Construction....................................................................................................... X N . . .
G93 C986 GasUtl_OCp F Other capital outlays........................................................................................................ G93=C984-F93; N . . .
369 -94 C988 TrnUtl_Tot C988 N Transit System Utilities, Total...............................................................................… X N . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 31 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
370 I94 C989 TrnUtl_Int I94 N Interest on debt...............................................................................................................
X N . . .
E94 C990 TrnUtl_Opr F Current operations.............................................................................................................E94=C988-I94-C991; N . . .
371 DDD C991 TrnUtl_Cap C991 N Capital outlays...................................................................................................... X N . . .
372 F94 C992 TrnUtl_Con F94 N Construction....................................................................................................... X N . . .
G94 C993 TrnUtl_OCp F Other capital outlays........................................................................................................ G94=C991-F94; N . . .
INSURANCE TRUST EXPENDITURE:
373 DDD C995 EmpRet_Tot C995 N Employee Retirement, Total.......................................................................................................
X . . . .
374 X11 C996 EmpRet_Ben X11 N Benefit payments...............................................................................................................
X . . . .
375 X12 C997 EmpRet_Wit X12 N Withdrawals............................................................................................................... X . . . .
376 X14 C999 EmpRet_Oth X14 N Other payments (Exhibit item-not included in C995)..............................................… X . . . .
377 DDD C1000 Unemp_Tot C1000 N Unemployment Compensation, Total (Washington DC only for local govts)..........................................… X . N N N
378 Y05 C1001 Unemp_Ben Y05 N Benefit payments...............................................................................................................
X . N N N
379 Y06 C1002 Unemp_Ext Y06 N Extended and special payments..............................................................................… X . N N N
*** INDEBTEDNESS ***
Note: The "All other general functions, NEC" variables below include all
obsolete general categories. For example, variable "_44X" includes former
codes 44E, 44J, 44K, 44M, 44N, 44P, and 44S. These codes became
obsolete after FY 1987.
380 DDD C1203 TotDebtOS C1203 N Total Debt Outstanding at End of Fiscal Year................................................................… X . . . .
381 DDD C1204 LTDebtOS C1204 N Long-term only....................................................................................................... X . . . .
382 64V C1205 ST_DebtOS _64V N Short-term only...................................................................................................... X . . . .
Long-Term Debt Outstanding at Beginning of Fiscal Year:
383 19- C1221 BegOS_Tot C1221 N Total.......................................................................................................………….. X . . . .
384 DDD C1222 BegOS_Utl C1222 N Utilities, total............................................................................................................ X N N . .
385 19A C1223 BegOS_Wat _19A N Water supply.............................................................................................................. X N N . .
386 19B C1224 BegOS_Ele _19B N Electric power............................................................................................................ X N N . .
387 19C C1225 BegOS_Gas _19C N Gas supply...................................................................................................... X N N . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 32 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
388 19D C1226 BegOS_Trn _19D N Transit systems...........................................................................................................
X N N . .
389 DDD C1227 BegOS_Gen C1227 N General, total..............................................................................................................
X . . . .
390 19H C1228 BegOS_Ed _19H N Education, NEC............................................................................................................
X N N . .
391 19T C1695 BegOS_PDPP _19T N Public debt for private purposes (includes 19W)...............................................… X N N . .
392 19X C1231 BegOS_NEC _19X N All other general functions, NEC..................................................................... X . . . .
Total Long-Term Debt Issued During Fiscal Year (all types):
393 2-- C1232 TotIss_Tot C1232 N Total.......................................................................................................…………………. X . . . .
394 DDD C1233 TotIss_Utl C1233 N Utilities, total............................................................................................................ X . . . .
395 2-A C1234 TotIss_Wat C1234 N Water supply.............................................................................................................. X . . . .
396 2-B C1235 TotIss_Ele C1235 N Electric power............................................................................................................ X N . . .
397 2-C C1236 TotIss_Gas C1236 N Gas supply...................................................................................................... X N . . .
398 2-D C1237 TotIss_Trn C1237 N Transit systems........................................................................................................... X N . . .
399 DDD C1238 TotIss_Gen C1238 N General, total.............................................................................................................. X . . . .
DDD C1240 TotIss_Ed F Education, total.......................................................................................................... C1240=C1241+C1242; . . . .
400 2-F C1241 TotIss_ES C1241 N Elementary and secondary education.........................................................… X . . . .
401 2-G C1242 TotIss_OEd C1242 N Higher and other education (includes 2-H).............................………………… X . . . .
402 2-X C1253 TotIss_NEC C1253 N All other general functions, NEC (includes 24T)........................................................… X . . . .
Long-Term Debt Issued, Full-Faith and Credit (Note: Also includes
Unspecified Debt issued):
403 21/29- C1255 FFCIss_Tot C1255 N Total.......................................................................................................…………. X . . . .
404 DDD C1256 FFCIss_Utl C1256 N Utilities, total............................................................................................................ X . . . .
405 21/29A C1257 FFCIss_Wat C1257 N Water supply.............................................................................................................. X . . . .
406 21/29B C1258 FFCIss_Ele C1258 N Electric power............................................................................................................ X N . . .
407 21/29C C1259 FFCIss_Gas C1259 N Gas supply...................................................................................................... X N . . .
408 21/29D C1260 FFCIss_Trn C1260 N Transit systems........................................................................................................... X N . . .
409 DDD C1261 FFCIss_Gen C1261 N General, total.............................................................................................................. X . . . .
DDD C1263 FFCIss_Ed F Education, total.......................................................................................................... C1263=C1264+C1265; . . . .
410 21/29F C1264 FFCIss_ES C1264 N Elementary and secondary education................................................................… X . . . .
411 21/29G C1265 FFCIss_OEd C1265 N Higher and other education (includes 21/29H).............................……………. X . . . .
412 21/29X C1276 FFCIss_NEC C1276 N All other general functions, NEC.......................................................................… X . . . .
Long-Term Debt Issued, Nonguaranteed:
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 33 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
413 24- C1323 NGIss_Tot C1323 N Total.......................................................................................................………… X . . . .
414 DDD C1324 NGIss_Util C1324 N Utilities, total............................................................................................................ X . . N N
415 24A C1325 NGIss_Wat _24A N Water supply.............................................................................................................. X . . N N
416 24B C1326 NGIss_Ele _24B N Electric power............................................................................................................ X N . N N
417 24C C1327 NGIss_Gas _24C N Gas supply...................................................................................................... X N . N N
418 24D C1328 NGIss_Trn _24D N Transit systems........................................................................................................... X N . N N
419 DDD C1329 NGIss_Gen C1329 N General, total.............................................................................................................. X . . . .
DDD C1331 NGIss_Ed F Education, total.......................................................................................................... C1331=_24F+_24G; . . N .
420 24F C1332 NGIss_ES _24F N Elementary and secondary education................................................................… X . . N .
421 24G C1333 NGIss_OtEd _24G N Higher and other education (includes 24H).............................………………. X . . N .
422 24T C1696 NGIss_PDPP _24T N Public debt for private purposes (includes 24W)...............................................… X . . . .
423 24X C1346 NGIss_NEC _24X N All other general functions, NEC.........................................................................…X . . N N
Long-Term Debt Issued, Unspecified (Note: Also included in Full-Faith and
Credit debt issued):
424 29- C1347 UnsIss_Tot C1347 N Total.......................................................................................................……….. X N N . .
425 DDD C1348 UnsIss_Utl C1348 N Utilities, total............................................................................................................ X N N . .
426 29A C1349 UnsIss_Wat _29A N Water supply.............................................................................................................. X N N . .
427 29B C1350 UnsIss_Ele _29B N Electric power............................................................................................................ X N N . .
428 29C C1351 UnsIss_Gas _29C N Gas supply...................................................................................................... X N N . .
429 29D C1352 UnsIss_Trn _29D N Transit systems........................................................................................................... X N N . .
430 DDD C1353 UnsIss_Gen C1353 N General, total.............................................................................................................. X N N . .
DDD C1355 UnsIss_Ed F Education, total.......................................................................................................... C1355=_29F+_29G; N N . .
431 29F C1356 UnsIss_ES _29F N Elementary and secondary education.................................................................… X N N . .
432 29G C1357 UnsIss_OEd _29G N Higher and other education (includes 29H).............................…………………. X N N . .
433 29X C1368 UnsIss_NEC _29X N All other general functions, NEC..........................................................................… X N N . .
Total Long-Term Debt Retired During Fiscal Year (all types):
434 3-- C1401 TotRet_Tot C1401 N Total.......................................................................................................……….. X . . . .
435 DDD C1402 TotRet_Utl C1402 N Utilities, total............................................................................................................ X . . . .
436 3-A C1403 TotRet_Wat C1403 N Water supply.............................................................................................................. X . . . .
437 3-B C1404 TotRet_Ele C1404 N Electric power............................................................................................................ X N . . .
438 3-C C1405 TotRet_Gas C1405 N Gas supply...................................................................................................... X N . . .
439 3-D C1406 TotRet_Trn C1406 N Transit systems........................................................................................................... X N . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 34 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
440 DDD C1407 TotRet_Gen C1407 N General, total..............................................................................................................
X . . . .
DDD C1409 TotRet_Ed F Education, total.......................................................................................................... C1409=C1410+C1411; . . . .
441 3-F C1410 TotRet_ES C1410 N Elementary and secondary education...............................................................…X . . . .
442 3-G C1411 TotRet_OEd C1411 N Higher and other education (includes 3-H).............................…………………. X . . . .
443 3-X C1422 TotRet_NEC C1422 N All other general functions, NEC (includes 34T)......................................................… X . . . .
Long-Term Debt Retired, Full-Faith and Credit (Note: Also includes
Unspecified Debt retired):
444 31/39- C1424 FFCRet_Tot C1424 N Total.......................................................................................................……….. X . . . .
445 DDD C1425 FFCRet_Utl C1425 N Utilities, total............................................................................................................ X . . . .
446 31/39A C1426 FFCRet_Wat C1426 N Water supply.............................................................................................................. X . . . .
447 31/39B C1427 FFCRet_Ele C1427 N Electric power............................................................................................................ X N . . .
448 31/39C C1428 FFCRet_Gas C1428 N Gas supply...................................................................................................... X N . . .
449 31/39D C1429 FFCRet_Trn C1429 N Transit systems........................................................................................................... X N . . .
450 DDD C1430 FFCRet_Gen C1430 N General, total.............................................................................................................. X . . . .
DDD C1432 FFCRet_Ed F Education, total.......................................................................................................... C1432=C1433+C1434; . . . .
451 31/39F C1433 FFCRet_ES C1433 N Elementary and secondary education................................................................… X . . . .
452 31/39G C1434 FFCRet_OEd C1434 N Higher and other education (includes 31/39H).............................………………… X . . . .
453 31/39X C1445 FFCRet_NEC C1445 N All other general functions, NEC.............................................................................… X . . . .
Long-Term Debt Retired, Nonguaranteed:
454 34- C1492 NGRet_Tot C1492 N Total.......................................................................................................……….. X . . . .
455 DDD C1493 NGRet_Util C1493 N Utilities, total............................................................................................................ X . . N N
456 34A C1494 NGRet_Wat _34A N Water supply.............................................................................................................. X . . N N
457 34B C1495 NGRet_Ele _34B N Electric power............................................................................................................ X N . N N
458 34C C1496 NGRet_Gas _34C N Gas supply...................................................................................................... X N . N N
459 34D C1497 NGRet_Trn _34D N Transit systems........................................................................................................... X N . N N
460 DDD C1498 NGRet_Gen C1498 N General, total.............................................................................................................. X . . . .
DDD C1500 NGRet_Ed F Education, total.......................................................................................................... C1500=_34F+_34G; . . N .
461 34F C1501 NGRet_ES _34F N Elementary and secondary education................................................................… X . . N .
462 34G C1502 NGRet_OtEd _34G N Higher and other education (includes 34H).............................…………………. X . . N .
463 34T C1697 NGRet_PDPP _34T N Public debt for private purposes (includes 34W)...............................................… X . . . .
464 34X C1515 NGRet_NEC _34X N All other general functions, NEC.......................................................................… X . . N N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 35 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
Long-Term Debt Retired, Unspecified (Note: Also included in Full-Faith and
Credit debt retired):
465 39- C1516 UnsRet_Tot C1516 N Total.......................................................................................................……….. X N N . .
466 DDD C1517 UnsRet_Utl C1517 N Utilities, total............................................................................................................ X N N . .
467 39A C1518 UnsRet_Wat _39A N Water supply.............................................................................................................. X N N . .
468 39B C1519 UnsRet_Ele _39B N Electric power............................................................................................................ X N N . .
469 39C C1520 UnsRet_Gas _39C N Gas supply...................................................................................................... X N N . .
470 39D C1521 UnsRet_Trn _39D N Transit systems........................................................................................................... X N N . .
471 DDD C1522 UnsRet_Gen C1522 N General, total.............................................................................................................. X N N . .
DDD C1524 UnsRet_Ed F Education, total.......................................................................................................... C1524=_39F+_39G; N N . .
472 39F C1525 UnsRet_ES _39F N Elementary and secondary education...................................................................… X N N . .
473 39G C1526 UnsRet_OEd _39G N Higher and other education (includes 39H).............................……………………….. X N N . .
474 39X C1537 UnsRet_NEC _39X N All other general functions, NEC.........................................................................…X N N . .
Long-Term Debt Outstanding, Total (see C1204 above):
475 DDD C1571 TotOut_Utl C1571 N Utilities, total.........................................................................................................… X . . . .
476 4-A C1572 TotOut_Wat C1572 N Water supply..............................................................................................................X . . . .
477 4-B C1573 TotOut_Ele C1573 N Electric power............................................................................................................X N . . .
478 4-C C1574 TotOut_Gas C1574 N Gas supply...................................................................................................... X N . . .
479 4-D C1575 TotOut_Trn C1575 N Transit systems...........................................................................................................X N . . .
480 DDD C1576 TotOut_Gen C1576 N General, total..............................................................................................................
X . . . .
DDD C1578 TotOut_Ed F Education, total.......................................................................................................... C1578=C1579+C1580; . . . .
481 4-F C1579 TotOut_ES C1579 N Elementary and secondary education................................................................… X . . . .
482 4-G C1580 TotOut_OEd C1580 N Higher and other education (includes 4-H).............................……………………….. X . . . .
483 4-X C1591 TotOut_NEC C1591 N All other general functions, NEC (includes 44T).................................................................… X . . . .
Long-Term Debt Outstanding, Full-Faith and Credit:
484 41- C1601 FFCOut_Tot C1601 N Total.......................................................................................................……….. X . . . .
485 DDD C1602 FFCOut_Utl C1602 N Utilities, total............................................................................................................ X . . . .
486 41A C1603 FFCOut_Wat _41A N Water supply.............................................................................................................. X . . . .
487 41B C1604 FFCOut_Ele _41B N Electric power............................................................................................................ X N . . .
488 41C C1605 FFCOut_Gas _41C N Gas supply...................................................................................................... X N . . .
489 41D C1606 FFCOut_Trn _41D N Transit systems........................................................................................................... X N . . .
490 DDD C1607 FFCOut_Gen C1607 N General, total.............................................................................................................. X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 36 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
DDD C1609 FFCOut_Ed F Education, total.......................................................................................................... C1609=_41F+_41G; . . . .
491 41F C1610 FFCOut_ES _41F N Elementary and secondary education..................................................................… X . . . .
492 41G C1611 FFCOut_OEd _41G N Higher and other education (includes 41H).............................……………………….. X . . . .
493 41X C1622 FFCOut_NEC _41X N All other general functions, NEC.............................................................................… X . . . .
Long-Term Debt Outstanding, Nonguaranteed:
494 44- C1669 NGOut_Tot C1669 N Total.......................................................................................................……….. X . . . .
495 DDD C1670 NGOut_Util C1670 N Utilities, total............................................................................................................ X . . . .
496 44A C1671 NGOut_Wat _44A N Water supply.............................................................................................................. X . . . .
497 44B C1672 NGOut_Ele _44B N Electric power............................................................................................................ X N . . .
498 44C C1673 NGOut_Gas _44C N Gas supply...................................................................................................... X N . . .
499 44D C1674 NGOut_Trn _44D N Transit systems........................................................................................................... X N . . .
500 DDD C1675 NGOut_Gen C1675 N General, total.............................................................................................................. X . . . .
DDD C1677 NGOut_Ed F Education, total.......................................................................................................... C1677=_44F+_44G; . . . .
501 44F C1678 NGOut_ES _44F N Elementary and secondary education..................................................................… X . . . .
502 44G C1679 NGOut_OtEd _44G N Higher and other education (includes 44H).............................……………………….. X . . . .
503 44T C1698 NGOut_PDPP _44T N Public debt for private purposes (includes 44W)...............................................… X . . . .
504 44X C1692 NGOut_NEC _44X N All other general functions, NEC...........................................................................… X . . . .
*** CASH AND SECURITIES ***
505 DDD C1801 TotCashSec C1801 N All Funds Cash and Securities (insurance and noninsurance) .............……………… X . . . .
506 DDD C1809 InsTr_CSc C1809 N Insurance Trust Funds Only Cash and Securities, Total...................................................…
X . . . .
Employee Retirement Systems:
507 X-- C1817 EmpR_CSc C1817 N Total cash and securities..................................................................................… X . . . .
508 X21 C1818 EmpR_Cash X21 N Cash and deposits ........................................................................................… X . . . .
509 DDD C1819 EmpR_TotSc C1819 N Securities, total ..............................................................................................… X . . . .
510 DDD C1820 EmpR_FdSec C1820 N Federal securities, total (Note: Includes X30 and X33)..............................… X . . . .
511 X35 C1823 EmpR_SLSec X35 N State & local govt (Note: Included in X44 after FY87).............................… X . . . .
512 DDD C1824 EmpR_NonGv C1824 N Nongovernmental securities, NEC................................................................… X . . . .
513 X40 C1825 EmpR_CpBds X40 N Corporate bonds................................................................………………….. X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 37 of 209
2. Annotated Guide to Variables in the Historical Finance Data Base (IndFin)
11-Apr-2001
Is variable a data field Local government
S2K SAS T - or - data collection coverage:
Fin. Comp. SAS Label/ Variable y must it be calculated? Other Spec
# Code # DBF Name Name p Full Name Field SAS Formula DC Jacket GenP Dist.
(A) (B) (C) (D) (E) e (G) (H) (I) (J) (K) (L) (M)
514 X41 C1826 EmpR_CpStk X41 N Corporate stock.............................................................................................… X . . . .
515 X42 C1827 EmpR_Mortg X42 N Mortgages...................................................................................................… X . . . .
516 X47 C1880 EmpR_Misc X47 N Miscellaneous investments (Note: Added in FY 88)..................................… X . . . .
517 X44 C1828 EmpR_Other X44 N Other (includes X35 after FY 87)..............................................................…… X . . . .
Unemployment Compensation Funds (Washington DC only for local govts):
518 DDD C1829 Unemp_CSc C1829 N Total cash and securities.................................................................................… X . N N N
519 Y07 C1830 Unemp_Bal Y07 N Balance held in U.S. Treasury.......................................................................… X . N N N
520 Y08 C1831 Unemp_Oth Y08 N Other balances (can be positive or negative)................................................… X . N N N
521 DDD C1848 NonIns_CSc C1848 N Other Than Insurance Trusts Holdings Cash and Securities, Total..............................…
X . . . .
522 DDD C1856 Sink_CSc C1856 N Sinking Funds (debt service funds) Cash and Securities………………………………….
X . . . .
523 DDD C1864 Bond_CSc C1864 N Bond Funds Cash and Securities........................................................................… X . . . .
524 DDD C1872 Other_CSc C1872 N All Other Noninsurance Funds Cash and Securities..............................................… X . . . .
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 38 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 39 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 40 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
.
.
.
.
.
.
.
.
.
.
.
.
.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 41 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
.
N
.
.
.
.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 42 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
.
N
.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 43 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 44 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 2 2 1 2 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 0 1 1 1 2 2 2 2 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 45 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N
N 0 0 0 1 2 0 0 0 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1
N 2 2 2 2 2 2 2 2 2 2 0 1 1 1 1 1 0 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 1 1 1 2 1 1 1
N 1 1 1 1 1 1 1 1 2 1 2 1 2 2 2 2 2 2 2 1 2 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 0 0 0 0 0 0 0 0 2 0 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 0 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 46 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 2 1 1 1 1 2 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 47 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 48 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
. 1 1 1 1 1 1 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 2 2
. 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 49 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 0 0 0 0 0
N
N 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 50 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N
N 1 1 1 1 1 1 1 1 1 2 2 2 2 1 1 1 2 1 1 1 2 2 1 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 1 1 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 0 0 2 2 2 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 1 1 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 0 0 1
. 2 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 51 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 1 1
N
N 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 1 1 1 1 1 1 1
N
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 1
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1
N
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 1 1 1 0 0 0 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1
N
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 52 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 0 0 0 0 0 0 0 0
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 1 1 1
N 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 53 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N
N
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 0 1 1 1 1 1 1 1 1
N
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 54 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
N
N 2 1 1 1 1 2 1 1 1 2 2 2 2 2 2 2 1 1 1 1 2 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 55 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 56 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 57 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0
N 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N
N 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 58 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 1 1 1 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 1 1 1 1 2 1 1 1 1 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 59 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 2 1 1 1
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 2 1 1 1 1 2 1 1 1
N
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 60 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N
N 2 1 1 1 1 2 1 1 1 1 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1
N 1 0 0 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 61 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 1 1 1 2 2 2 1 1 1 1 2 1 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1
N
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1
N
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
. 0 0 0 0 0 0 0 0 1 1 2 1 1 1 1 1 1 2 2 2 2 1 1 1 0 2 1 1 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
N 2 1 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 62 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 1 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 1 0 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 1 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 1 0 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 63 of 209
Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 0 0 0 1 1 0 1 1 1 0 1 1 1 0 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0
N 0 0 0 0 1 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1
.
. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1
. 0 0 0 0 0 1 1 1 0 0 1 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 1 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 1 2 0 0 0 0 0 0 0 0
. 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 2 2 2 2 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
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Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 0 0 0 1 0 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 0 0 0 1 0 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 2 2 2 2 2 2 2 2 2
.
. 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 2 2 2 2 2 2 2 2 2
. 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0
N 1 1 1 1 1 2 2 2 2 1 1 1 1 1 1 1 1 1 1 2 2 0 0 0 0 0 0 0 0
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Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 2 2 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 2 2 2 2 2 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 1 1 2 2 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
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Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 1 1 1 1 1 1 1 1 1 1 2 2 2 2 1 2 2 2 2 2 2 1 1 1 1 1 1 1 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
N 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
.
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 1 2 2 2 2 2 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0
N 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
. 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 1 1 0 2 1 1 2
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Local government Number of governments reporting data for variable, by survey year
data collection coverage: (0 = None 1 = From 1 to 100 governments 2 = Over 100 governments)
Sch (O)
Dist. FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY FY
(N) 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 67
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 1 1 1 0 2 1 1 2
. 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 2 1 1 2
. 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 2 1 1 2
N 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
N 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
. 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
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Extended
data
notes
(P)
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Extended
data
notes
(P)
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Extended
data
notes
(P)
Maximum # of ID changes is 2 for any one government.
Reliability of data not verified. Variety of coding schemes used over time.
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Extended
data
notes
(P)
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Extended
data
notes
(P)
No county jacket units prior to FY 1973. Codes mostly based on units published.
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Extended
data
notes
(P)
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Extended
data
notes
(P)
Includes any spurious data for T11 (none for FY 1967 - 97).
Includes any spurious data for T21, T23, or T27 (none for FY 1967 - 97).
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Extended
data
notes
(P)
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Extended
data
notes
(P)
For pre-77 data, values of 1 (or 2) may be have been generated by calculation method.
Prior to FY 1974, expenditures for category were included in function -89.
No data reported for A21 for 1967 - 1997.
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Extended
data
notes
(P)
Includes any spurious data for U50 (83 records reported it for FY 1967 - 97).
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Extended
data
notes
(P)
Includes old "H" salaries and wages codes.
UserGuide.Xls (2. Variables) Print version does not show all columns (including extended data notes). Page 79 of 209
Extended
data
notes
(P)
Includes old "H" salaries and wages codes.
Included in code -89 prior to FY 1974.
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Extended
data
notes
(P)
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data
notes
(P)
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data
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(P)
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data
notes
(P)
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Extended
data
notes
(P)
Represents code -46 prior to FY 1977.
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Extended
data
notes
(P)
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Extended
data
notes
(P)
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Extended
data
notes
(P)
Between 1967 and 1997, only 1 govt reported S67 (New York City, 1979).
Code L68 does not exist. Although "legal" for locals, M68 never reported.
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Extended
data
notes
(P)
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(P)
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Extended
data
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(P)
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Extended
data
notes
(P)
For pre-77 data, values of 1 (or 2) may be have been generated by calculation method.
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Extended
data
notes
(P)
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(P)
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Extended
data
notes
(P)
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Extended
data
notes
(P)
For pre-77 data, values of 1 (or 2) may be have been generated by calculation method.
For pre-77 data, values of 1 (or 2) may be have been generated by calculation method.
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Extended
data
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(P)
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Go to Contents
3. Latest Version Number For Each Year
As of: 16-July-2001
This document shows the latest release number for each data file in the historical data base
on individual local government finances. The most current version is indicated by a date under
that column. (# column indicates a footnote.)
Version number and release date
Survey A B C D E F G
Year Date # Date # Date # Date # Date # Date # Date #
1999 7/18/01
1998 4/11/01
1997 8/17/00 2/26/01 3
1996 9/01/99
1995 9/01/99
1994 9/01/99 8/30/00 2
1993 9/01/99 8/30/00 2
1992 9/01/99
1991 9/01/99 8/30/00 2
1990 9/01/99 8/30/00 2
1989 9/01/99 8/30/00 2
1988 9/01/99 8/30/00 2
1987 9/01/99 8/30/00 2
1986 9/01/99
1985 9/01/99
1984 9/01/99
1983 9/01/99
1982 9/01/99
1981 9/01/99
1980 9/01/99
1979 9/01/99
1978 9/01/99
1977 9/01/99
1976 9/01/99
1975 9/01/99
1974 9/01/99
1973 9/01/99
1972 9/01/99
1971 9/01/99
1970 9/01/99
1967 9/01/99
FedState 9/08/00
IDxWalk 9/01/99
ALLIDs 9/01/99 1
Release Notes:
1 - This file is updated annually.
2 - Removed educational service agencies (ESAs), which are not independent governmental entities.
3 - Updated with latest version of individual unit file (dated 1-29-2001).
UserGuide.Xls (3. Versions) 1/5/2013
Go to Contents
4. Guide to Reference Tables in the Data Base (ALLIds and IDxWalk)
As of: 16-July-2001
In addition to data files, the "IndFin" historical data base has two reference tables (click
on the table name below for a detailed description):
1. ALLIds (IndFin.ALLIds)
Consists of all unique government ID numbers in the data base and the earliest
and latest survey years for which data are available.
2. IDxWalk (IndFin.IDxWalk)
Consists of governments whose ID numbers have changed since 1967. It provides
a crosswalk between these governments' current ID and all their previous IDs.
ALLIds (IndFin.ALLIds)
This reference table lists all 103,707 unique government ID numbers in the data base.
It has one record for each ID. It is updated annually when data for the latest survey
year are added. Note that there are nearly 9,000 ID numbers in this data base
that are not in the current Governments Integrated Directory (GID).
For any government whose ID number was changed during the period covered by the
data base, the most current ID number is shown in this table. For information
on previous IDs for these governments, see the IDxWalk reference table.
# SAS Name Type Description
1 ID C Current GOVS identification number (9-digit)
2 IdChged N Indicates how many times ID number has changed since 1967
Same as IdxWalk's "TotIDChg" variable
3 State C 2-digit GOVS state code (00, 01, 02, 21, 36, 50, etc.)
4 Type C 1-digit type of government code
5 County C 3-digit GOVS county code (001, 002, etc.)
6 Name C Name of government (generally, from latest year in data base)
7 Cen_Reg C Census region code
8 FIPS_ST C FIPS state code
9 Version C Data base version (always "A" for this reference table)
10 JackFlag C Jacket unit flag
1 = Unit was jacket unit for at least one survey period
11 ZeroFlag C Blank (zero-filled) record flag
1 = All variables are zero for one or more years in the data base
12 Pop N Population/enrollment/function code (for latest year available)
13 FirstYr N Indicates the first survey year for which data are available*
14 LastYr N Indicates the latest survey year for which data are available*
15 IncDate C Incorporation date (from GID - updated annually)
16 Disinc C Disincorporation date (from GID - updated annually)
UserGuide.Xls (4. Reference) Page 100 of 209
4. Guide to Reference Tables in the Data Base (ALLIds and IDxWalk)
As of: 16-July-2001
* Does not indicate whether data for all survey years between these two dates are available.
IDxWalk (IndFin.IDxWalk)
While most government ID numbers prove to be permanent, there are situations
that result in an ID number being changed. Some government IDs were changed
more than once! The IndFin data base uses a government's current ID number.
Any change to its ID number is indicated by a value in the "IDChged" variable.
This reference table (IDxWalk) lists all the governments identified as having their
ID number changed since 1967. It provides a crosswalk between these
governments' current ID and all previous IDs. To link this table
to any data table, use the ID variable.
# SAS Name Type Description
1 ID C Current GOVS identification number (9-digit)
2 OldID C ID number prior to change
3 IDChgNum N Sequence number of the ID change (1 = first time ID changed)
4 TotIDChg N Total number of ID changes for that government. This number
is the same as the "IdChged" field in the data base.
5 Reused N Indicates if OldId has been re-assigned to another government:
0 = No 1 = Yes
2 = County code part of OldID has been reused
6 Name C Name of government (generally, from latest year in data base)
7 Version C Data base version (initial release is A)
8 JackFlag C Jacket unit flag
1 = Unit was jacket unit for at least one survey period
9 FirstYr N First year OldID used in data base (i.e., oldest)
10 LastYr N Most recent year OldID used in data base (i.e., latest)
11 AddDate C Date record was added to this table
12 DBFixed C Date data base was fixed to replace OldID with current ID
13 Reason N Code indicating reason for ID change (see below)
14 Annotate C Explanatory notes
Reason for ID Change Codes:
1 = Alaska global ID changes in FY 1982 Census of Governments*
2 = New county creation
3 = Independent city creation/dissolution
4 = Change in county where special district headquartered
99 = Unknown
* Computer staff also revised IDs in source files for fiscal years 1981 and 1980.
NOTES:
This reference table excludes ID changes that were the result of these events:
City-county consolidations
School district mergers
Change in type of government (e.g., township that converted to a city government)
UserGuide.Xls (4. Reference) Page 101 of 209
4. Guide to Reference Tables in the Data Base (ALLIds and IDxWalk)
As of: 16-July-2001
Other structural changes that result in an ID change
UserGuide.Xls (4. Reference) Page 102 of 209
Go to Contents
5. Important Data Use
Putting These Data User Notes into Perspective: An Overview
1. Introducing...The Historical Finance Data Base of Individual Lo
2. Standardizing the Presentation of Historical Data
3. Other Members of the Historical Finance Data Base Series
4. Data Are Provided (Largely) "As Is"
5. Number of Records
6. Government Name Problems
7. School District Enrollment Issues--FY 1974-1976, 1978, and 19
8. Statistical Weight Issues--FY 1967, 1970, 1971, 1973, and 199
9. Employee Retirement Issues--FY 1967 to 1976
10. Government ID Changes
11. Other Data Anomalies
12. Records with No Data
13. Data Revisions
14. Substitution of Data Using Public-Use Files (FY 1981 and 1983
15. Meaning of "DataFlag" Codes
16. "Jacket" Units (Largest Cities and Counties)
17. Year of Population Data
18. Information to Provide Outside Data Users
19. A Note on Federal and State Government Records
20. Miscellaneous FAQs
These data user notes focus on limitations, problems, and anomalie
give false impressions regarding the overall quality of the data. Thi
items. Despite the problems and limitations listed here, the vast ma
be released after spending years, even decades, locked up in a tap
Perhaps the most amazing aspect of these historical data is that the
encountered was the inability to read the old data files. This is a trib
from computer staffs at both the Census Bureau and the National A
So, do not hesitate to explore the data base--but be sure to look ou
Note: In this document, terms like "fiscal 1988" or "FY 1988" refer to
1. Introducing...The Historical Finance Data Base of Individual
For the first time, historical data on individual local government finan
This SAS data base, called "IndFin," covers data for fiscal years 19
data base include:
- It comprises over one million individual local government records
districts, and independent school districts.
- It has 524 variables, including:
115 revenue items
242 expenditure items
125 debt items (issued, retired, and outstanding)
20 cash and securities items
It also contains 22 general reference data like population, school
UserGuide.Xls (5. User Notes) 103 of 209
5. Important Data Use
- It includes not only individual finance codes but also dozens of to
Revenues" to "Highways Capital Outlay."
- In addition to its 524 variables, the data base is designed so that
derived by adding or subtracting two variables (e.g., current oper
- An easy-to-use application is available to query the data base an
Return to top
2. Standardizing the Presentation of Historical Data
The nearly 30 year span covered by this data base saw numerous c
The Census Bureau employed different electronic record formats (e
classification changes, revised the meaning of finance codes, and a
major impact on the electronic data. Previously, a user interested in
ment finances had to obtain electronic data from three different sou
reconcile all these changes.
A major goal of this data base was to present data in an historically
- All source files were converted to a standardized format. Source
1967 to 1977); the 1200-word record (fiscal years 1977 to 1986);
to 1991); and the latest "item code" format. Thus, no matter whe
file, it is always located in the same spot in this data base.
- Unlike public-use files issued between fiscal years 1977 and 198
1200-word record. The public-use version was based on the sma
of Governments. This is the first time such detail has been mad
- The impact of classification changes was minimized to the exten
base are generally those still being collected. For example, sinc
in fiscal 1988, the data base consolidates these obsolete categor
- Revisions to finance codes were also standardized. For instanc
classified expenditures for purchase of land and existing structur
prefix pertained to the salaries portion of current operations expe
codes to their proper location (i.e., capital outlays or current oper
- Past practices differing from current treatment were revised so th
illustrate, in today's classification system all finance codes (excep
was not always true. Some finance codes were shown separatel
A03 and A59 were also included in code A89 for some years whi
General Revenue Sharing Program, was included in code B89).
- Prior to fiscal 1977, the Bureau used a 10-digit ID numbering sch
adopted the current 9-digit ID by reducing the type code segment
numbers in this data base were converted to the 9-digit format.
- Prior to fiscal 1977, finance data were recorded in whole dollars;
in thousands of dollars. For this data base, pre-1977 data have
calculation of totals and subtotals. This rounding may cause tota
their detail.
UserGuide.Xls (5. User Notes) 104 of 209
5. Important Data Use
- Other miscellaneous clean-up chores included: eliminating duplic
function codes; resolving invalid type codes; inserting governme
fields such as "Year of Data" (sometimes called "Imputation" fiel
downloaded from the mainframe and it was necessary to analyze
Perfect historical consistency is a goal rarely achieved. For exampl
was a single function (code -46) versus the two current subfunction
code 44). These Data User Notes and the Annotated Guide to the
historical inconsistencies.
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3. Other Members of the Historical Finance Data Base Series
This data base, "IndFin," is the latest addition to the historical data b
members of this series include:
- National Trend ("Hist_Fin"). This Microsoft Access data base pr
by level of government for selected years between 1902 to 1999
- State Aggregates ("Rex" and "Dac"). This Microsoft Access data
of government for fiscal years 1972 and 1977 to 1999. It also inc
government activities. It contains nearly 1,500 data variables, in
- County Areas (Fin_CoArea). This future data base will cover loc
every census of governments since 1972 plus limited data for 19
- State Trends ("St_Trend"). Also a Microsoft Access data base, i
census of governments between 1957 and 1972 plus data for 19
specifically to reproduce the employment and finance data publis
"Historical Statistics" census report. For most users, however, it
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4. Data Are Provided (Largely) "As Is"
The original source files for this data base are what we believe to be
Little data revision was done (see Data User Note 13 for exceptions
The fact that these sources are finalized data files does not mean th
years covered by this data base, the goal of the finance survey was
data files. Users of the data base need to be aware that they may e
other surprises in the data (e.g., the 300+ governments reporting ne
extracted from the data base be carefully reviewed.
Caveat emptor!
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5. Number of Records
UserGuide.Xls (5. User Notes) 105 of 209
5. Important Data Use
The number of records available for each year varies. For some ye
1994, the smallest file, has 12,862 records); for others, a full census
for many years both the sample units and nonsample units in states
latter case, the number of records rivals a full census of governmen
Although 1967 was a census year, it consists entirely of sample uni
To limit queries to sample units, add this condition to your selection
WEIGHT GT 0
The table below shows the number of records for noncensus years,
NonSample -------- Sample Units ---
Year Total Units Total Certainty NonCe
---- ------- --------- ------- --------- -----
99 22,854 10,373 12,481 6,665
98 22,939 9,609 13,330 6,707
96 13,346 0 13,346 6,702
95 12,884 0 12,884 6,592
94 12,862 2 12,860 6,546
93 12,892 0 12,892 NA
91 32,154 10,381 21,773 13,691
90 34,915 13,071 21,844 13,714
89 34,015 12,171 21,844 13,668
88 36,127 13,908 22,219 14,724
86 53,083 30,679 22,404 14,796
85 54,579 32,221 22,358 14,678
84 54,359 32,127 22,232 14,547
83* 33,125 3,365 29,760 22,145
81 53,442 27,006 26,436 20,825
80 29,548 1 29,547 24,656
79 56,154 26,861 29,293 24,394
78 19,505 0 19,505 15,410
76 15,971 16 15,955 11,035
75 15,956 11 15,945 11,025
74 15,940 1 15,939 11,000
73 16,145 0 16,145 NA
71 16,177 0 16,177 NA
70 16,177 0 16,177 NA
67 16,107 0 16,107 NA
NA Not available
Note: Certainty/NonCertainty breakdown not avai
see Data User Note 8 for details.
* Number of nonsample units affected by need to
file; see Data User Note 14 below.
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6. Government Name Problems
UserGuide.Xls (5. User Notes) 106 of 209
5. Important Data Use
Government names were unavailable for over 6,700 records (repre
special and school district records, 179 are general purpose govern
nearly 50,000 population (ID = 233082015). These records have "N
Unit names were a major problem for this data base. Prior to fiscal
names (that field was blank). Names were therefore extracted from
the mainframe, the oldest of which was for 1979; (2) archived copie
GID; (3) public-use files (many of which contained names); (4) 198
current "live" GID; and (6) employment individual unit data files ("Ind
Names in these sources were not ideal. Often they contained garba
were thousands of meaningless names like "Housing Auth of." Abb
different abbreviations for "conservation").
Government names were cleaned up and standardized as much as
for all years involved and it existed as of FY 1987, then the current n
(like "Suitland Village Village") were eliminated. Names beginning w
"Township of Suitland" were altered to say "Suitland City" or "Suitlan
inconsistent, the latest year was assumed to be the best available. A
Given these difficulties, it is possible that the name assigned to a go
fiscal 1987.
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7. School District Enrollment Issues--FY 1974-1976, 1978, and
The population field ("Pop") contains enrollment data for school dist
regarding enrollment data:
A. For fiscal years 1974, 1975, 1976 and 1978 the enrollment data
many records). The population field was zeroed-out for school
undocumented field, called "BadEnrol."
In August 2000, these missing enrollment data were replaced w
unit files ("IndEmp"). The "DataFlag" field for these records will
file's enrollment data do not agree always with those in the finan
that the employment file's enrollment that were substituted for th
ones in the finance files.
B. In FY 1987, two new fields were added to the source file: V33 (e
V34 (higher education enrollment). Not only were they in additio
often disagreed with the latter amount. Moreover, V34 amounts
Thus, fiscal 1987-96 enrollment data were extracted as follows:
- For elementary-secondary school districts, the difference betwe
V33 was more current (generally, the fall enrollment for that sch
"Pop" field's data by applying these rules:
For fiscal years 1987 - 1992, V33 replaced Pop's Enrollment fo
(1) V33 was missing
UserGuide.Xls (5. User Notes) 107 of 209
5. Important Data Use
(2) Finance data were prior year data, in which case the "P
enrollment data for a period later than its finances
(3) Obvious errors in V33 data (e.g., in thousands instead o
The "Pop" field's original enrollment data can be found in th
For fiscal year 1993, population data (which represent enrollme
V33 was substituted instead.
For fiscal year 1994, the population field's enrollment was ident
not, V33 was used following the same rules above.
For fiscal years after 1994, V33 was not reported in the source f
- For higher education school districts (representing less than thr
amounts were used since V34 appeared unreliable for all years
* Example: According to the 1991 Public Education Finances report
28,821 students but V34 for this district exceeded 263,00
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8. Statistical Weight Issues--FY 1967, 1970, 1971, 1973, and 19
Note: The statistical weight is provided for informational purposes o
or national totals (or county area totals). Instead, use the historical
which includes the additional statistical adjustments needed.
The statistical weight assigned to each government can be found in
fiscal years (1967, 1970, 1971, and 1973) the weight data were use
undocumented field, "BadWeigh," and the Weight field's value chan
For fiscal year 1993, the statistical weight was not available. Since
same as those for fiscal 1994, the latter year's weights were used fo
file that were not in the 1994 (or later) file. These records were ass
For fiscal year 1993 and later, the method of presenting the weight
reciprocal of the weight (what SAS calls "frequency"). Examples: C
(vs. 10000 in prior years) while a weight of 200 is now shown as 50
years, the data base converted these amounts to their former forma
field, called "OldWeigh."
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9. Employee-Retirement Data Issues--FY 1967 to 1976
Employee-retirement data posed numerous problems, primarily in y
different operating environment during this period. In the city and co
were published only for large "jacket" units; these records had their
record); and the survey's goal was producing publications, not a squ
their fixes, were:
A. Except for the two census years (1967 and 1972), the only retire
UserGuide.Xls (5. User Notes) 108 of 209
5. Important Data Use
were for "jacket" units and a few others (mostly prior year imputa
historical data base, these missing data were replaced with the l
available (generally, from 1967 or 1972). Units with prior year e
in the following manner:
- The "YrRet" (Year of Retirement Data) variable has a value ind
blank prior to fiscal 1987, the survey year it was added to the s
- The "DataFlag" variable contains the 'M' code. To identify reco
Where DataFlag Contai
B. While the only employee-retirement data before fiscal 1977 were
employee-retirement data before FY 1977. Since retirement dat
City and County Government Finances as well as the Employm
were replaced with current data from publications.
The main drawbacks of this method were: (1) the following retire
exhibit code) and X40, X41, and X42 (which were subsumed in c
for a few jacket units were not published, in which case prior yea
For units whose employee-retirement data were extracted from p
year contains the 'L' code.
C. For some county jacket units which had retirement data in the fi
summed and keyed as one number. For example, instead of ke
codes, they were summed and keyed at X21. (The code used w
years and X44 for others.)
For this data base, the missing detail was replaced with data from
the "DataFlag" variable was assigned the 'L' code.
Note: When missing data or detail were extracted from employe
necessary to compute a residual amount. Generally, the residua
code for a category (e.g., to code X11, Benefit Payments, for exp
D. Before FY 1977, certain employee-retirement revenue data were
received from other governments were incorrectly keyed as Stat
(X06) rather than at code X05. This data base reclassified them
The significance of this error is that X06 is an intragovernmental
revenue totals and subtotals. Thus, totals published in City and
stated by the amount mis-coded as X06 instead of X05. This will
with the data base.
Note that these contributions were reported correctly in the empl
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10. Government ID Changes
Although most governments retain the ID number they are assigned
in a government's ID being changed. Since a major purpose of this
UserGuide.Xls (5. User Notes) 109 of 209
5. Important Data Use
over time, it is critical that a government possess the same ID for al
structural cause).
Examples of ID changes include:
- All Alaska IDs were changed in the 1982 Census of Government
their old ID because they were disincorporated before the global
- New county incorporations, where governments in the new count
new county code (e.g., La Paz County, AZ).
- Creation or dissolution of an independent city, which also affects
- At one time it was common practice to change a special district's
headquartered changed (which may have been simply a new ma
rarely documented.
Consequently, if a government ID number was changed under any
base is its current number (based on the "live" GID). That is, the ID
preceding the cause of the change) is its current one. There will als
"IDChged," indicating the total number of ID changes identified.
There will also be an entry in a special data base reference table, ca
has one record for every ID change identified and lists its previous I
most of which are the Alaska global ID changes.
Click here for more information about the specia
Exceptions: This practice was not followed in cases where the ID
alteration, such as: mergers or annexations where a
another; city-county consolidations, in which the cou
and conversions (e.g., a township that converts to a
Unfortunately, the true extent of ID changes cannot be determined b
documented. Generally, when an ID number is changed today, the
"incorporated." There is no link between the two IDs, however, exc
Past practice in some cases was simply to change the ID number w
Click here for more information on this top
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11. Other Data Anomalies
The source files for this data base possessed numerous anomalies
for many years the goal of the finance survey was to issue publicati
the anomalies, many of which were undocumented, are these:
- Prior to FY 1977, there were two finance data files: one for the la
record and no longer available) and a smaller one for all governm
base). Data for jacket units were collapsed into this smaller file
From FY 1967 to 1973, then jacket-only code A03 (charges for
UserGuide.Xls (5. User Notes) 110 of 209
5. Important Data Use
displayed separately in the 400-word file but expenditures for t
expenditures, NEC (code -89).
Jacket units had more detailed codes for nonguaranteed debt.
into the smaller file, these additional codes lost their "nonguara
nonguaranteed debt amounts for jacket units may be higher th
In the City and County Government Finances publications, the
larger file) may not agree with their data in other tables (based
Errors found in jacket unit data during the publication phase we
but not the 400-word record file. Alternately, sometimes the er
unit table but no other tables (or vice versa).
- The FY 1974 source file has prior year data (1973) for three jack
Jefferson County, AL, Baltimore County, MD and Monroe County
Finances report provides 1974 data but it appears to have been t
- Before FY 1977, highways expenditures were reported as a singl
in the data base under regular highways category (code -44) for t
purposes (obsolete code A46) were included under A44 prior to f
- The data base has 104,330 unique IDS, 8,832 of which are not in
purpose governments.
- Liquor Stores data (code -90) appear to be missing from source
in Montgomery County, MD and in census of governments years.
- Source files before fiscal 1977 were in whole dollars rather than t
any field could hold. If a figure exceeded that amount, then the fi
(999999999). Few governments exceeded the limit (Port Authori
are two that did). For the data base, actual data were substituted
In theory, the overflow flag was spotted during the publication pha
In practice, the overflow flagged was sometimes overlooked and
employee-retirement cash and securities data for fiscal 1974).
- Prior to fiscal 1988, intergovernmental revenue for transit subsidi
In fiscal 1988, these codes were replaced with B94, C94, and D9
file contains no data for any of these codes. On the other hand, B
governments: only 21 local records reported data for these codes
- There are over 300 records reporting negative values. Also, nea
wages (exhibit code Z00) exceeding total current operations expe
- Even if a finance code is "illegal" for a type of government, it is s
illustrate, 18 school districts reported utility data between fiscal 1
government-only revenue code but 82 local governments reporte
Similarly, between fiscal 1988 and 1997, over 1,700 local govern
a state government-only code: X06, state government contributio
- Data for certain finance codes were sometimes reported separat
practice applied primarily to files before FY 1977 (some codes lis
UserGuide.Xls (5. User Notes) 111 of 209
5. Important Data Use
and therefore did not affect this data base):
Data for this finance code: Were sometimes duplicated in this
A03 A89
A16 A18
A21 A12
A45 A46
A59 A89
B27 B89
T41 T49
E19 E21
E84 E89
In the data base, these amounts were "unduplicated."
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12. Records with No Data
The data base contains 42,149 records that are blank--i.e., every fin
(89 percent) are for census of governments years and 92 percent a
records whose four major totals (revenue, expenditure, debt outstan
zero but they had data for at least one variable not included in any t
Z00, or long-term debt retired or issued).
These records can be identified using the "ZeroFlag" variable, whic
'1' indicates that all finance variables are zero
'2' indicates that the four major totals are zero but at least one var
'0' indicates all other records
The following table provides a count of blank records, by type of gov
Survey Spe
year Total Counties Cities Townships Dist
------ ------- -------- ------ --------- ----
Total 42,149 14 1,055 1,733 3
1999 6 0 1 0
1998 5 0 1 0
1997 3,057 0 64 99
1996 0 0 0 0
1995 1 0 1 0
1994 3 0 0 0
1993 5 0 0 0
1992 7,153 0 50 114
1991 299 0 42 9
1990 403 4 39 9
1989 380 0 37 2
1988 258 1 29 4
1987 5,022 0 45 46
1986 222 2 30 44
1985 246 2 28 42
1984 258 1 27 49
UserGuide.Xls (5. User Notes) 112 of 209
5. Important Data Use
1983 333 3 19 10
1982 5,649 0 58 172
1981 281 0 57 94
1980 192 0 14 7
1979 325 0 58 81
1978 196 0 2 5
1977 6,826 0 177 250
1976 151 0 4 5
1975 170 0 4 7
1974 188 0 5 7
1973 233 0 7 9
1972 9,288 1 213 627
1971 299 0 12 15
1970 371 0 19 11
1967 329 0 12 15
* Shows number of governments whose four major
data for one or more variables not included i
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13. Data Revisions
The source files from which this data base was developed were fina
project to re-edit the data. Nonetheless, there were instances whe
for this data base. Some were official revisions never applied to the
Others resulted from the different environment and operating practi
the only employee-retirement data needed before FY 1977 for City
jacket units). Other revisions were necessitated by their bizarre na
ment that ballooned its data).
Less than one percent of the data base received any type of data re
employee-retirement data prior to fiscal 1977 (see Data User Note 9
data revisions.
A. Post-publication errata changes (including ones applied only to t
errors discovered after publication were corrected via errata notic
form. Often, the data file involved was not corrected. If possible
by, first, identifying errata changes made (studying publications, l
2000 notes for estimates data base) and, second, applying the ch
be identified: the government involved, the codes affected, and th
are identified with a DataFlag code of 'X'.
EXAMPLE: An errata notice was issued in 1977 for New York Cit
expenditures from the former Federal General Reven
years. Although an errata notice had been issued, the
corrected. This data base, however, includes these d
underreported expenditure.
Note that many minor errata changes appear only as an "r" footn
thus could not be applied to the data base.
B. Jacket unit publication changes not applied to data file. It was o
UserGuide.Xls (5. User Notes) 113 of 209
5. Important Data Use
but not the data file when an error was found in final stages of pu
and pasted into the publication tables but the data file itself was o
detected by their slightly different typeface.) To identify such revi
compared to the publications. Differences were scrutinized for e
found, and the codes involved could be identified, then the data b
publication amount. These data base revisions are identified wit
EXAMPLE: Cook County, IL's total revenue for FY 1973 did not a
minute publication correction to local intergovernment
a keying error in code D79, which had been entered a
error (if uncorrected) would have overstated Cook Co
C. Extreme outliers , where identified, were corrected. These data
code of 'K'.
EXAMPLE: In fiscal year 1974, state aid data (code C21) for ten
billion each (sic). In contrast, C21 for all local govern
Why or how $10 billion had been added to their C21 a
base amounts were revised.
Perhaps the most typical outlier was a survey data correction, us
keyed in whole dollars rather than in thousands. Outlier revisions
Click here for detailed information about these data r
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14. Substitution of Data Using Public-Use Files (FY 1981 and 1
The primary source files for this data base were the Census Bureau
with mainframe files was determining whether they were the final ve
involved the following tasks:
- Comparing the data for individual cities and counties to their resp
- Comparing the data for individual governments to internal printou
- Summarizing the data by population-size group and comparing th
- For census years, summarizing the data by type of government a
Government Finances.
- Comparing the data electronically to the public-use version (if ava
was not released until the data were finalized (not always true).
This review revealed that source files for two years appeared incom
years it was necessary to supplement the internal file with data from
records missing from the internal file or because its data were incom
based on the smaller 400-word record, using it as a substitute had a
1983: The internal version of this file suffered from a number of prob
- It contained no data for school districts (type 5's). As a result, al
public-use version. Substitution in this situation, however, had l
school districts less detail is collected compared to other types a
released in the public-use version. These 12,206 records are id
UserGuide.Xls (5. User Notes) 114 of 209
5. Important Data Use
- The internal and public-use files did not contain the same record
file contained 6,500 sample units that were not in the public-use
districts that were not in the internal one. The data base include
- The internal file contained 659 records that appeared to be incom
file, 92 percent of which were special districts. Data from the pu
To minimize the impact of using the smaller file, each record wa
debt, and cash and securities). Data were substituted only for th
if only revenue data were incomplete, then only those data were
DataFlag variable indicates which parts were replaced (number
parenthesis):
'R' code indicates that all revenue data were substituted (644
'E' code indicates that all expenditure data were substituted (
'D' code indicates that all debt data were substituted (20)
'C' code indicates that all cash and securities data were subs
Combinations of codes indicate that more than one part was rep
and expenditures were replaced). The number of governments
substitution of more than one part.
The table below summarizes the number of governments whose
the public-use file, by type of government and DataFlag code (ex
DataFlag Total Counties Cities Townsh
-------- ----- -------- ------ ------
Total 659 15 28 7
D 1 1 0 0
E 13 4 1 0
ED 1 0 1 0
R 51 4 17 0
RD 2 0 1 1
RE 570 3 1 1
REC 5 1 1 3
RED 4 0 0 0
REDC 12 2 6 2
- The internal file contained 23,034 nonsample records (mostly cit
use file. These records were excluded from the data base beca
on the completeness of the internal data file and (2) the fact tha
file eliminated the best verification of their completeness.
1981: The internal version of this file was incomplete for three gover
discovered in a jacket unit:
- Denver CO's record was basically blank and was replaced with d
the public-use file was missing data for two major codes (based
report): T09 and M80. These missing data were added to the da
DataFlag codes for 1981: 'REDC'.
- Debt data for Douglas County, NE and Everett WA were missing
with data from the public-use version. These two units were ass
UserGuide.Xls (5. User Notes) 115 of 209
5. Important Data Use
- Most of Philadelphia PA's tax data (i.e., codes T01, T40, and T9
thousands, thereby understating its revenue by over $835 million
for this error and Philadelphia assigned the 'K' DataFlag code fo
*Consequences of substituting public-use file data: The 400-word v
internal file. Note that the data themselves are not missing but are s
other"). Substituting the smaller, public-use version has two major
historical comparisons based on the missing detail will have gaps.
codes that subsume the missing ones will be overstated. This latte
the sudden drop to zero for missing codes.
Click here for a more detailed description of these co
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15. Meaning of "DataFlag" Codes
To provide users with more information about individual records, the
"DataFlag." The Data Flag field may contain one or more code, as
Code Description (number of records i
A All data (including nonfinance data) were replaced with those
C Cash and securities data were replaced with those in public-u
D Debt data were replaced with those in public-use file (23) %
E Expenditure data were replaced with those in public-use file (6
F Reserved for employment historical data base
G Missing population, function code, or enrollment data replaced
K Keying and/or outlier error revised (39)
L Missing employee-retirement data were replaced with current
M Missing employee-retirement data were replaced with prior ye
N Negative value corrected in source file (5)
O Overflow flag found in source file (9)
P Publication table correction was not applied to source file (32)
Q Q11 extracted from M12 using Q11 data from school finance
R Revenue data were replaced with those in public-use file (645
S Salary & wages (Z00) data replaced with public-use file's but n
X Errata notice revision not applied to source file (15)
Z Revision for reasons NEC (14)
* Applies only to fiscal year 1983 and represents special and sch
requiring data in public-use file to be used.
% Applies only to fiscal years 1981 and 1983.
# Applies only to fiscal 1973-1976 jacket units.
@ Applies only to fiscal 1970, 1971, and 1973-1976.
& Applies to fiscal 1983 only.
To search for records with any of these codes, use the SAS "contai
Where DataFlag Contains 'R' or Data
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UserGuide.Xls (5. User Notes) 116 of 209
5. Important Data Use
16. "Jacket" Units (Largest Cities and Counties)
"Jacket units" are state governments and the very largest cities and
that they are compiled by Census Bureau staff (rather than collecte
canvass).
The data base contains a variable (JackFlag) indicating whether a g
JackFlag of '1' indicates a jacket unit; a value of '0' indicates that it w
a review of the special jacket unit table in City and County Governm
governments JackFlag equals '0' for years prior to fiscal 1973, the f
issued.
The criteria for jacket units for the period 1967 to 1992 were: for cou
and for city governments, population of 300,000 or more. For 1993
governments, population of 1,000,000 or more and for city governm
The list below shows every city and county that was a jacket unit be
indicated, county governments were jackets from 1973 to 1999 and
to 1999.
County Government Jacket Units: City G
No. ID Name ID
--- --------- ------------------------- ------
1. 051001001 Alameda Co. 322001
2. 391002002 Allegheny Co. 112060
3. 211003003 Baltimore Co. (73-92) 442227
4. 311002002 Bergen Co. (73-92) 212004
5. 441015015 Bexar Co. 192017
6. 101006006 Broward Co. 012037
7. 391009009 Bucks Co. (87-92) 222013
8. 311004004 Camden Co. (89-92) 332015
9. 291002002 Clark Co. (84-92) 342060
10. 051007007 Contra Costa Co. (73-92) 142016
11. 141016016 Cook Co. 362031
12. 361018018 Cuyahoga Co. 362018
13. 441057057 Dallas Co. 362025
14. 111044044 DeKalb Co. (87-92) 442057
15. 391023023 Delaware Co. (73-92) 062016
16. 141022022 Du Page Co. (73-92) 232082
17. 441071071 El Paso Co. (84-92) 442071
18. 331015014 Erie Co. (73-92) 052010
19. 221005005 Essex Co., MA (73-92) 442220
20. 311007007 Essex Co., NJ (73-92) 122002
21. 471030030 Fairfax Co. (74-92) 442101
22. 361025025 Franklin Co. (73-92) 152049
23. 051010010 Fresno Co. (82-92) 102016
24. 111060060 Fulton Co. (73-92) 262048
25. 361031031 Hamilton Co. (73-92) 052019
26. 441101101 Harris Co. 052019
27. 241027027 Hennepin Co. 182056
28. 101029029 Hillsborough Co. (73-92) 432079
29. 311009009 Hudson Co. (73-92) 102013
30. 261048048 Jackson Co. (73-92) 502041
UserGuide.Xls (5. User Notes) 117 of 209
5. Important Data Use
31. 011037037 Jefferson Co., AL (73-92) 242027
32. 181056056 Jefferson Co., KY (73-92) 432019
33. 051015015 Kern Co. (89-92) 192036
34. 481017017 King Co. 332031
35. 151045045 Lake Co. (73-86) 312007
36. 051019019 Los Angeles Co. 472122
37. 231050050 Macomb Co. (73-92) 052001
38. 031007007 Maricopa Co. 372055
39. 101013013 Metropolitan Dade Co. 282028
40. 221009009 Middlesex Co., MA (73-97) 392051
41. 311012012 Middlesex Co., NJ (73-92) 032007
42. 501041041 Milwaukee Co. (73-92) 392002
43. 311013013 Monmouth Co. (82-92) 382026
44. 331028026 Monroe Co. (73-92) 332028
45. 211016015 Montgomery Co., MD (73-92) 052034
46. 361057057 Montgomery Co., OH (73-92) 442015
47. 391046046 Montgomery Co., PA (73-92) 052037
48. 381026026 Multnomah Co. (73-92) 052038
49. 331030028 Nassau Co. 052043
50. 221011010 Norfolk Co. (73-92) 482017
51. 231063063 Oakland Co. 262096
52. 371055055 Oklahoma Co. (73-92) 242062
53. 051030030 Orange Co., CA 362048
54. 101048048 Orange Co., FL (84-92) 032010
55. 101050050 Palm Beach Co. (82-92) 372072
56. 481027027 Pierce Co. (84-92) 472132
57. 031010010 Pima Co. (82-92) 092001
58. 101052052 Pinellas Co. (73-92)
59. 211017016 Prince Georges Co. (73-92)
60. 051033033 Riverside Co. (74-97)
61. 051034034 Sacramento Co.
62. 451018018 Salt Lake Co. (76-92)
63. 051036036 San Bernardino Co.
64. 051037037 San Diego Co.
65. 051041040 San Mateo Co. (73-92)
66. 051043042 Santa Clara Co.
67. 431079079 Shelby Co. (73-92)
68. 261095095 St Louis Co. (73-92)
69. 331052047 Suffolk Co.
70. 361077077 Summit Co. (73-92)
71. 441220220 Tarrant Co.
72. 441227227 Travis Co. (87-92)
73. 371072072 Tulsa Co. (87-92)
74. 311020020 Union Co. (73-92)
75. 051056055 Ventura Co. (82-92)
76. 231082082 Wayne Co.
77. 331060055 Westchester Co. (73-92)
78. 221014012 Worcester Co. (73-92)
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17. Year of Population Data
UserGuide.Xls (5. User Notes) 118 of 209
5. Important Data Use
Beginning with fiscal year 1987, the source file included a field that
data. Shown below is the most common reference period for popul
the actual population data for some governments may be for a diffe
were extracted from an earlier survey). For survey years before 19
comparison of the population data to published amounts.
Survey Year of Survey Year of Survey
Year Population Year Population Year
------ ------------ ------ ------------ ------
1999 1998 1990 1988 1981
1998 1996 1989 1988 1980
1997 1996 1988 1986 1979
1996 1996 1987 1986 1978
1995 1994 1986 1986 1977
1994 1994 1985 1984 1976
1993 1990 1984 1982 1975
1992 1990 1983 1982 1974
1991 1990 1982 1980 1973
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18. Information to Provide Outside Data Users
Below is the minimum information that should be provided to outsid
You may also need to provide more information on finance concept
TIP: Copy this section and paste into your word processor (as text)
<><><><><><><><><><
Notes to Historical Finance Data on Ind
(Beta Version of Data B
The electronic data being provided came primarily from a data base
data files on the finances of individual governments. These files ca
quinquennial census of governments.
This data base is still in the testing and review phase and is su
Users need to be aware that some of these internal data files were
public on a wide scale. Also, computer technology, practices and th
changed considerably over the period covered. To illustrate, for ma
by the finance survey's primary goal, to issue publications on a time
handle data in the electronic form then available.
Information missing from the internal files (such as the governmen
sources. These sources may be the best available but are rarely pe
The period covered by these data may contain classification revisio
For example, in some years certain finance items were collected fo
for the largest cities and counties. To the extent possible, the impa
but cannot be totally eliminated.
UserGuide.Xls (5. User Notes) 119 of 209
5. Important Data Use
The data may also contain anomalies, discrepancies, or inconsisten
comparing data for individual governments over a period of time. In
even explained because the survey materials are no longer availabl
These data may not be identical to previously-released data (either
numerous reasons, including revisions to publications that were not
the release of data, and limited data revisions that were applied to t
The number of records available for each survey year varies depen
ments; the sample size for the annual finance survey; and whether
in states where the Bureau had data collection arrangements with s
If included, the population data are those found in the original financ
been updated since they were originally obtained.
Although the governments in this data base may have comprised a
(wholly or partly) on a sample and therefore are not subject to any s
provided) is for informational purposes only and should not be used
The finance statistics provided are in terms of current dollar amoun
adjusted for price and wage changes occurring through the years.
If provided, the user guide for this data base (UserGuide.xls) is an i
broken links or sections not relevant to outside data users.
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19. A Note on Federal and State Government Records
The focus of this data base is on local government finances. Feder
the historical data base covering the finance "estimates" (state-by-ty
base is in Microsoft Access97 format. Data users can extract Fede
"IndFin" data base by using special Access97 queries. Instructions
(opens new spreadsheet):
\\Govs05\PEB\\Historical Data\Finance\Individual Units\Documen
Including the Federal and state governments in this data base is a b
Please note the following features about the data for these records:
- There are numerous finance codes that apply only to the Federa
subsumed into other categories. Examples--
Federal Customs Duties (T08) are included in General Sales T
Expenditures for Federal-only functions (e.g., National Defense
General Expenditure NEC category.
Expenditures for Veterans' Services are also included in the G
- There are some Federal- and state-only finance codes that do n
example, assistance and subsidies codes E19 (education) and
governments. While they are included in their respective totals,
reason, calculating current operations for Education, NEC (E21)
UserGuide.Xls (5. User Notes) 120 of 209
5. Important Data Use
include these assistance and subsidies amounts.
- Similarly, for the Federal Government only, the Employment Sec
ernmental expenditure codes (L22 and M22). For local governm
only. Thus, calculating E22 for the Federal Government will inc
- Total insurance trust revenue and expenditure for the Federal an
applicable to local governments (e.g., workers' compensation a
shown separately in this data base.
- Population are not for the same year as local records; generally,
"How to" instructions above will replace the estimates pop data w
- No data are available for the Federal Government after fiscal ye
- "Rex" and "Dac" contain no data for the Federal or state governm
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20. Miscellaneous FAQs
Please feel free to suggest other topics for FAQs; submit them to Jo
a. Why does the data base disagree with the publications?
b. Why are there no data for 1968 and 1969?
c. Why is there no data older than 1967?
d. What is excluded from the data base?
e. Why doesn't the number of records agree with the official counts
f. Why are data reported for obsolete codes (e.g., Federal general r
g. Why is this data base in SAS when all other finance historical dat
h. Does IndFin include ALL the individual finance codes?
a. Why does the data base disagree with the publications?
It is not unusual for the data base to disagree with finance publicatio
differences; let us count the ways:
- The data file was not always frozen when the publication was com
corrections.
- Conversely, data errors spotted during the publication process of
selves. These can often be denoted by the different font in the pu
cut and pasted into the report). For the largest city and county go
unit" tables were reviewed for these types of corrections. If found
corrected; see Data User Note 13.
- Large errors found after publication were revised in published err
data base contains these fixes, the original publication tables do
- Prior to fiscal 1977, City and County Government Finances used
for these governments and the standard, but smaller, file for all o
on the latter file. As described in Data User Note 11, the jacket u
file, sometimes resulting in data being published for the jacket un
UserGuide.Xls (5. User Notes) 121 of 209
5. Important Data Use
base.
- The publications are sometimes wrong! For instance, 1973 City
spending a negative amount for medical vendor payments while
expenditure exceeding its total expenditure. The 1974 County G
"overflow" flag for Los Angeles County, CA employee-retirement
- It is also possible the mainframe file downloaded for this data ba
not the one used for publication).
- Interestingly, the data revisions described in Data User Note 13 h
amounts. For instance, only 47 cities with population over 50,000
of data revision. Only 41 counties with population over 100,000 (
revision. (These counts exclude pre-1977 revisions for missing e
and 'M', since retirement data were published only for jacket units
resulted in the data base agreeing with the publications (which th
b. Why are there no data for 1968 and 1969?
The simple answer is that no data files for fiscal 1968 and 1969 exis
census of governments was a test. Punch card technology had bee
declared a success and computer processing became standard wit
c. Why are there no data older than 1967?
No data files before 1967 have been found--and none probably exis
storage media, data were stored primarily on punch cards.
We did retrieve from the National Archives a data file that supposed
1973 but the computer staff has not been able to read it.
d. What is excluded from the data base?
Not much, such as:
- Finances of the Federal and state governments (see historical da
- Data no longer being collected (e.g., cash and securities detail an
like revenue from the old Federal General Revenue Sharing Prog
- Character and object expenditure codes applicable only to the lar
prefix code "K").
e. Why doesn't the number of records agree with the official co
Until recently, there was no concentrated effort to have the various
agree in number of records. Listed below is the "official" count of
the number of records in the data base for that year:
Census Official # of Records
Year Count in Data Base
------ -------- ------------
1997 87,453 87,453
UserGuide.Xls (5. User Notes) 122 of 209
5. Important Data Use
1992 84,955 84,955
1987 83,186 83,784
1982 81,780 82,566
1977 79,862 79,832
1972 78,218 78,216
Note: The data file for 1967 consists o
Even though the numbers are close, the data base contains thousa
Data User Note 12 for details.
f. Why are data reported for obsolete codes (e.g., Federal gene
These anomalies are largely the result of nonresponse imputation
were unavailable. In some cases, this results in data being report
survey. In the case of the 117 governments that reported receivin
program in FY 1993, all are prior year "plugs" dating from the fisca
Another example is the 287 governments reporting state tax relief
dropped after FY 1987 but data for these units were pulled from t
The "YrData" (Year of Data) variable tells you the actual fiscal year
"plugs" were referred to as imputations and will have a YrData val
g. Why is this data base in SAS when all other finance historica
To borrow a real estate expression, there are three reasons why SA
A. SAS can store data in variable length records, greatly reducing s
Microsoft Access version of the data base would be 5-10 times l
storage space versus 500 megabytes for SAS.
B. SAS can store all 520+ variables in a single file. Other PC softw
250 variables per table. Thus, the number of tables to manage i
C. MS Access has other limitations, such as maximum table and d
the numerous tables required must be spread across three to fiv
D. With smaller records, fewer tables, and less fragmentation of th
other software.
E. SAS has extensive support in the Census Bureau.
Although data are in SAS format, you are not limited to using SAS f
can be easily exported to other software. Data users should view th
withdrawals--large or small--can be made as needed.
The following have been created to help users extract data:
A. An interactive application has been created to extract data from
(dbf) or ASCII format (txt). Nearly all software can read either or
fulfill 90+ percent of all queries, eliminating the need to write a si
UserGuide.Xls (5. User Notes) 123 of 209
5. Important Data Use
Click here to view instructions on usi
B. For more advanced SAS users, sample SAS programs have be
as needed.
Click here to view these samp
The data base can also be queried using SAS/Assist, the tool many
Click" course.
h. Does IndFin include ALL the individual finance codes?
IndFin includes over 93 percent of the finance codes applicable to lo
be derived from the data base). Listed below is a comparison of the
1997 Census of Governments (excluding employee-retirement exhi
outside the scope of the basic finance survey) and their treatment in
# of Finance Codes Description
515 Total number of finance codes reported in 199
337 Finance codes available in IndFin (including 8
116 State government-only codes (outside scope o
38 Local jacket-unit only codes (mostly the "K" eq
24 All other local finance codes, which consist of:
15 Intergovernmental revenue/expenditure cod
4 Tax codes "possible" for DC but no data we
4 Liquor store exhibit codes applicable only to
1 Beginning short-term debt code (61V)
*Water, electric, and gas utility codes. Transit utility intergovernmen
(B47, M47, etc.).
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UserGuide.Xls (5. User Notes) 124 of 209
Go to Contents
5. Important Data User Notes
Putting These Data User Notes into Perspective: An Overview
1. Introducing...The Historical Finance Data Base of Individual Local Governments
2. Standardizing the Presentation of Historical Data
3. Other Members of the Historical Finance Data Base Series
4. Data Are Provided (Largely) "As Is"
5. Number of Records
6. Government Name Problems
7. School District Enrollment Issues--FY 1974-1976, 1978, and 1987-96
8. Statistical Weight Issues--FY 1967, 1970, 1971, 1973, and 1993-99
9. Employee Retirement Issues--FY 1967 to 1976
10. Government ID Changes
11. Other Data Anomalies
12. Records with No Data
13. Data Revisions
14. Substitution of Data Using Public-Use Files (FY 1981 and 1983)
15. Meaning of "DataFlag" Codes
16. "Jacket" Units (Largest Cities and Counties)
17. Year of Population Data
18. Information to Provide Outside Data Users
19. A Note on Federal and State Government Records
20. Miscellaneous FAQs
These data user notes focus on limitations, problems, and anomalies related to the historical data base. They may
give false impressions regarding the overall quality of the data. This data base comprises over 600 million data
items. Despite the problems and limitations listed here, the vast majority of these data are healthy facts eager to
be released after spending years, even decades, locked up in a tape library.
Perhaps the most amazing aspect of these historical data is that they were still available. One problem rarely
encountered was the inability to read the old data files. This is a tribute to the care that the tape files received
from computer staffs at both the Census Bureau and the National Archives.
So, do not hesitate to explore the data base--but be sure to look out for the occasional statistical pothole!
Note: In this document, terms like "fiscal 1988" or "FY 1988" refer to the survey period (e.g., 1987-88).
1. Introducing...The Historical Finance Data Base of Individual Local Governments
For the first time, historical data on individual local government finances are available in a standardized format.
This SAS data base, called "IndFin," covers data for fiscal years 1967 and 1970 through 1999. Highlights of the
data base include:
- It comprises over one million individual local government records, including counties, cities, townships, special
districts, and independent school districts.
- It has 524 variables, including:
115 revenue items
242 expenditure items
125 debt items (issued, retired, and outstanding)
20 cash and securities items
It also contains 22 general reference data like population, school district enrollment, and census region code.
UserGuide.Xls (5. User Notes) 125 of 209
5. Important Data User Notes
- It includes not only individual finance codes but also dozens of totals and subtotals, ranging from "Total
Revenues" to "Highways Capital Outlay."
- In addition to its 524 variables, the data base is designed so that an additional 130+ data items can be
derived by adding or subtracting two variables (e.g., current operations expenditure for any function).
- An easy-to-use application is available to query the data base and export the results to other software.
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2. Standardizing the Presentation of Historical Data
The nearly 30 year span covered by this data base saw numerous changes in both technology and classification.
The Census Bureau employed different electronic record formats (each having unique "flavors"), applied major
classification changes, revised the meaning of finance codes, and altered many practices, all of which had
major impact on the electronic data. Previously, a user interested in time-series analysis of individual govern-
ment finances had to obtain electronic data from three different sources (including the National Archives) and
reconcile all these changes.
A major goal of this data base was to present data in an historically-consistent fashion:
- All source files were converted to a standardized format. Sources included the 400-word record (fiscal years
1967 to 1977); the 1200-word record (fiscal years 1977 to 1986); the 14000 character text file (fiscal years 1987
to 1991); and the latest "item code" format. Thus, no matter where a finance code resided in any source
file, it is always located in the same spot in this data base.
- Unlike public-use files issued between fiscal years 1977 and 1986, this data base employed the more detailed
1200-word record. The public-use version was based on the smaller 400-word record until the 1987 Census
of Governments. This is the first time such detail has been made publicly available.
- The impact of classification changes was minimized to the extent possible. Variables included in this data
base are generally those still being collected. For example, since most functional detail for debt was eliminated
in fiscal 1988, the data base consolidates these obsolete categories into their current classification.
- Revisions to finance codes were also standardized. For instance, prior to fiscal 1977 the "H" prefix
classified expenditures for purchase of land and existing structures. Between fiscal 1977 and 1981 the
prefix pertained to the salaries portion of current operations expenditure. This data base assigned all "H"
codes to their proper location (i.e., capital outlays or current operations).
- Past practices differing from current treatment were revised so the data could be portrayed consistently. To
illustrate, in today's classification system all finance codes (except exhibit ones) are mutually-exclusive. That
was not always true. Some finance codes were shown separately and recorded in other codes (e.g., codes
A03 and A59 were also included in code A89 for some years while code B27, receipts from the former Federal
General Revenue Sharing Program, was included in code B89). Such practices were rarely documented.
- Prior to fiscal 1977, the Bureau used a 10-digit ID numbering scheme for governments; starting in fiscal 1977 it
adopted the current 9-digit ID by reducing the type code segment from two characters to one. All pre-1977 ID
numbers in this data base were converted to the 9-digit format.
- Prior to fiscal 1977, finance data were recorded in whole dollars; starting in fiscal 1977 they were reported
in thousands of dollars. For this data base, pre-1977 data have been rounded to thousands after the
calculation of totals and subtotals. This rounding may cause totals and subtotals not to equal the sum of
their detail.
UserGuide.Xls (5. User Notes) 126 of 209
5. Important Data User Notes
- Other miscellaneous clean-up chores included: eliminating duplicate records; correcting invalid special district
function codes; resolving invalid type codes; inserting government names; and standardizing codes used in
fields such as "Year of Data" (sometimes called "Imputation" field). For some years, multiple files were
downloaded from the mainframe and it was necessary to analyze which one to use.
Perfect historical consistency is a goal rarely achieved. For example, prior to fiscal year 1977 highway expenditure
was a single function (code -46) versus the two current subfunctions (toll highways, code 45, and regular highways,
code 44). These Data User Notes and the Annotated Guide to the Data Base Variables point out many of the
historical inconsistencies.
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3. Other Members of the Historical Finance Data Base Series
This data base, "IndFin," is the latest addition to the historical data base series on government finances. Other
members of this series include:
- National Trend ("Hist_Fin"). This Microsoft Access data base provides over 50 years of national totals
by level of government for selected years between 1902 to 1999. It includes no data for state areas.
- State Aggregates ("Rex" and "Dac"). This Microsoft Access data base provides finance data by state and type
of government for fiscal years 1972 and 1977 to 1999. It also includes finance data on Federal and state
government activities. It contains nearly 1,500 data variables, including hundreds of totals and subtotals.
- County Areas (Fin_CoArea). This future data base will cover local government finances within county areas for
every census of governments since 1972 plus limited data for 1962 and 1967.
- State Trends ("St_Trend"). Also a Microsoft Access data base, it provides limited data, by state, for each
census of governments between 1957 and 1972 plus data for 1977 through 1999. This data base was designed
specifically to reproduce the employment and finance data published in tables 9 and 24, respectively, of the
"Historical Statistics" census report. For most users, however, it will have limited use.
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4. Data Are Provided (Largely) "As Is"
The original source files for this data base are what we believe to be the final, edited data file for each survey year.
Little data revision was done (see Data User Note 13 for exceptions).
The fact that these sources are finalized data files does not mean they are perfect. As noted elsewhere, in many
years covered by this data base, the goal of the finance survey was to produce publications, not squeaky clean
data files. Users of the data base need to be aware that they may encounter inconsistencies, anomalies, and
other surprises in the data (e.g., the 300+ governments reporting negative values). It is important that all data
extracted from the data base be carefully reviewed.
Caveat emptor!
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5. Number of Records
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5. Important Data User Notes
The number of records available for each year varies. For some years, it represents sample units only (fiscal year
1994, the smallest file, has 12,862 records); for others, a full census of governments (87,453 in fiscal 1997); and
for many years both the sample units and nonsample units in states with central collection arrangements. In the
latter case, the number of records rivals a full census of governments (e.g. fiscal year 1979 with 56,154 records).
Although 1967 was a census year, it consists entirely of sample units.
To limit queries to sample units, add this condition to your selection criteria:
WEIGHT GT 0
The table below shows the number of records for noncensus years, by sample vs. nonsample status.
NonSample -------- Sample Units ----------
Year Total Units Total Certainty NonCertainty
---- ------- --------- ------- --------- ------------
99 22,854 10,373 12,481 6,665 5,816
98 22,939 9,609 13,330 6,707 6,623
96 13,346 0 13,346 6,702 6,644
95 12,884 0 12,884 6,592 6,292
94 12,862 2 12,860 6,546 6,314
93 12,892 0 12,892 NA NA
91 32,154 10,381 21,773 13,691 8,082
90 34,915 13,071 21,844 13,714 8,130
89 34,015 12,171 21,844 13,668 8,176
88 36,127 13,908 22,219 14,724 7,495
86 53,083 30,679 22,404 14,796 7,608
85 54,579 32,221 22,358 14,678 7,680
84 54,359 32,127 22,232 14,547 7,685
83* 33,125 3,365 29,760 22,145 7,615
81 53,442 27,006 26,436 20,825 5,611
80 29,548 1 29,547 24,656 4,891
79 56,154 26,861 29,293 24,394 4,899
78 19,505 0 19,505 15,410 4,095
76 15,971 16 15,955 11,035 4,920
75 15,956 11 15,945 11,025 4,920
74 15,940 1 15,939 11,000 4,939
73 16,145 0 16,145 NA NA
71 16,177 0 16,177 NA NA
70 16,177 0 16,177 NA NA
67 16,107 0 16,107 NA NA
NA Not available
Note: Certainty/NonCertainty breakdown not available for 1967-1973 and 1993;
see Data User Note 8 for details.
* Number of nonsample units affected by need to substitute data from public-use
file; see Data User Note 14 below.
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6. Government Name Problems
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5. Important Data User Notes
Government names were unavailable for over 6,700 records (representing 3,922 governments). While most are
special and school district records, 179 are general purpose governments, the largest of which is a township of
nearly 50,000 population (ID = 233082015). These records have "NOT AVAILABLE" in the name field.
Unit names were a major problem for this data base. Prior to fiscal year 1987, finance files contained no record
names (that field was blank). Names were therefore extracted from (1) name and address files downloaded from
the mainframe, the oldest of which was for 1979; (2) archived copies of the Governments Integrated Directory, or
GID; (3) public-use files (many of which contained names); (4) 1987 census of governments finance file; (5) the
current "live" GID; and (6) employment individual unit data files ("IndEmp").
Names in these sources were not ideal. Often they contained garbage characters (like the "@" sign). There
were thousands of meaningless names like "Housing Auth of." Abbreviations were inconsistent (such as 18
different abbreviations for "conservation").
Government names were cleaned up and standardized as much as possible. If a government had the same name
for all years involved and it existed as of FY 1987, then the current name in the GID was used. Redundant words
(like "Suitland Village Village") were eliminated. Names beginning with expressions like "City of Suitland" or
"Township of Suitland" were altered to say "Suitland City" or "Suitland Township." If names for a government were
inconsistent, the latest year was assumed to be the best available. All names are in upper case.
Given these difficulties, it is possible that the name assigned to a government may be incorrect, especially before
fiscal 1987.
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7. School District Enrollment Issues--FY 1974-1976, 1978, and 1987-96
The population field ("Pop") contains enrollment data for school districts. There were two sets of problems
regarding enrollment data:
A. For fiscal years 1974, 1975, 1976 and 1978 the enrollment data were useless (either missing or garbage for
many records). The population field was zeroed-out for school districts after copying the data to an
undocumented field, called "BadEnrol."
In August 2000, these missing enrollment data were replaced with those from the employment survey individual
unit files ("IndEmp"). The "DataFlag" field for these records will contain a "G" code. CAVEAT: The employment
file's enrollment data do not agree always with those in the finance file for the same year. Thus, it is possible
that the employment file's enrollment that were substituted for the above years are not the same as the original
ones in the finance files.
B. In FY 1987, two new fields were added to the source file: V33 (elementary-secondary school enrollment) and
V34 (higher education enrollment). Not only were they in addition to enrollment in the Population field but they
often disagreed with the latter amount. Moreover, V34 amounts appeared to be unreliable for most years*.
Thus, fiscal 1987-96 enrollment data were extracted as follows:
- For elementary-secondary school districts, the difference between V33 and the "Pop" field appears to be timing:
V33 was more current (generally, the fall enrollment for that school year). V33 was, therefore, substituted for
"Pop" field's data by applying these rules:
For fiscal years 1987 - 1992, V33 replaced Pop's Enrollment for all school districts except where:
(1) V33 was missing
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5. Important Data User Notes
(2) Finance data were prior year data, in which case the "Pop" field's data were retained to avoid having
enrollment data for a period later than its finances
(3) Obvious errors in V33 data (e.g., in thousands instead of whole numbers)
The "Pop" field's original enrollment data can be found in the undocumented variable, "OldEnrol."
For fiscal year 1993, population data (which represent enrollment data for school districts) were unavailable so
V33 was substituted instead.
For fiscal year 1994, the population field's enrollment was identical to V33 for nearly all school districts. Where
not, V33 was used following the same rules above.
For fiscal years after 1994, V33 was not reported in the source files so the population field's amounts were used.
- For higher education school districts (representing less than three percent of all school districts), the "Pop" field
amounts were used since V34 appeared unreliable for all years but 1994. For FY 1994, V34 was used.
* Example: According to the 1991 Public Education Finances report, Dallas (Texas) Community College had
28,821 students but V34 for this district exceeded 263,000 in survey years 1988 - 1990 and 1993.
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8. Statistical Weight Issues--FY 1967, 1970, 1971, 1973, and 1993-99
Note: The statistical weight is provided for informational purposes only. Do not use the weight field to derive state
or national totals (or county area totals). Instead, use the historical data base of the finance estimates ("Rex-Dac")
which includes the additional statistical adjustments needed.
The statistical weight assigned to each government can be found in the data base's "Weight" variable. For four
fiscal years (1967, 1970, 1971, and 1973) the weight data were useless. The original weights were copied to an
undocumented field, "BadWeigh," and the Weight field's value changed to 1 (to denote sample units).
For fiscal year 1993, the statistical weight was not available. Since the weights for this survey year were the
same as those for fiscal 1994, the latter year's weights were used for 1993. There were 99 records in the 1993
file that were not in the 1994 (or later) file. These records were assigned a weight of 10000.
For fiscal year 1993 and later, the method of presenting the weight changed. Source files now show it as the
reciprocal of the weight (what SAS calls "frequency"). Examples: Certainty units now have a weight of 1.0000
(vs. 10000 in prior years) while a weight of 200 is now shown as 50.0000. To maintain a consistent format with prior
years, the data base converted these amounts to their former format after copying the data to an undocumented
field, called "OldWeigh."
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9. Employee-Retirement Data Issues--FY 1967 to 1976
Employee-retirement data posed numerous problems, primarily in years before 1977. These problems reflect the
different operating environment during this period. In the city and county finance reports, employee-retirement data
were published only for large "jacket" units; these records had their own data file (the precursor to the 1200-word
record); and the survey's goal was producing publications, not a squeaky clean data file. The problems, and
their fixes, were:
A. Except for the two census years (1967 and 1972), the only retirement data in source files before FY 1977
UserGuide.Xls (5. User Notes) 130 of 209
5. Important Data User Notes
were for "jacket" units and a few others (mostly prior year imputations based on census data). For this
historical data base, these missing data were replaced with the latest, prior-year employee-retirement data
available (generally, from 1967 or 1972). Units with prior year employee-retirement data can be identified
in the following manner:
- The "YrRet" (Year of Retirement Data) variable has a value indicating the year used. Normally, this field is
blank prior to fiscal 1987, the survey year it was added to the source file.
- The "DataFlag" variable contains the 'M' code. To identify records with this value, use the expression:
Where DataFlag Contains 'M'
B. While the only employee-retirement data before fiscal 1977 were for jacket units, not all jacket units had
employee-retirement data before FY 1977. Since retirement data for most jacket units were published in
City and County Government Finances as well as the Employment-Retirement report, these missing data
were replaced with current data from publications.
The main drawbacks of this method were: (1) the following retirement codes were not published: X14 (an
exhibit code) and X40, X41, and X42 (which were subsumed in code X44) and (2) employee-retirement data
for a few jacket units were not published, in which case prior year data were used.
For units whose employee-retirement data were extracted from publications, the "DataFlag" field for that
year contains the 'L' code.
C. For some county jacket units which had retirement data in the finance file, all codes for a category were
summed and keyed as one number. For example, instead of keying eight retirement cash and securities
codes, they were summed and keyed at X21. (The code used was inconsistent: X21 was keyed for some
years and X44 for others.)
For this data base, the missing detail was replaced with data from the employee-retirement publication and
the "DataFlag" variable was assigned the 'L' code.
Note: When missing data or detail were extracted from employee-retirement reports, it was sometimes
necessary to compute a residual amount. Generally, the residual was assigned to the largest retirement
code for a category (e.g., to code X11, Benefit Payments, for expenditures).
D. Before FY 1977, certain employee-retirement revenue data were mis-coded: contributions that local systems
received from other governments were incorrectly keyed as State Government Contribution to Own System
(X06) rather than at code X05. This data base reclassified them at their proper location (X05).
The significance of this error is that X06 is an intragovernmental transfer. As a result, it is excluded from
revenue totals and subtotals. Thus, totals published in City and County Government Finances are under-
stated by the amount mis-coded as X06 instead of X05. This will cause publication totals not to agree
with the data base.
Note that these contributions were reported correctly in the employee-retirement publications.
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10. Government ID Changes
Although most governments retain the ID number they are assigned originally, there are circumstances that result
in a government's ID being changed. Since a major purpose of this data base is tracking government finances
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over time, it is critical that a government possess the same ID for all years (unless the ID change had a major
structural cause).
Examples of ID changes include:
- All Alaska IDs were changed in the 1982 Census of Governments (12 governments in the data base retain
their old ID because they were disincorporated before the global change).
- New county incorporations, where governments in the new county area are re-assigned an ID based on the
new county code (e.g., La Paz County, AZ).
- Creation or dissolution of an independent city, which also affects the county code (e.g., Manassas City, VA).
- At one time it was common practice to change a special district's ID number if the county in which it was
headquartered changed (which may have been simply a new mailing address). Unfortunately, these were
rarely documented.
Consequently, if a government ID number was changed under any of the above scenarios, the ID used in this data
base is its current number (based on the "live" GID). That is, the ID for every year in the data base (including those
preceding the cause of the change) is its current one. There will also be a value in the data base variable, called
"IDChged," indicating the total number of ID changes identified.
There will also be an entry in a special data base reference table, called IDxWalk (ID crosswalk). This special table
has one record for every ID change identified and lists its previous ID as well. This file currently has 188 records,
most of which are the Alaska global ID changes.
Click here for more information about the special ID crosswalk table (IDxWalk)
Exceptions: This practice was not followed in cases where the ID change represented a major structural
alteration, such as: mergers or annexations where a government becomes structurally part of
another; city-county consolidations, in which the county is subsumed under the city's ID number ;
and conversions (e.g., a township that converts to a city government).
Unfortunately, the true extent of ID changes cannot be determined because they were not--and still are not--carefully
documented. Generally, when an ID number is changed today, the old ID is "disincorporated" and a new one
"incorporated." There is no link between the two IDs, however, except for a possible note in the GID "rulings" field.
Past practice in some cases was simply to change the ID number without leaving any trail.
Click here for more information on this topic (opens WordPerfect)
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11. Other Data Anomalies
The source files for this data base possessed numerous anomalies and peculiarities. These largely reflect that
for many years the goal of the finance survey was to issue publications, not perfectly clean data files. Among
the anomalies, many of which were undocumented, are these:
- Prior to FY 1977, there were two finance data files: one for the large jacket units (precursor of the 1200-word
record and no longer available) and a smaller one for all governments (the 400-word record used for the data
base). Data for jacket units were collapsed into this smaller file but this process often produced anomalies:
From FY 1967 to 1973, then jacket-only code A03 (charges for miscellaneous commercial activities) was
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displayed separately in the 400-word file but expenditures for this function (-03) were buried in general
expenditures, NEC (code -89).
Jacket units had more detailed codes for nonguaranteed debt. When the jacket units' data were collapsed
into the smaller file, these additional codes lost their "nonguaranteed" identity. As a result, published
nonguaranteed debt amounts for jacket units may be higher than that shown in the data base.
In the City and County Government Finances publications, the special jacket units table (based on the
larger file) may not agree with their data in other tables (based on the 400-word record).
Errors found in jacket unit data during the publication phase were sometimes corrected in the jacket unit file
but not the 400-word record file. Alternately, sometimes the error was corrected in the publication's jacket
unit table but no other tables (or vice versa).
- The FY 1974 source file has prior year data (1973) for three jacket units (except employee retirement data):
Jefferson County, AL, Baltimore County, MD and Monroe County, NY. Note that the 1974 County Government
Finances report provides 1974 data but it appears to have been typed (note darker font for these units).
- Before FY 1977, highways expenditures were reported as a single function (code -46). This code is included
in the data base under regular highways category (code -44) for those years. Similarly, all charges for highway
purposes (obsolete code A46) were included under A44 prior to fiscal 1977.
- The data base has 104,330 unique IDS, 8,832 of which are not in the GID. Eighty of these latter IDs are general
purpose governments.
- Liquor Stores data (code -90) appear to be missing from source files before fiscal year 1977, except those
in Montgomery County, MD and in census of governments years.
- Source files before fiscal 1977 were in whole dollars rather than thousands. This set a limit on the largest value
any field could hold. If a figure exceeded that amount, then the field contained a special "overflow" flag
(999999999). Few governments exceeded the limit (Port Authority of NY and NJ and Los Angeles County, CA
are two that did). For the data base, actual data were substituted for the overflow flag.
In theory, the overflow flag was spotted during the publication phase and actual data pasted into the report.
In practice, the overflow flagged was sometimes overlooked and published (e.g., Los Angeles County's
employee-retirement cash and securities data for fiscal 1974).
- Prior to fiscal 1988, intergovernmental revenue for transit subsidies were reported at codes B47, C47, and D47.
In fiscal 1988, these codes were replaced with B94, C94, and D94. For unknown reasons, the fiscal 1987 source
file contains no data for any of these codes. On the other hand, B47, C47, and D47 were rarely used for local
governments: only 21 local records reported data for these codes before fiscal 1988.
- There are over 300 records reporting negative values. Also, nearly 7,900 records show total salaries and
wages (exhibit code Z00) exceeding total current operations expenditures.
- Even if a finance code is "illegal" for a type of government, it is still possible to find data reported for it. To
illustrate, 18 school districts reported utility data between fiscal 1967 and 1975. U50 (donations) is a state
government-only revenue code but 82 local governments reported it (these amounts were added into U99).
Similarly, between fiscal 1988 and 1997, over 1,700 local governments reported data for what appears to be
a state government-only code: X06, state government contribution to its own retirement system.
- Data for certain finance codes were sometimes reported separately and included in other codes as well. This
practice applied primarily to files before FY 1977 (some codes listed below pertain to state governments only
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and therefore did not affect this data base):
Data for this finance code: Were sometimes duplicated in this code: Notes
A03 A89
A16 A18
A21 A12
A45 A46 In data base, A46 included in A44
A59 A89
B27 B89
T41 T49 In data base, T49 included in T40
E19 E21
E84 E89
In the data base, these amounts were "unduplicated."
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12. Records with No Data
The data base contains 42,149 records that are blank--i.e., every finance variable is zero. Most blank records
(89 percent) are for census of governments years and 92 percent are special districts. In addition, there are 490
records whose four major totals (revenue, expenditure, debt outstanding, and cash and security holdings) are
zero but they had data for at least one variable not included in any total (e.g., salaries and wages exhibit, code
Z00, or long-term debt retired or issued).
These records can be identified using the "ZeroFlag" variable, which consists of three possible codes:
'1' indicates that all finance variables are zero
'2' indicates that the four major totals are zero but at least one variable not in these totals has data
'0' indicates all other records
The following table provides a count of blank records, by type of government and survey year:
Survey Special School Exhibit*:
year Total Counties Cities Townships Districts Districts ZeroFlag = '2'
------ ------- -------- ------ --------- --------- --------- --------------
Total 42,149 14 1,055 1,733 38,686 661 490
1999 6 0 1 0 3 2 0
1998 5 0 1 0 3 1 10
1997 3,057 0 64 99 2,867 27 0
1996 0 0 0 0 0 0 0
1995 1 0 1 0 0 0 2
1994 3 0 0 0 0 3 3
1993 5 0 0 0 0 5 3
1992 7,153 0 50 114 6,935 54 121
1991 299 0 42 9 202 46 10
1990 403 4 39 9 257 94 7
1989 380 0 37 2 316 25 20
1988 258 1 29 4 203 21 15
1987 5,022 0 45 46 4,881 50 265
1986 222 2 30 44 143 3 1
1985 246 2 28 42 172 2 1
1984 258 1 27 49 177 4 2
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1983 333 3 19 10 299 2 2
1982 5,649 0 58 172 5,417 2 8
1981 281 0 57 94 129 1 0
1980 192 0 14 7 168 3 1
1979 325 0 58 81 184 2 1
1978 196 0 2 5 188 1 0
1977 6,826 0 177 250 6,395 4 3
1976 151 0 4 5 138 4 0
1975 170 0 4 7 154 5 0
1974 188 0 5 7 169 7 0
1973 233 0 7 9 186 31 0
1972 9,288 1 213 627 8,268 179 15
1971 299 0 12 15 240 32 0
1970 371 0 19 11 307 34 0
1967 329 0 12 15 285 17 0
* Shows number of governments whose four major totals are zero but report
data for one or more variables not included in these totals.
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13. Data Revisions
The source files from which this data base was developed were final, edited files. It was never the purpose of this
project to re-edit the data. Nonetheless, there were instances where the original data in source files were revised
for this data base. Some were official revisions never applied to the data files (e.g., publication errata notices).
Others resulted from the different environment and operating practices under which source files were created (e.g.,
the only employee-retirement data needed before FY 1977 for City and County Government finances were for the
jacket units). Other revisions were necessitated by their bizarre nature (e.g., a keying error for a small govern-
ment that ballooned its data).
Less than one percent of the data base received any type of data revision. Of these, 89 percent involved missing
employee-retirement data prior to fiscal 1977 (see Data User Note 9). Listed below are the most common types of
data revisions.
A. Post-publication errata changes (including ones applied only to the estimates historical data base). Major data
errors discovered after publication were corrected via errata notices. Lesser errors were announced in memo
form. Often, the data file involved was not corrected. If possible, these notices were applied to the data base
by, first, identifying errata changes made (studying publications, locating errata notices, referring to the System
2000 notes for estimates data base) and, second, applying the change to this data base if these items could
be identified: the government involved, the codes affected, and the amounts involved. These data base revisions
are identified with a DataFlag code of 'X'.
EXAMPLE: An errata notice was issued in 1977 for New York City covering three fiscal years of data: city
expenditures from the former Federal General Revenue Sharing program were missing for those
years. Although an errata notice had been issued, the three data files involved were never
corrected. This data base, however, includes these data revisions, which total $649 million in
underreported expenditure.
Note that many minor errata changes appear only as an "r" footnote in the following year's summary table and
thus could not be applied to the data base.
B. Jacket unit publication changes not applied to data file. It was once common practice to revise a publication
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but not the data file when an error was found in final stages of publication. The correct figures were literally cut
and pasted into the publication tables but the data file itself was often untouched. (These changes can be
detected by their slightly different typeface.) To identify such revisions, major totals for jacket units were
compared to the publications. Differences were scrutinized for evidence of these last minute revisions. If
found, and the codes involved could be identified, then the data base was revised to agree with the corrected
publication amount. These data base revisions are identified with a DataFlag code of 'P'.
EXAMPLE: Cook County, IL's total revenue for FY 1973 did not agree with the published amount due to a last
minute publication correction to local intergovernmental revenue. The correction was generated by
a keying error in code D79, which had been entered as 94,670 instead of 9,467 (in $000). This
error (if uncorrected) would have overstated Cook County's total revenue by over 18 percent.
C. Extreme outliers , where identified, were corrected. These data base revisions are identified with a DataFlag
code of 'K'.
EXAMPLE: In fiscal year 1974, state aid data (code C21) for ten small school districts were overstated by $10
billion each (sic). In contrast, C21 for all local governments was just $26.6 billion in that year.
Why or how $10 billion had been added to their C21 amounts is not clear; in any event, the data
base amounts were revised.
Perhaps the most typical outlier was a survey data correction, usually for a small government, that had been
keyed in whole dollars rather than in thousands. Outlier revisions will have a DataFlag code of 'K'.
Click here for detailed information about these data revisions (opens new spreadsheet)
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14. Substitution of Data Using Public-Use Files (FY 1981 and 1983)
The primary source files for this data base were the Census Bureau's internal, mainframe data files. One problem
with mainframe files was determining whether they were the final version for that fiscal year. Solving this riddle
involved the following tasks:
- Comparing the data for individual cities and counties to their respective publications.
- Comparing the data for individual governments to internal printouts (if available).
- Summarizing the data by population-size group and comparing them to published amounts.
- For census years, summarizing the data by type of government and comparing them to the Compendium of
Government Finances.
- Comparing the data electronically to the public-use version (if available), the assumption being that the latter file
was not released until the data were finalized (not always true).
This review revealed that source files for two years appeared incomplete: fiscal years 1981 and 1983. For these
years it was necessary to supplement the internal file with data from the public-use one, either to replace
records missing from the internal file or because its data were incomplete. Because the public-use version was
based on the smaller 400-word record, using it as a substitute had a number of consequences*.
1983: The internal version of this file suffered from a number of problems:
- It contained no data for school districts (type 5's). As a result, all data for these governments came from the
public-use version. Substitution in this situation, however, had little effect on the data base because (1) for
school districts less detail is collected compared to other types and (2) most data collected for them are
released in the public-use version. These 12,206 records are identified with a DataFlag code of 'A'.
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- The internal and public-use files did not contain the same records (exclusive of school districts). The internal
file contained 6,500 sample units that were not in the public-use file while the latter had 1,881 sample special
districts that were not in the internal one. The data base includes all these 8,381 sample records.
- The internal file contained 659 records that appeared to be incomplete based on comparison to the public-use
file, 92 percent of which were special districts. Data from the public-use file were substituted in these cases.
To minimize the impact of using the smaller file, each record was divided into four parts (revenue, expenditure,
debt, and cash and securities). Data were substituted only for the part(s) that were incomplete. To illustrate,
if only revenue data were incomplete, then only those data were substituted from the public-user file. The
DataFlag variable indicates which parts were replaced (number of governments whose data were replaced in
parenthesis):
'R' code indicates that all revenue data were substituted (644)
'E' code indicates that all expenditure data were substituted (605)
'D' code indicates that all debt data were substituted (20)
'C' code indicates that all cash and securities data were substituted (17)
Combinations of codes indicate that more than one part was replaced (e.g., 'RE' means that both revenues
and expenditures were replaced). The number of governments cited above does not equal 659 because of the
substitution of more than one part.
The table below summarizes the number of governments whose 1983 data were supplemented with those from
the public-use file, by type of government and DataFlag code (excluding school districts):
Special
DataFlag Total Counties Cities Townships Districts
-------- ----- -------- ------ --------- ---------
Total 659 15 28 7 609
D 1 1 0 0 0
E 13 4 1 0 8
ED 1 0 1 0 0
R 51 4 17 0 30
RD 2 0 1 1 0
RE 570 3 1 1 565
REC 5 1 1 3 0
RED 4 0 0 0 4
REDC 12 2 6 2 2
- The internal file contained 23,034 nonsample records (mostly cities and townships) that were not in the public-
use file. These records were excluded from the data base because (1) the problems cited above cast doubt
on the completeness of the internal data file and (2) the fact that they could not be compared to the public-use
file eliminated the best verification of their completeness.
1981: The internal version of this file was incomplete for three governments. Also, a major keying error was
discovered in a jacket unit:
- Denver CO's record was basically blank and was replaced with data from the public-use version. Interestingly,
the public-use file was missing data for two major codes (based on comparison to City Government Finances
report): T09 and M80. These missing data were added to the data base record. Denver was assigned these
DataFlag codes for 1981: 'REDC'.
- Debt data for Douglas County, NE and Everett WA were missing from the internal file and were supplemented
with data from the public-use version. These two units were assigned the 'D' DataFlag code for 1981.
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- Most of Philadelphia PA's tax data (i.e., codes T01, T40, and T99) were in millions of dollars rather than
thousands, thereby understating its revenue by over $835 million (39 percent). The data base file was revised
for this error and Philadelphia assigned the 'K' DataFlag code for 1981.
*Consequences of substituting public-use file data: The 400-word version lacks much detail found in the larger
internal file. Note that the data themselves are not missing but are subsumed into other categories (such as "all
other"). Substituting the smaller, public-use version has two major implications for historical research. First,
historical comparisons based on the missing detail will have gaps. Second, historical comparisons based on the
codes that subsume the missing ones will be overstated. This latter problem may be less apparent to users than
the sudden drop to zero for missing codes.
Click here for a more detailed description of these consequences (opens WordPerfect)
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15. Meaning of "DataFlag" Codes
To provide users with more information about individual records, the data base contains a special field, called the
"DataFlag." The Data Flag field may contain one or more code, as follows:
Code Description (number of records involved)
A All data (including nonfinance data) were replaced with those in public-use file's (14,087) *
C Cash and securities data were replaced with those in public-use file (18) %
D Debt data were replaced with those in public-use file (23) %
E Expenditure data were replaced with those in public-use file (606) %
F Reserved for employment historical data base
G Missing population, function code, or enrollment data replaced with data from employment file ("IndEmp")
K Keying and/or outlier error revised (39)
L Missing employee-retirement data were replaced with current year data from publications (199) #
M Missing employee-retirement data were replaced with prior year (5,933) @
N Negative value corrected in source file (5)
O Overflow flag found in source file (9)
P Publication table correction was not applied to source file (32)
Q Q11 extracted from M12 using Q11 data from school finance files (FY 1995 and 1996 school districts only)
R Revenue data were replaced with those in public-use file (645) %
S Salary & wages (Z00) data replaced with public-use file's but not any other expenditure data (14) &
X Errata notice revision not applied to source file (15)
Z Revision for reasons NEC (14)
* Applies only to fiscal year 1983 and represents special and school districts missing from the internal file,
requiring data in public-use file to be used.
% Applies only to fiscal years 1981 and 1983.
# Applies only to fiscal 1973-1976 jacket units.
@ Applies only to fiscal 1970, 1971, and 1973-1976.
& Applies to fiscal 1983 only.
To search for records with any of these codes, use the SAS "contains" operator. Example:
Where DataFlag Contains 'R' or DataFlag Contains 'E'
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16. "Jacket" Units (Largest Cities and Counties)
"Jacket units" are state governments and the very largest cities and counties whose finances are so complicated
that they are compiled by Census Bureau staff (rather than collected by regular survey methods, such as mail
canvass).
The data base contains a variable (JackFlag) indicating whether a government was a jacket unit for that fiscal year.
JackFlag of '1' indicates a jacket unit; a value of '0' indicates that it was not. This variable is based primarily on
a review of the special jacket unit table in City and County Government Finances reports. Note that for county
governments JackFlag equals '0' for years prior to fiscal 1973, the first year County Government Finances was
issued.
The criteria for jacket units for the period 1967 to 1992 were: for county governments, population of 500,000 or more
and for city governments, population of 300,000 or more. For 1993 and later surveys, the criteria were: for county
governments, population of 1,000,000 or more and for city governments, population of 500,000 or more.
The list below shows every city and county that was a jacket unit between 1967 and 1999. Unless otherwise
indicated, county governments were jackets from 1973 to 1999 and city governments were jackets from 1967
to 1999.
County Government Jacket Units: City Government Jacket Units:
No. ID Name ID Name
--- --------- ------------------------- --------- -----------------------------
1. 051001001 Alameda Co. 322001001 Albuquerque City (82-92)
2. 391002002 Allegheny Co. 112060002 Atlanta City (67-92)
3. 211003003 Baltimore Co. (73-92) 442227001 Austin City (77-92)
4. 311002002 Bergen Co. (73-92) 212004001 Baltimore City
5. 441015015 Bexar Co. 192017002 Baton Rouge-E Bat Roug(82-92)
6. 101006006 Broward Co. 012037003 Birmingham City (67-76)
7. 391009009 Bucks Co. (87-92) 222013001 Boston City
8. 311004004 Camden Co. (89-92) 332015005 Buffalo City (67-92)
9. 291002002 Clark Co. (84-92) 342060001 Charlotte City (82-92)
10. 051007007 Contra Costa Co. (73-92) 142016016 Chicago City
11. 141016016 Cook Co. 362031006 Cincinnati City (67-92)
12. 361018018 Cuyahoga Co. 362018014 Cleveland City
13. 441057057 Dallas Co. 362025003 Columbus City
14. 111044044 DeKalb Co. (87-92) 442057007 Dallas City
15. 391023023 Delaware Co. (73-92) 062016001 Denver City And Co. (67-92)
16. 141022022 Du Page Co. (73-92) 232082004 Detroit City
17. 441071071 El Paso Co. (84-92) 442071002 El Paso City (70-97)
18. 331015014 Erie Co. (73-92) 052010005 Fresno City (89-92)
19. 221005005 Essex Co., MA (73-92) 442220011 Ft Worth City (67-92)
20. 311007007 Essex Co., NJ (73-92) 122002001 Honolulu City And Co.
21. 471030030 Fairfax Co. (74-92) 442101008 Houston City
22. 361025025 Franklin Co. (73-92) 152049008 Indianapolis City
23. 051010010 Fresno Co. (82-92) 102016003 Jacksonville City (70-97)
24. 111060060 Fulton Co. (73-92) 262048006 Kansas City (67-92)
25. 361031031 Hamilton Co. (73-92) 052019026 Long Beach City (67-92)
26. 441101101 Harris Co. 052019027 Los Angeles City
27. 241027027 Hennepin Co. 182056014 Louisville City (67-81)
28. 101029029 Hillsborough Co. (73-92) 432079005 Memphis City
29. 311009009 Hudson Co. (73-92) 102013013 Miami City (70-92)
30. 261048048 Jackson Co. (73-92) 502041009 Milwaukee City
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31. 011037037 Jefferson Co., AL (73-92) 242027020 Minneapolis City (67-92)
32. 181056056 Jefferson Co., KY (73-92) 432019003 Nashville-Davidson (70-92)
33. 051015015 Kern Co. (89-92) 192036001 New Orleans City (67-92)
34. 481017017 King Co. 332031001 New York City
35. 151045045 Lake Co. (73-86) 312007009 Newark City (67-92)
36. 051019019 Los Angeles Co. 472122001 Norfolk City (67-76)
37. 231050050 Macomb Co. (73-92) 052001009 Oakland City (67-92)
38. 031007007 Maricopa Co. 372055015 Oklahoma City (67-92)
39. 101013013 Metropolitan Dade Co. 282028004 Omaha City (67-92)
40. 221009009 Middlesex Co., MA (73-97) 392051001 Philadelphia City
41. 311012012 Middlesex Co., NJ (73-92) 032007010 Phoenix City
42. 501041041 Milwaukee Co. (73-92) 392002056 Pittsburgh City (67-92)
43. 311013013 Monmouth Co. (82-92) 382026003 Portland City (67-92)
44. 331028026 Monroe Co. (73-92) 332028008 Rochester City (1967 Only)
45. 211016015 Montgomery Co., MD (73-92) 052034005 Sacramento City (87-92)
46. 361057057 Montgomery Co., OH (73-92) 442015010 San Antonio City
47. 391046046 Montgomery Co., PA (73-92) 052037010 San Diego City
48. 381026026 Multnomah Co. (73-92) 052038001 San Francisco City and Co.
49. 331030028 Nassau Co. 052043012 San Jose City (70-97)
50. 221011010 Norfolk Co. (73-92) 482017021 Seattle City
51. 231063063 Oakland Co. 262096001 St Louis City (67-92)
52. 371055055 Oklahoma Co. (73-92) 242062009 St Paul City (67-76)
53. 051030030 Orange Co., CA 362048007 Toledo City (67-92)
54. 101048048 Orange Co., FL (84-92) 032010002 Tucson City (82-92)
55. 101050050 Palm Beach Co. (82-92) 372072010 Tulsa City (70-92)
56. 481027027 Pierce Co. (84-92) 472132001 Virginia Beach City (87-92)
57. 031010010 Pima Co. (82-92) 092001001 Washington DC
58. 101052052 Pinellas Co. (73-92)
59. 211017016 Prince Georges Co. (73-92)
60. 051033033 Riverside Co. (74-97)
61. 051034034 Sacramento Co.
62. 451018018 Salt Lake Co. (76-92)
63. 051036036 San Bernardino Co.
64. 051037037 San Diego Co.
65. 051041040 San Mateo Co. (73-92)
66. 051043042 Santa Clara Co.
67. 431079079 Shelby Co. (73-92)
68. 261095095 St Louis Co. (73-92)
69. 331052047 Suffolk Co.
70. 361077077 Summit Co. (73-92)
71. 441220220 Tarrant Co.
72. 441227227 Travis Co. (87-92)
73. 371072072 Tulsa Co. (87-92)
74. 311020020 Union Co. (73-92)
75. 051056055 Ventura Co. (82-92)
76. 231082082 Wayne Co.
77. 331060055 Westchester Co. (73-92)
78. 221014012 Worcester Co. (73-92)
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17. Year of Population Data
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5. Important Data User Notes
Beginning with fiscal year 1987, the source file included a field that provided the reference period for its population
data. Shown below is the most common reference period for population data for each survey year. Note that
the actual population data for some governments may be for a different period (e.g., nonrespondents whose data
were extracted from an earlier survey). For survey years before 1987, the reference period cited is based on a
comparison of the population data to published amounts.
Survey Year of Survey Year of Survey Year of Survey Year of
Year Population Year Population Year Population Year Population
------ ------------ ------ ------------ ------ ------------ ------ ------------
1999 1998 1990 1988 1981 1980 1972 1970
1998 1996 1989 1988 1980 1980 1971 1970
1997 1996 1988 1986 1979 1977 1970 1970
1996 1996 1987 1986 1978 1977 1967 1960
1995 1994 1986 1986 1977 1975
1994 1994 1985 1984 1976 1975
1993 1990 1984 1982 1975 1973
1992 1990 1983 1982 1974 1973
1991 1990 1982 1980 1973 1970
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18. Information to Provide Outside Data Users
Below is the minimum information that should be provided to outside data users when filling special requests.
You may also need to provide more information on finance concepts and methodology of the finance survey.
TIP: Copy this section and paste into your word processor (as text) when preparing your cover letter.
<><><><><><><><><><><><>
Notes to Historical Finance Data on Individual Governments
(Beta Version of Data Base)
The electronic data being provided came primarily from a data base assembled from the Census Bureau's internal
data files on the finances of individual governments. These files came from either the annual finance survey or the
quinquennial census of governments.
This data base is still in the testing and review phase and is subject to change at any time without notice.
Users need to be aware that some of these internal data files were not originally designed to be released to the
public on a wide scale. Also, computer technology, practices and the environment in which they operated have
changed considerably over the period covered. To illustrate, for many years computer practices were dictated
by the finance survey's primary goal, to issue publications on a timely basis. Few data users had the capability to
handle data in the electronic form then available.
Information missing from the internal files (such as the government's name) was supplemented from other
sources. These sources may be the best available but are rarely perfect.
The period covered by these data may contain classification revisions or changes in the coverage of categories.
For example, in some years certain finance items were collected for all governments but in other years only
for the largest cities and counties. To the extent possible, the impact of these changes has been minimized
but cannot be totally eliminated.
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5. Important Data User Notes
The data may also contain anomalies, discrepancies, or inconsistencies. These may become more apparent when
comparing data for individual governments over a period of time. In most cases, these cannot be corrected or
even explained because the survey materials are no longer available.
These data may not be identical to previously-released data (either in publication or electronic forms). This is due to
numerous reasons, including revisions to publications that were not applied to data files, corrections to files after
the release of data, and limited data revisions that were applied to this historical data base.
The number of records available for each survey year varies depending on: whether it was a census of govern-
ments; the sample size for the annual finance survey; and whether the internal data file included nonsample units
in states where the Bureau had data collection arrangements with state governments.
If included, the population data are those found in the original finance data files. These population data may have
been updated since they were originally obtained.
Although the governments in this data base may have comprised a sample, the data themselves are not based
(wholly or partly) on a sample and therefore are not subject to any sampling variability. The statistical weight (if
provided) is for informational purposes only and should not be used to derive any other statistics.
The finance statistics provided are in terms of current dollar amounts at the time of reporting. They have not been
adjusted for price and wage changes occurring through the years.
If provided, the user guide for this data base (UserGuide.xls) is an internal census document and may contain
broken links or sections not relevant to outside data users.
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19. A Note on Federal and State Government Records
The focus of this data base is on local government finances. Federal and state government data are available in
the historical data base covering the finance "estimates" (state-by-type-of-government aggregates). This data
base is in Microsoft Access97 format. Data users can extract Federal and state data in a format comparable to the
"IndFin" data base by using special Access97 queries. Instructions on using these queries can be found here
(opens new spreadsheet):
\\Govs05\PEB\\Historical Data\Finance\Individual Units\Documentation\How to Add Fed and State Govt Data.xls
Including the Federal and state governments in this data base is a bit like putting the "square peg in a round hole."
Please note the following features about the data for these records:
- There are numerous finance codes that apply only to the Federal and/or state governments. These have been
subsumed into other categories. Examples--
Federal Customs Duties (T08) are included in General Sales Tax (T09).
Expenditures for Federal-only functions (e.g., National Defense and U.S. Postal Service) are included in the
General Expenditure NEC category.
Expenditures for Veterans' Services are also included in the General Expenditure NEC category.
- There are some Federal- and state-only finance codes that do not have local government equivalents. For
example, assistance and subsidies codes E19 (education) and E84 (veterans bonuses) do not apply to local
governments. While they are included in their respective totals, they are not displayed separately. For this
reason, calculating current operations for Education, NEC (E21) or for General Expenditure NEC (E89) will
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5. Important Data User Notes
include these assistance and subsidies amounts.
- Similarly, for the Federal Government only, the Employment Security Administration function has two intergov-
ernmental expenditure codes (L22 and M22). For local governments, this category is direct expenditure
only. Thus, calculating E22 for the Federal Government will include these two intergovernmental codes.
- Total insurance trust revenue and expenditure for the Federal and state governments include systems not
applicable to local governments (e.g., workers' compensation and Social Security). These systems are not
shown separately in this data base.
- Population are not for the same year as local records; generally, they are the same as the survey year. The
"How to" instructions above will replace the estimates pop data with those for the same year as the local records.
- No data are available for the Federal Government after fiscal year 1995.
- "Rex" and "Dac" contain no data for the Federal or state governments before fiscal year 1977 (except 1972).
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20. Miscellaneous FAQs
Please feel free to suggest other topics for FAQs; submit them to John Curry.
a. Why does the data base disagree with the publications?
b. Why are there no data for 1968 and 1969?
c. Why is there no data older than 1967?
d. What is excluded from the data base?
e. Why doesn't the number of records agree with the official counts for the census of governments?
f. Why are data reported for obsolete codes (e.g., Federal general revenue sharing receipts in FY 1993)?
g. Why is this data base in SAS when all other finance historical data bases are in Microsoft Access?
h. Does IndFin include ALL the individual finance codes?
a. Why does the data base disagree with the publications?
It is not unusual for the data base to disagree with finance publications. There are numerous reasons for these
differences; let us count the ways:
- The data file was not always frozen when the publication was completed. Thus, it may contain last-minute
corrections.
- Conversely, data errors spotted during the publication process often were corrected only in the reports them-
selves. These can often be denoted by the different font in the publication table (the numbers were literally
cut and pasted into the report). For the largest city and county governments, the special publication "jacket
unit" tables were reviewed for these types of corrections. If found and verified, the data base was also
corrected; see Data User Note 13.
- Large errors found after publication were revised in published errata notices or internal memoranda. The
data base contains these fixes, the original publication tables do not.
- Prior to fiscal 1977, City and County Government Finances used two files: the detailed, larger jacket unit file
for these governments and the standard, but smaller, file for all other governments. This data base is based
on the latter file. As described in Data User Note 11, the jacket unit data had to be collapsed into this smaller
file, sometimes resulting in data being published for the jacket units that do not appear in or agree with the data
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5. Important Data User Notes
base.
- The publications are sometimes wrong! For instance, 1973 City Government Finances shows Indianapolis IN
spending a negative amount for medical vendor payments while the 1979 one shows San Diego CA's general
expenditure exceeding its total expenditure. The 1974 County Government Finances report printed the
"overflow" flag for Los Angeles County, CA employee-retirement assets rather than the actual data.
- It is also possible the mainframe file downloaded for this data base was not the very last version (or at least
not the one used for publication).
- Interestingly, the data revisions described in Data User Note 13 have little to do with differences with published
amounts. For instance, only 47 cities with population over 50,000 (the cutoff for many years) received any type
of data revision. Only 41 counties with population over 100,000 (this type's cutoff) received any type of data
revision. (These counts exclude pre-1977 revisions for missing employee-retirement data, DataFlag codes 'L'
and 'M', since retirement data were published only for jacket units in those years.) Many data revisions
resulted in the data base agreeing with the publications (which the source file did not).
b. Why are there no data for 1968 and 1969?
The simple answer is that no data files for fiscal 1968 and 1969 exist. It appears that using a computer for the 1967
census of governments was a test. Punch card technology had been used successfully for years. The test was
declared a success and computer processing became standard with the fiscal 1970 finance survey.
c. Why are there no data older than 1967?
No data files before 1967 have been found--and none probably exist. Before the advent of computers and magnetic
storage media, data were stored primarily on punch cards.
We did retrieve from the National Archives a data file that supposedly contained jacket unit finances for 1964 to
1973 but the computer staff has not been able to read it.
d. What is excluded from the data base?
Not much, such as:
- Finances of the Federal and state governments (see historical data base of the finance estimates, "Rex-Dac").
- Data no longer being collected (e.g., cash and securities detail and debt functional detail) with a few exceptions,
like revenue from the old Federal General Revenue Sharing Program, which continues to interest data users.
- Character and object expenditure codes applicable only to the large "jacket" units (e.g., purchase of equipment,
prefix code "K").
e. Why doesn't the number of records agree with the official counts for the census of governments?
Until recently, there was no concentrated effort to have the various files released during a census of governments
agree in number of records. Listed below is the "official" count of local governments (from 1997's Volume 1) and
the number of records in the data base for that year:
Census Official # of Records
Year Count in Data Base
------ -------- ------------
1997 87,453 87,453
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5. Important Data User Notes
1992 84,955 84,955
1987 83,186 83,784
1982 81,780 82,566
1977 79,862 79,832
1972 78,218 78,216
Note: The data file for 1967 consists of the survey sample.
Even though the numbers are close, the data base contains thousands of empty records for census years ; see
Data User Note 12 for details.
f. Why are data reported for obsolete codes (e.g., Federal general revenue sharing receipts in FY 1993)?
These anomalies are largely the result of nonresponse imputation. Prior year data were used when current data
were unavailable. In some cases, this results in data being reported for codes that are obsolete in the current
survey. In the case of the 117 governments that reported receiving monies for the Federal general revenue sharing
program in FY 1993, all are prior year "plugs" dating from the fiscal 1987 or earlier surveys.
Another example is the 287 governments reporting state tax relief aid (C28) in fiscal year 1989. This code was
dropped after FY 1987 but data for these units were pulled from the 1987 and earlier surveys.
The "YrData" (Year of Data) variable tells you the actual fiscal year being reported. For earlier years, prior year
"plugs" were referred to as imputations and will have a YrData value of "II".
g. Why is this data base in SAS when all other finance historical data bases are in Microsoft Access?
To borrow a real estate expression, there are three reasons why SAS was chosen: size, size, and size:
A. SAS can store data in variable length records, greatly reducing storage space required. In contrast, a
Microsoft Access version of the data base would be 5-10 times larger, requiring 2.5 to 5 gigabytes of
storage space versus 500 megabytes for SAS.
B. SAS can store all 520+ variables in a single file. Other PC software, including MS Access, are limited to about
250 variables per table. Thus, the number of tables to manage is reduced by a third or more.
C. MS Access has other limitations, such as maximum table and data base size of one gigabyte. As a result,
the numerous tables required must be spread across three to five separate data bases.
D. With smaller records, fewer tables, and less fragmentation of the data, SAS queries run much faster than
other software.
E. SAS has extensive support in the Census Bureau.
Although data are in SAS format, you are not limited to using SAS for all your historical research. The SAS data
can be easily exported to other software. Data users should view the SAS version as a data bank from which
withdrawals--large or small--can be made as needed.
The following have been created to help users extract data:
A. An interactive application has been created to extract data from the data base and export them to either dBase
(dbf) or ASCII format (txt). Nearly all software can read either or both of these formats. This application should
fulfill 90+ percent of all queries, eliminating the need to write a single line of SAS code.
UserGuide.Xls (5. User Notes) 145 of 209
5. Important Data User Notes
Click here to view instructions on using the application.
B. For more advanced SAS users, sample SAS programs have been created These programs can be customized
as needed.
Click here to view these sample programs.
The data base can also be queried using SAS/Assist, the tool many staff members learned in the "Point and
Click" course.
h. Does IndFin include ALL the individual finance codes?
IndFin includes over 93 percent of the finance codes applicable to local, nonjacket units (including variables that can
be derived from the data base). Listed below is a comparison of the 515 finance codes that were reported in the
1997 Census of Governments (excluding employee-retirement exhibit codes and school system subcodes, which are
outside the scope of the basic finance survey) and their treatment in the IndFin data base.
# of Finance Codes Description
515 Total number of finance codes reported in 1997 finance file (May 2000 version)
337 Finance codes available in IndFin (including 83 that can be derived)
116 State government-only codes (outside scope of IndFin)
38 Local jacket-unit only codes (mostly the "K" equipment-only ones)
24 All other local finance codes, which consist of:
15 Intergovernmental revenue/expenditure codes for utilities*
4 Tax codes "possible" for DC but no data were reported for them in 1997
4 Liquor store exhibit codes applicable only to DC
1 Beginning short-term debt code (61V)
*Water, electric, and gas utility codes. Transit utility intergovernmental codes have always been in the finance file
(B47, M47, etc.).
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d receiving monies for the Federal general revenue sharing
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ment exhibit codes and school system subcodes, which are
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Go to Contents All code tested: 8/18/99
6. Sample SAS Programs for Querying the IndFin Data Base
This section provides sample SAS programs. Copy them to the clipboard, paste to the SAS Program Editor, and
modify as necessary to fit your particular application. This section assume you have a basic knowledge of SAS.
TIP: Add these lines to your AutoExec.Sas file:
OPTION Compress=Yes YearCutoff=1950;
LibName IndFIn '\\Govs05\PEB\Historical Data\Finance\Individual Units';
LibName MySAS 'C:\MyFiles\SAS';
LibName Library 'C:\MyFiles\SAS'; [Be sure to create 'C:\MyFiles\SAS' folder.]
Note: Do NOT store your files on the historical data server. They WILL be deleted at any time.
# Sample SAS Program Notes
1. Goal: Extracting county government tax data from 1991 file.
Data MySAS.CountTax;
Set IndFin.IndFin91;
Where Type = '1'; Note ' ' around type code, a character variable
Keep ID Name
C105 Total taxes
T01 Property taxes
T09 General sales taxes
C118 Total license taxes
C129; Total income taxes
Run;
2. Goal: Converting above SAS query to Microsoft Access97 TIP: Your can also export a file using SAS'
format. "Export" facility (under FILE menu)
Proc Export Data= MySAS.CountTax
OutTable= "County Taxes" Max number of fields for MDB format = 250
DBMS=Access97 Replace;
DataBase="C:\My Documents\CountyTaxes.mdb";
Run;
3. Goal: Extracting major finance totals for city governments
over 25,000 population from 1990 file.
Data MySAS.CityFin;
Set IndFin.IndFin90;
Where Type = '2' and Pop > 25000; No comma in population criteria
Keep ID Name
Pop Population is in whole numbers
C101 Total revenue
C301 Total expenditure
C1203 Total debt outstanding
C1801; Total cash and securities
Run;
4. Goal: Computing per capita data for counties between 200,000
UserGuide.Xls (6. SAS Samples) Page 169 of 209
6. Sample SAS Programs for Querying the IndFin Data Base
and 400,000 population in CA and FL from 1989 file.
Data MySAS.PerCaps;
Set IndFin.IndFin89;
Where Type = '1' and Pop GE 200000 and Pop LE 400000 and No comma in population criteria
(State = '05' or State = '10'); Note ' ' around type code and state codes
Keep ID Name
Pop Population is in whole numbers
C101 Total revenue
C301 Total expenditure
C1203 Total debt outstanding
C1801 Total cash and securities
TotRevPC Per capital total revenue
TotExpPC Per capital total expenditure
TotDebPC Per capital total debt outstanding
TotCSPC; Per capital total cash and securities
IF Pop NE 0 Then DO;
TotRevPC = ROUND(C101/(Pop/1000),.01); Be sure to divide Pop by 1000
TotExpPC = ROUND(C301/(Pop/1000),.01);
TotDebPC = ROUND(C1203/(Pop/1000),.01);
TotCSPC = ROUND(C1801/(Pop/1000),.01);
END;
ELSE DO; IF-THEN-ELSE statements avoid dividing by
TotRevPC = 0; zero
TotExpPC = 0;
TotDebPC = 0;
TotCSPC = 0;
END;
Format TotRevPC--TotCSPC Comma8.2; Displays results in 2 decimal places (cents)
Run;
Proc Print Label; Run;
5. Goal: Selecting cities over 50,000 pop and tabulating their total
taxes by state and population-size group (FY 1991).
Data MySAS.CertCity;
Set IndFin.IndFin91;
Where Type = '2' and Pop GT 50000; No comma in population criteria
Keep ID State Name
Pop
C105; Total taxes
Run;
Proc Format Library=Library; Create your own pop-size groups
Value Pop1Grp
750000-High = '750,000 or more'
500000-749999 = '500,000 to 749,999'
250000-499999 = '250,000 to 499,999'
50001-249999 = '50,001 to 249,999'
0-50000 = '50,000 or less'; No govts in query should fall into this group!
UserGuide.Xls (6. SAS Samples) Page 170 of 209
6. Sample SAS Programs for Querying the IndFin Data Base
Run;
Option PageSize = 55 LineSize = 127 Obs = Max This linesize is for printing in Landscape
NoDate NoNumber;
Proc Tabulate Data = MySAS.CertCity Missing
Format = Comma12. ORDER = Internal;
Class State Pop;
Var C105;
Table ALL State, C105*(Pop*Sum) / RTS=8; "RTS=8" reduces size of table stub
Title1 'Total Taxes Collected by Certainty Cities: FY 1991';
Title2 'By State and Population-Size Group';
Footnote '"." means no cities in that group';
Format Pop Pop1Grp.; Note period after format name
Label Pop = 'Population-Size Group'
C105 = 'Sum of Total Taxes';
KeyLabel Sum = ' ';
Run;
Option PageSize = 72 LineSize = 95;
6. Goal: Extracting selected revenue data (including all taxes) for Note that this method will exclude counties
counties over 100,000 population for ALL available years. whose pop falls below 100,000 in any year
*Create a macro variable called Vars--;
%Let Vars = C101 C105 T01--T99 C138 C183; Note how tax codes are selected by specifying
a range of variables using the double-hyphen
LibName MySAS 'C:\MyFiles\SAS'; (T01 -- T99)
Data MySAS.SelRev;
Set
IndFin.IndFin99 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin98 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin97 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin96 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin95 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin94 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin93 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin92 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin91 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin90 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin89 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin88 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin87 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin86 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin85 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin84 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin83 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin82 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin81 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin80 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin79 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin78 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin77 (Keep = ID Type Name SurveyYr Pop &Vars)
UserGuide.Xls (6. SAS Samples) Page 171 of 209
6. Sample SAS Programs for Querying the IndFin Data Base
IndFin.IndFin76 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin75 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin74 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin73 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin72 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin71 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin70 (Keep = ID Type Name SurveyYr Pop &Vars)
IndFin.IndFin67 (Keep = ID Type Name SurveyYr Pop &Vars);
Where type = '1' and pop gt 100000; No comma in population criteria
Run;
Proc Sort Data = MySAS.SelRev; This program sorts your output by ID and by
By ID Descending SurveyYr; year (from high to low)
Run;
7. Goal: Extracting data for all available census years using your You must first create a text file with the ID
own list of ID numbers. numbers you want--one ID per row/record.
FileName MyIDs 'C:\MyFiles\MyIDs.Txt'; Enter here the name of your text file of IDs.
FileName RevIDs 'C:\MyFiles\RevIDs.Txt';
Data _Null_; Do NOT modify this Data step.
InFILE MyIDs Length = LengA Missover End = Last; This step reads your IDs, cleans them up, and
Input @; outputs them as a SAS "Where" statement.
Input @1 ID $Varying200. LengA;
These next two lines clean up the file and strip
ID = Compress(ID,'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"~`!@#$%^&*()_+=-|}{:<>?[]\;,./''');
ID = Compress(Trim(ID)); ID = Substr(Left(ID),1,9); off first 9 digits of ID.
FILE RevIDs;
IF _N_ = 1 THEN PUT 'Where ID IN ('; Output the cleaned up IDs to a new text file.
IF Length(ID) = 9 THEN DO;
PUT @1 "'" @; The "Put "'" @;" statement uses pointer
PUT @2 ID @; controls (the "@" sign) to place single quote
PUT @11 "'" ; marks around each ID in your file.
END;
IF Last THEN PUT ');';
Run;
Data MySAS.MyIDs; Modify this Data step as needed.
Set This program uses the new text file to
IndFin.IndFin97 actually select the IDs you want.
IndFin.IndFin92
IndFin.IndFin87 This program may take a while if you have a
IndFin.IndFin82 very long list of IDs.
IndFin.IndFin77
IndFin.IndFin72
IndFin.IndFin67; Note: 1967 file includes only the sample units.
%Include RevIds; The "include" command inserts your "where"
Run; statement into the program.
Proc Sort; Optional.
UserGuide.Xls (6. SAS Samples) Page 172 of 209
6. Sample SAS Programs for Querying the IndFin Data Base
BY ID Descending SurveyYr;
Run;
8. Goal: Computing county area totals for 1992 census of govern- This program is valid only for census of gov-
ment file. ernment years (except 1967). Results may
not agree with published amounts.
Proc Summary Data = IndFin.IndFin92 MaxDec=0 NWay;
Output Out= COA92 Sum=;
Var C101--C1872;
Class State County;
ID SurveyYr Cen_Reg FIPS_ST;
Run;
Data COA92; This step adds county names to summary file.
Update COA92 (IN = A) Special file of county area names.
IndFin.CoAreas;
BY State County;
IF A;
DROP _TYPE_;
Run;
Data COA92; This next step deletes duplicative intergovern-
Set COA92; mental amounts.
C101 = C101 - C168; Revenues (D--)
C103 = C103 - C168;
C138 = C138 - C168;
C168=0; D11=0; D21=0; D30=0; D42=0; D46=0; D47=0;
D50=0; D79=0; D80=0; D89=0;
C301 = C301 - C317; Expenditures (M--)
C302 = C302 - C317;
C304 = C304 - C317;
C315 = C315 - C317;
C326 = C326 - C317;
C350 = C350 - M01; C391 = C391 - M05;
C406 = C406 - M12 - Q11 - M18 - M21; C412 = C412 - M12 - Q11;
C438 = C438 - M18; C456 = C456 - M21;
C478 = C478 - M23; C493 = C493 - M24;
C508 = C508 - M25; C529 = C529 - M29;
C562 = C562 - M32; C577 = C577 - M38;
C588 = C588 - M38; C603 = C603 - M44;
C608 = C608 - M44; C650 = C650 - M47;
C660 = C660 - M50; C675 = C675 - M52;
C740 = C740 - M59; C755 = C755 - M60;
C770 = C770 - M61; C785 = C785 - M62;
C800 = C800 - M66; C815 = C815 - M67 - M68 - M79;
C821 = C821 - M67; C831 = C831 - M68;
C858 = C858 - M79; C878 = C878 - M80;
C893 = C893 - M81; C916 = C916 - M87;
C938 = C938 - M89;
C317=0; M01=0; M05=0; M12=0; M18=0; M21=0; M23=0; M24=0;
M25=0; M29=0; M32=0; M38=0; M44=0; M47=0; M50=0; M52=0;
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6. Sample SAS Programs for Querying the IndFin Data Base
M59=0; M60=0; M61=0; M62=0; M66=0; M67=0; M68=0; M79=0;
M80=0; M81=0; M87=0; M89=0; Q11=0;
Run;
9. Goal: Extracting all tax data for Federal, state, and city
governments for 1997, 1992, 1987, and 1982.
Data Taxes;
SET IndFin.IndFin97 (Where = (Type = '2')) Federal data not available for FY 1997.
IndFin.IndFin92 (Where = (Type = '2'))
IndFin.IndFin87 (Where = (Type = '2'))
IndFin.IndFin82 (Where = (Type = '2'))
IndFin.FedState (Where = (SurveyYr in (97 92 87 82))); Note how this file has multiple years of data.
Keep SurveyYr -- T99;
Run;
Proc Sort;
BY ID Descending SurveyYr;
Run;
10. Goal: Exporting data from your own SAS program into an ASCII Requirements:
comma-delimited file. - Your SAS data set MUST contain these
two variables: SurveyYr and ID
Use the following SAS program: - Limited to datasets with 750 variables
- You must revise the program to show
UniversalExport.sas (a) the name of your SAS dataset to
export; (b) the name of the export files
Located in this folder: (if you don't like the default names); and
(c) what type of column headings to put in
\\Govs05\PEB\Historical Data\Finance\Individual Units\Documentation\ Record 1 (optional-default is variable label).
The program will divide your dataset into as
many as three ASCII text files. Record 1 will
contain column headings; data records will
begin in Record 2.
UserGuide.Xls (6. SAS Samples) Page 174 of 209
Go to Contents
7. SAS Formulas For Deriving "Calculable" Variables
The "IndFIn" data base provides two types of data: variables physically stored in the data tables and variables that can be derived fro
them. This section provides SAS formulas for deriving the latter type of data. Note that they represent all the formulas listed in the
Annotated Guide to Variables (section 2).
To use this page:
(1) Copy the formulas you need from Column (c) to the "clipboard" and paste into the SAS Program Editor.
(2) To create SAS labels and formats, also copy/paste the "Attrib" statements from Column (d).
Caution: The source files for 1967 through 1976 were in whole dollars. These numbers were rounded to thousands for the data base.
Thus, formulas below involving subtraction may produce minor positive or negative results (typically +1 and -1) due to round
Data Type Variable to Create SAS Formula
(a) (b) (c)
Revenue: Total Motor Veh & Oper License Taxes C123 = T24 + T25;
(6) Federal IG Rev-Total General Support C143 = B27 + B30;
State IG Rev-Total General Support C158 = C28 + C30;
Charges-Total Elem/Sec Education C187 = A09 + A10 + A12;
Charges-Total Highways C196 = A44 + A45;
Total Sale of Property Revenue C213 = U10 + U11;
Expenditure: Total intergovernmental formulas:
(113) Air Transportation C351 = C350-C352;
Corrections C392 = C391-C393;
Total Education C407 = C406-C408;
Elementary/Secondary Education C413 = C412-C414;
Higher Education C439 = C438-C440;
Education, NEC C457 = C456-C458;
Financial Administration C479 = C478-C480;
Fire Protection C494 = C493-C495;
Judicial and Legal C509 = C508-C510;
Central Staff Services C530 = C529-C531;
Health C563 = C562-C564;
Hospitals C589 = C588-C590;
Total Highways C604 = C603-C605;
Regular Highways (same as C604) C609 = C608-C610;
Transit Subsidies C651 = C650-E47;
Housing and Community Development C661 = C660-C662;
Libraries C676 = C675-C677;
UserGuide.Xls (7. Formulas) Page 175 of 209
7. SAS Formulas For Deriving "Calculable" Variables
Natural Resources C741 = C740-C742;
Parking Facilities C756 = C755-C757;
Parks and Recreation C771 = C770-C772;
Police Protection C786 = C785-C787;
Protective Inspection and Regulation C801 = C800-C802;
Public Welfare, Total C816 = C815-C817;
Public Welf-Categorical Assistance C822 = C821-E67;
Public Welf-Categ-IG to Fed Govt S67 = C821-E67-L67-M67;
Public Welf-Other Assistance Prog C832 = C831-E68;
Public Welfare, NEC C859 = C858-C860;
Sewerage C879 = C878-C880;
Solid Waste Management C894 = C893-C895;
Water Transport and Terminals C917 = C916-C918;
General Expenditure, NEC C939 = C938-C940;
Current operation formulas:
Air Transportation E01 = C352-C354;
Miscellaneous Commercial Activities E03 = C365-C367;
Corrections E05 = C393-C395;
Total Education C409 = C408-C410;
Elementary/Secondary Education E12 = C414-C416;
Higher Education E18 = C440-C442;
Education, NEC E21 = C458-C460;
Employment Security Administration E22 = C472-C474;
Financial Administration E23 = C480-C482;
Fire Protection E24 = C495-C497;
Judicial and Legal E25 = C510-C512;
Central Staff Services E29 = C531-C533;
General Public Buildings E31 = C551-C553;
Health E32 = C564-C566;
Total Hospitals C579 = C578-C580;
Own Hospitals E36 = C582-C584;
Other Hospitals E38 = C590-C592;
Total Highways C606 = C605-C607;
Regular Highways E44 = C610-C612;
Toll Highways E45 = C623-C627;
Housing and Community Development E50 = C662-C664;
Libraries E52 = C677-C679;
Natural Resources E59 = C742-C744;
UserGuide.Xls (7. Formulas) Page 176 of 209
7. SAS Formulas For Deriving "Calculable" Variables
Parking Facilities E60 = C757-C759;
Parks and Recreation E61 = C772-C774;
Police Protection E62 = C787-C789;
Protective Inspection and Regulation E66 = C802-C804;
Public Welfare, Total C818 = C817-C819-C820;
Public Welfare Institutions E77 = C843-C847;
Public Welfare, NEC E79 = C860-C862;
Sewerage E80 = C880-C882;
Solid Waste Management E81 = C895-C897;
Water Transport and Terminals E87 = C918-C920;
General Expenditure, NEC E89 = C940-C942;
Liquor Stores E90 = C953-C955;
Total Utilities C961 = C959-C960-C962;
Water Supply Utilities E91 = C965-I91-C968;
Electric Power Utilities E92 = C974-I92-C977;
Gas Supply Utilities E93 = C981-I93-C984;
Transit Systems Utilities E94 = C988-I94-C991;
Other capital outlay formulas:
Total Other Capital Outlay C309 = C307-C308;
General Other Capital Outlay C331 = C329-C330;
Air Transportation G01 = C354-F01;
Miscellaneous Commercial Activities G03 = C367-F03;
Corrections G05 = C395-F05;
Elementary/Secondary Education G12 = C416-F12;
Higher Education G18 = C442-F18;
Education, NEC G21 = C460-F21;
Employment Security Administration G22 = C474-F22;
Financial Administration G23 = C482-F23;
Fire Protection G24 = C497-F24;
Judicial and Legal G25 = C512-F25;
Central Staff Services G29 = C533-F29;
General Public Buildings G31 = C553-F31;
Health G32 = C566-F32;
Own Hospitals G36 = C584-F36;
Other Hospitals G38 = C592-F38;
Regular Highways G44 = C612-F44;
Toll Highways G45 = C627-F45;
Housing and Community Development G50 = C664-F50;
UserGuide.Xls (7. Formulas) Page 177 of 209
7. SAS Formulas For Deriving "Calculable" Variables
Libraries G52 = C679-F52;
Natural Resources G59 = C744-F59;
Parking Facilities G60 = C759-F60;
Parks and Recreation G61 = C774-F61;
Police Protection G62 = C789-F62;
Protective Inspection and Regulation G66 = C804-F66;
Public Welfare Institutions G77 = C847-F77;
Public Welfare, NEC G79 = C862-F79;
Sewerage G80 = C882-F80;
Solid Waste Management G81 = C897-F81;
Water Transport and Terminals G87 = C920-F87;
General Expenditure, NEC G89 = C942-F89;
Liquor Stores G90 = C955-F90;
Total Utilities C964 = C962-C963;
Water Supply Utilities G91 = C968-F91;
Electric Power Utilities G92 = C977-F92;
Gas Supply Utilities G93 = C984-F93;
Transit Systems Utilities G94 = C991-F94;
Other expenditure formulas:
Health & Hospitals-Total Expenditure C557 = C562+C577;
Health & Hospitals-Direct Expenditure C559 = C564+C578;
Health & Hospitals-Capital Outlays C561 = C566+C580;
Total Vendor Payments C3027 = E74 + E75;
Debt: LTD Issued-General-Education C1240 = C1241 + C1242;
(11) LTD Issued-FFC-Education C1263 = C1264 + C1265;
LTD Issued-NG-Education C1331 = _24F + _24G;
LTD Issued-Unspecified-Education C1355 = _29F + _29G;
LTD Retired-General-Education C1409 = C1410 + C1411;
LTD Retired-FFC-Education C1432 = C1433 + C1434;
LTD Retired-NG-Education C1500 = _34F + _34G;
LTD Retired-Unspecified-Education C1524 = _39F + _39G;
LTD Outstanding-General-Education C1578 = C1579 + C1580;
LTD Outstanding-FFC-Education C1609 = _41F + _41G;
LTD Outstanding-NG-Education C1677 = _44F + _44G;
UserGuide.Xls (7. Formulas) Page 178 of 209
7. SAS Formulas For Deriving "Calculable" Variables
s two types of data: variables physically stored in the data tables and variables that can be derived from
AS formulas for deriving the latter type of data. Note that they represent all the formulas listed in the
ed from Column (c) to the "clipboard" and paste into the SAS Program Editor.
formats, also copy/paste the "Attrib" statements from Column (d).
67 through 1976 were in whole dollars. These numbers were rounded to thousands for the data base.
nvolving subtraction may produce minor positive or negative results (typically +1 and -1) due to rounding.
SAS Label and Format
(d)
Attrib C123 Format = Comma12. Label = 'TotMVehLic';
Attrib C143 Format = Comma12. Label = 'FIGR_TotGS';
Attrib C158 Format = Comma12. Label = 'SIGR_TotGS';
Attrib C187 Format = Comma12. Label = 'Chg_TotES';
Attrib C196 Format = Comma12. Label = 'Chg_TotHwy';
Attrib C213 Format = Comma12. Label = 'TotPropSal';
Attrib C351 Format = Comma12. Label = 'Airp_IGE';
Attrib C392 Format = Comma12. Label = 'Correc_IGE';
Attrib C407 Format = Comma12. Label = 'TotEd_IGE';
Attrib C413 Format = Comma12. Label = 'ElSEd_IGE';
Attrib C439 Format = Comma12. Label = 'HiEd_IGE';
Attrib C457 Format = Comma12. Label = 'OthEd_IGE';
Attrib C479 Format = Comma12. Label = 'FinAdm_IGE';
Attrib C494 Format = Comma12. Label = 'Fire_IGE';
Attrib C509 Format = Comma12. Label = 'Judic_IGE';
Attrib C530 Format = Comma12. Label = 'CStaff_IGE';
Attrib C563 Format = Comma12. Label = 'Health_IGE';
Attrib C589 Format = Comma12. Label = 'OthHos_IGE';
Attrib C604 Format = Comma12. Label = 'TotHwy_IGE';
Attrib C609 Format = Comma12. Label = 'RegHwy_IGE';
Attrib C651 Format = Comma12. Label = 'TranSb_IGE';
Attrib C661 Format = Comma12. Label = 'HoCD_IGE';
Attrib C676 Format = Comma12. Label = 'Libry_IGE';
UserGuide.Xls (7. Formulas) Page 179 of 209
7. SAS Formulas For Deriving "Calculable" Variables
Attrib C741 Format = Comma12. Label = 'NatRes_IGE';
Attrib C756 Format = Comma12. Label = 'Parkg_IGE';
Attrib C771 Format = Comma12. Label = 'PrkRec_IGE';
Attrib C786 Format = Comma12. Label = 'Police_IGE';
Attrib C801 Format = Comma12. Label = 'ProtRg_IGE';
Attrib C816 Format = Comma12. Label = 'Welf_IGE';
Attrib C822 Format = Comma12. Label = 'Wel_Ct_IGE';
Attrib S67 Format = Comma12. Label = 'Wel_Ct_Fed';
Attrib C832 Format = Comma12. Label = 'Wel_Cs_IGE';
Attrib C859 Format = Comma12. Label = 'OthWel_IGE';
Attrib C879 Format = Comma12. Label = 'Sewer_IGE';
Attrib C894 Format = Comma12. Label = 'SWMgmt_IGE';
Attrib C917 Format = Comma12. Label = 'WatTrn_IGE';
Attrib C939 Format = Comma12. Label = 'GenNEC_IGE';
Attrib E01 Format = Comma12. Label = 'Airp_Opr';
Attrib E03 Format = Comma12. Label = 'MisCom_Opr';
Attrib E05 Format = Comma12. Label = 'Correc_Opr';
Attrib C409 Format = Comma12. Label = 'TotEd_Opr';
Attrib E12 Format = Comma12. Label = 'ElSEd_Opr';
Attrib E18 Format = Comma12. Label = 'HiEd_Opr';
Attrib E21 Format = Comma12. Label = 'OthEd_Opr';
Attrib E22 Format = Comma12. Label = 'EmpSec_Opr';
Attrib E23 Format = Comma12. Label = 'FinAdm_Opr';
Attrib E24 Format = Comma12. Label = 'Fire_Opr';
Attrib E25 Format = Comma12. Label = 'Judic_Opr';
Attrib E29 Format = Comma12. Label = 'CStaff_Opr';
Attrib E31 Format = Comma12. Label = 'GenBld_Opr';
Attrib E32 Format = Comma12. Label = 'Health_Opr';
Attrib C579 Format = Comma12. Label = 'Hosp_Opr';
Attrib E36 Format = Comma12. Label = 'OwnHos_Opr';
Attrib E38 Format = Comma12. Label = 'OthHos_Opr';
Attrib C606 Format = Comma12. Label = 'TotHwy_Opr';
Attrib E44 Format = Comma12. Label = 'RegHwy_Opr';
Attrib E45 Format = Comma12. Label = 'TolHwy_Opr';
Attrib E50 Format = Comma12. Label = 'HoCD_Opr';
Attrib E52 Format = Comma12. Label = 'Libry_Opr';
Attrib E59 Format = Comma12. Label = 'NatRes_Opr';
UserGuide.Xls (7. Formulas) Page 180 of 209
7. SAS Formulas For Deriving "Calculable" Variables
Attrib E60 Format = Comma12. Label = 'Parkg_Opr';
Attrib E61 Format = Comma12. Label = 'PrkRec_Opr';
Attrib E62 Format = Comma12. Label = 'Police_Opr';
Attrib E66 Format = Comma12. Label = 'ProtRg_Opr';
Attrib C818 Format = Comma12. Label = 'Welf_Opr';
Attrib E77 Format = Comma12. Label = 'Wel_In_Opr';
Attrib E79 Format = Comma12. Label = 'OthWel_Opr';
Attrib E80 Format = Comma12. Label = 'Sewer_Opr';
Attrib E81 Format = Comma12. Label = 'SWMgmt_Opr';
Attrib E87 Format = Comma12. Label = 'WatTrn_Opr';
Attrib E89 Format = Comma12. Label = 'GenNEC_Opr';
Attrib E90 Format = Comma12. Label = 'LiqStr_Opr';
Attrib C961 Format = Comma12. Label = 'Util_Opr';
Attrib E91 Format = Comma12. Label = 'WatUtl_Opr';
Attrib E92 Format = Comma12. Label = 'EleUtl_Opr';
Attrib E93 Format = Comma12. Label = 'GasUtl_Opr';
Attrib E94 Format = Comma12. Label = 'TrnUtl_Opr';
Attrib C309 Format = Comma12. Label = 'TotOthCap';
Attrib C331 Format = Comma12. Label = 'GenOthCap';
Attrib G01 Format = Comma12. Label = 'Airp_OCp';
Attrib G03 Format = Comma12. Label = 'MisCom_OCp';
Attrib G05 Format = Comma12. Label = 'Correc_OCp';
Attrib G12 Format = Comma12. Label = 'ElSEd_OCp';
Attrib G18 Format = Comma12. Label = 'HiEd_OCp';
Attrib G21 Format = Comma12. Label = 'OthEd_OCp';
Attrib G22 Format = Comma12. Label = 'EmpSec_OCp';
Attrib G23 Format = Comma12. Label = 'FinAdm_OCp';
Attrib G24 Format = Comma12. Label = 'Fire_OCp';
Attrib G25 Format = Comma12. Label = 'Judic_OCp';
Attrib G29 Format = Comma12. Label = 'CStaff_OCp';
Attrib G31 Format = Comma12. Label = 'GenBld_OCp';
Attrib G32 Format = Comma12. Label = 'Health_OCp';
Attrib G36 Format = Comma12. Label = 'OwnHos_OCp';
Attrib G38 Format = Comma12. Label = 'OthHos_OCp';
Attrib G44 Format = Comma12. Label = 'RegHwy_OCp';
Attrib G45 Format = Comma12. Label = 'TolHwy_OCp';
Attrib G50 Format = Comma12. Label = 'HoCD_OCp';
UserGuide.Xls (7. Formulas) Page 181 of 209
7. SAS Formulas For Deriving "Calculable" Variables
Attrib G52 Format = Comma12. Label = 'Libry_OCp';
Attrib G59 Format = Comma12. Label = 'NatRes_OCp';
Attrib G60 Format = Comma12. Label = 'Parkg_OCp';
Attrib G61 Format = Comma12. Label = 'PrkRec_OCp';
Attrib G62 Format = Comma12. Label = 'Police_OCp';
Attrib G66 Format = Comma12. Label = 'ProtRg_OCp';
Attrib G77 Format = Comma12. Label = 'Wel_In_OCp';
Attrib G79 Format = Comma12. Label = 'OthWel_OCp';
Attrib G80 Format = Comma12. Label = 'Sewer_OCp';
Attrib G81 Format = Comma12. Label = 'SWMgmt_OCp';
Attrib G87 Format = Comma12. Label = 'WatTrn_OCp';
Attrib G89 Format = Comma12. Label = 'GenNEC_OCp';
Attrib G90 Format = Comma12. Label = 'LiqStr_OCp';
Attrib C964 Format = Comma12. Label = 'Util_OCp';
Attrib G91 Format = Comma12. Label = 'WatUtl_OCp';
Attrib G92 Format = Comma12. Label = 'EleUtl_OCp';
Attrib G93 Format = Comma12. Label = 'GasUtl_OCp';
Attrib G94 Format = Comma12. Label = 'TrnUtl_OCp';
Attrib C557 Format = Comma12. Label = 'TotHltHosp';
Attrib C559 Format = Comma12. Label = 'DirHltHosp';
Attrib C561 Format = Comma12. Label = 'HltHospCap';
Attrib C3027 Format = Comma12. Label = 'TotVendPmt';
Attrib C1240 Format = Comma12. Label = 'TotIss_Ed';
Attrib C1263 Format = Comma12. Label = 'FFCIss_Ed';
Attrib C1331 Format = Comma12. Label = 'NGIss_Ed';
Attrib C1355 Format = Comma12. Label = 'UnsIss_Ed';
Attrib C1409 Format = Comma12. Label = 'TotRet_Ed';
Attrib C1432 Format = Comma12. Label = 'FFCRet_Ed';
Attrib C1500 Format = Comma12. Label = 'NGRet_Ed';
Attrib C1524 Format = Comma12. Label = 'UnsRet_Ed';
Attrib C1578 Format = Comma12. Label = 'TotOut_Ed';
Attrib C1609 Format = Comma12. Label = 'FFCOut_Ed';
Attrib C1677 Format = Comma12. Label = 'NGOut_Ed';
UserGuide.Xls (7. Formulas) Page 182 of 209
8. Using the SAS Query Applic
from the Historical Finance
UserGuide.Xls (8. Query Application) Page 183 of 209
8. Using the SAS Query Applic
from the Historical Finance
General rules:
Start Application:
Intro:
WhatDrv:
QType:
Special:
UserGuide.Xls (8. Query Application) Page 184 of 209
8. Using the SAS Query Applic
from the Historical Finance
Select1:
Fiscal Years:
Variables:
UserGuide.Xls (8. Query Application) Page 185 of 209
8. Using the SAS Query Applic
from the Historical Finance
Type of government:
UserGuide.Xls (8. Query Application) Page 186 of 209
8. Using the SAS Query Applic
from the Historical Finance
Options:
States:
UserGuide.Xls (8. Query Application) Page 187 of 209
8. Using the SAS Query Applic
from the Historical Finance
Individual Units:
SortMe:
Results1:
ExportQ:
Results2:
WhatNext:
KeyWords:
Multi-category:
ALLData
ALLMajTotals
ALLEmpRet
UserGuide.Xls (8. Query Application) Page 188 of 209
8. Using the SAS Query Applic
from the Historical Finance
Revenues:
ALLRev
ALLMajRevTot
ALLTaxes
ALLSalesTax
ALLLicenses
ALLIGRev
ALLFedIGR
ALLStateIGR
ALLLocalIGR
ALLGenChgs
ALLMiscRev
ALLUtilRev
ALLInsrTrRev
Expenditures:
ALLExp
ALLMajExpTot
ALLTotalExp
ALLTotIGExp
ALLIGExpDet
ALLDirectExp
ALLCurOp
ALLCapOut
ALLConstr
ALLOthCap
ALLEducExp
ALLHltHospExp
ALLHwyExp
ALLWelfExp
ALLUtilExp
ALLInsrTrExp
Debt:
ALLDebt
ALLMajDebtTot
ALLIssDebt
ALLRetDebt
ALLOutDebt
Cash and Securities:
ALLCashSec
* This KeyWord will create variables that are not in the data base.
UserGuide.Xls (8. Query Application) Page 189 of 209
8. Using the SAS Query Applic
from the Historical Finance
Version
2.22
2.21
2.20
2.12
2.11
2.1
2.0
1.0
UserGuide.Xls (8. Query Application) Page 190 of 209
Go to Contents
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
What Does It Do?
Does It Do
Everything?
What Is in the
Data Base?
Where Do I Get
More Details
About this
Data Base?
What Do I Need
to Use the Query
Application?
How Do I View
the Results of
My Query?
Can I Use My Query
Results in Other Soft-
ware (like Microsoft
Access or Excel)?
Please Note:
UserGuide.Xls (8. Query Application) Page 191 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
How Do I Use It?
General rules:
Start Application:
Intro:
WhatDrv:
QType:
Special:
UserGuide.Xls (8. Query Application) Page 192 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
Select1:
Fiscal Years:
Variables:
UserGuide.Xls (8. Query Application) Page 193 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
Type of government:
UserGuide.Xls (8. Query Application) Page 194 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
Options:
States:
UserGuide.Xls (8. Query Application) Page 195 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
Individual Units:
SortMe:
Results1:
ExportQ:
Results2:
WhatNext:
KeyWords:
Multi-category:
ALLData
ALLMajTotals
ALLEmpRet
UserGuide.Xls (8. Query Application) Page 196 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
Revenues:
ALLRev
ALLMajRevTot
ALLTaxes
ALLSalesTax
ALLLicenses
ALLIGRev
ALLFedIGR
ALLStateIGR
ALLLocalIGR
ALLGenChgs
ALLMiscRev
ALLUtilRev
ALLInsrTrRev
Expenditures:
ALLExp
ALLMajExpTot
ALLTotalExp
ALLTotIGExp
ALLIGExpDet
ALLDirectExp
ALLCurOp
ALLCapOut
ALLConstr
ALLOthCap
ALLEducExp
ALLHltHospExp
ALLHwyExp
ALLWelfExp
ALLUtilExp
ALLInsrTrExp
Debt:
ALLDebt
ALLMajDebtTot
ALLIssDebt
ALLRetDebt
ALLOutDebt
Cash and Securities:
ALLCashSec
* This KeyWord will create variables that are not in the data base.
UserGuide.Xls (8. Query Application) Page 197 of 209
8. Using the SAS Query Application to Ex
from the Historical Finance Data Base (
Query Application Update Log
As of: 6-Sep-2001
Version
2.22
2.21
2.20
2.12
2.11
2.1
2.0
1.0
UserGuide.Xls (8. Query Application) Page 198 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
The purpose of this application is to provide an easy method for extracting data from the
historical finance data base. It is designed for people with basic knowledge of SAS (e.g.,
from the "Point and Click" course) as well as advanced SAS users.
You select which years, variables, states, and types of governments to extract. You can
limit your query to governments meeting specific population or data criteria (e.g., counties
over 100,000 population or any city with an income tax). You can select individual govern-
ments as well. You can also sort the output any way you want.
We expect the application to meet 90 percent or more of the query needs for this data base.
Note that it can also be used as a starting point for more elaborate queries: the SAS file
it creates can be processed further using SAS/Assist or regular SAS code.
The database contains finance data for individual governments for fiscal years 1967 and
1970 to 1999. It has over 500 finance data items, including major totals and subtotals*.
An additional 130+ finance items can be derived from them.
*For full data on the Federal or state governments, use the Microsoft Access historical
finance data bases ("Rex-Dac" and "Hist-Fin"); see Data User Notes 3 and 19.
This Excel spreadsheet has everything you need to know about the database:
\\Govs05\PEB\Historical Data\Finance\Individual Units\Documentation\UserGuide.xls
Be sure to read its important "Data User Notes" section.
There are just three requirements for using this application:
1. SAS software must be installed on your PC.
2. You must have access to the Historical Data Server (\\Govs05\PEB\Historical Data).
3. These two lines should be in your AutoExec.SAS file:
LibName IndFin '\\Govs05\PEB\Historical Data\Finance\Individual Units';
Options MStored SASMStore = IndFin Compress=Yes YearCutoff=1950;
Note: The application assumes that function key F8 is the SUBMIT command. If not,
substitute the function key that is.
The query application will ask if you want to view your results.
TIP: You can also use the SAS "ViewTable" facility. When the query is done, the LOG
window will display the ViewTable command for viewing your dataset. Copy this command,
paste it in the Program Editor, and then submit it.
Yes. The application will offer to export your data into Access97 (mdb), Excel97 (xls), ASCII
(txt), or dBase (dbf) format. (Excel97 is limited to queries of 25,000 records or less.)
TIP: Export the query to ASCII format since it creates a much smaller file than other
formats. It also provides longer, more meaningful variable names.
To learn how people use the data base, this application keeps track of what people are
extracting (e.g., the years, variables, and states, whether individual states or governments
are selected, the frequency of exporting the data base). It does not keep track of who is
UserGuide.Xls (8. Query Application) Page 199 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
extracting data. To see the latest user statistics, submit this SAS program:
%Include '\\Govs05\PEB\Historical Data\Finance\Individual Units\HSTabs.SAS';
TIP: Copy this command, paste it into the SAS Program Editor, and submit it.
Here are screen-by-screen directions for using the query application:
- Upper/lower case does NOT matter: t01 is the same as T01.
- Indicate your choices with an X (except your list of variables and record selection criteria).
- To move around the screens, use the Tab, Shift-Tab, and Arrow keys--or your mouse.
- On multiple choice screens, the first option is always the default.
- To quit the application, enter an X next to "Exit!" in the bottom right corner of most screens.
- SAS commands in these instructions can be copied and pasted into the SAS Program Editor.
Begin a SAS session by clicking the SAS icon on your Desktop.
Enter this command in the Program Editor and then submit it (press the F8 key)*:
%HSQuery1;
*NOTE:
- If you did not add the two lines above to your AutoExec.SAS file, you will first have to
compile the program by submitting the following:
%Include '\\Govs05\PEB\Historical Data\Finance\Individual Units\HSQuery1.SAS';
FREQUENT USER TIP:
- Add "%HSQuery1;" to your AutoExec.SAS to start the application automatically.
This informational screen normally appears once per SAS session.
This screen will appear only if there is a problem accessing the historical data server. If
you encounter this screen, please contact John Curry (x1582).
Select the type of query you want to do:
- "Regular" query extracts finance data from the data base.
- "Per Capita" query converts the finance data to per capita amounts (in dollars and cents).
- "Specialized" query takes you to another screen (Special).
Select one of two types of specialized query (both have per capita choices):
- Option A provides an alternate method for extracting records based on your selection
criteria. It identifies records in the latest available census year (1997) meeting your
selection criteria and extracts data for those same records for all years requested.
UserGuide.Xls (8. Query Application) Page 200 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
All other queries apply your selection criteria separately to each survey year selected.
To illustrate the difference, do a query selecting cities over 100,000 population for every
year. City X's population did not exceed 100,000 until 1982. Option A would include City
X for every year. But ALL other queries would extract data for City X only for 1982 and
later years.
- Option B rearranges the data so that years appear as fields rather than separate rows.
It is limited to ONE data variable and will automatically select all available years. It will
take longer to do than other queries. This example selects property taxes (T01) for all
cities with population of 1,000,000 or more (not every year or data item is shown below):
A "normal" query would produce output something like this:
Survey Yr ID Name T01
97 052019027 Los Angeles City 680,389
96 052019027 Los Angeles City 606,870
95 052019027 Los Angeles City 665,239
97 052037010 San Diego City 128,683
96 052037010 San Diego City 129,909
95 052037010 San Diego City 135,110
Option B would produce output something like this:
ID Name 1997 1996 1995 1994 1993 1992
052019027 Los Angeles City 680,389 606,870 665,239 641,813 725,142 774,409
052037010 San Diego City 128,683 129,909 135,110 138,122 146,239 156,402
The "response" variables indicate whether a record was included in the file for that year. For
example, if "Response96" equals zero for a record, it was NOT included in the 1996 data file
while a "1" indicates that it was included in that file.
First of two screens for selecting the data and records you want. It has three sections:
Put an X to the LEFT of each year you want (or select "All Available Years").
You MUST select at least one year.
Do NOT enter general variables, like ID, name, population, etc. They will be appended
automatically. The RULES:
- You MUST enter at least one variable name (or keyword).
- There are three ways to enter variables. You can mix and match all three ways, like this:
UserGuide.Xls (8. Query Application) Page 201 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
T01 T09 B01--b89 ALLExp
The three ways to enter variables are--
(1) List each SAS variable individually, separated by a space:
Good: T01 T09 T99
t01 T09 t99
Bad: T01 T09t99 [no space between T09 and T99]
T01 , T09 , T99 [no commas allowed!]
(2) List a range of variables connected with a double hyphen ("--"):
Examples: T01--T99 [all individual tax codes]
C350--M01 [all airport expenditures]
NOTE: When citing a range of variables, you MUST list them in the order shown
in the "Annotated Guide to Variables," as these examples illustrate:
Good: T01--T99
Bad: T99--T01 [T01 should be listed first: T01--T99]
(3) List any keyword specially created for this application. You can list more than one:
Examples: AllDirectExp AllMajDebtTot
Available keywords are listed at the end of these instructions.
This is where you specify which governments to select:
- You MUST select one or more type of government or select individual units on the
next screen (or both).
- Put an X to the LEFT of each type you want (or select "All Types (1-5)").
- You can limit your query to governments that meet selected criteria (e.g., counties over a
specified population, any city who reported data for T40, airport special districts):
- Enter your criteria on the line to the RIGHT of each type of government to be selected*.
- Enter your selection criteria as an expression having this form--
[Variable] [Operator] [Value]
Examples: POP GE 100000
T40 GT 0
POP EQ 01 [to select airport special districts]
UserGuide.Xls (8. Query Application) Page 202 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
Valid operators are: EQ [equal to] NE [not equal to]
GT [greater than] GE [greater than or equal to]
LT [less than] LE [less than or equal to]
BETWEEN x AND y [use to express a range]
- You can specify more than one criteria on a line using "AND" or "OR":
Examples: T40 GT 0 and POP LT 10000
POP EQ 01 or POP eq 24 [special district function codes]
POP Between 10000 and 100000
- Avoid putting commas in your selection criteria:
Good: POP GT 100000
Bad: POP GT 100,000
- Do not use the CONTAINS operator.
- You can use any variable in the data base for your selection criteria except these three:
Name
Version
DataFlag (but you can use this criteria: DataFlag NE '' )
*POWER USER TIPS:
- To specify selection criteria for ALL types of governments, enter it on the "All Types" line.
- To override this "global" criteria for a particular type of government, enter different data
selection criteria on the line to its right.
Example: To select city, county, townships, and school districts with a population/
enrollment over 10,000 AND all hospital districts, enter these two criteria:
On the "All Types" line: POP GT 10000
On the "Special Districts" line: Pop eq 40
- You can also specify formulas in your data selection criteria, such as this per capita:
(T01/(POP / 1000)) GT 100 [per capita property taxes over $100]
(C352-C354) GT 1000 [airport current operations over $1 million]
Second of two screens for selecting records you want. It has two sections, both of which
are optional:
Put an X to the LEFT of each state you want to select (leave blank to select ALL states).
NOTE: This section modifies your choices on the previous screen. For instance, if you
specified county governments on Select1, putting an X next to AL, MS, and WY will select
all available counties in just those three states.
UserGuide.Xls (8. Query Application) Page 203 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
Enter the 9-digit Govs ID number of any individual unit you want (e.g., 332031001).
NOTE: Individual units listed will be ADDED to your selection criteria. For example,
specifying county governments in AL, MS, and WY and listing New York City's ID number
will select all available county governments in those three states plus New York City.
Use this screen only if you do not want your query sorted in the default order (i.e., by
descending survey year and ID number).
This screen shows the number of records and variables your query extracted. Be sure to:
- Jot down the name of the SAS dataset it created.
- Note the size of the file, especially its estimated size in ASCII and dBase formats.
All SAS datasets created by this query will be deleted when you exit SAS unless you
export the query dataset to a dBase or ASCII file (or save it under your own, permanent
LibName). This screen allows you to export your query into another format:
- Exported versions of your dataset will be 2 to 15 times larger than the SAS file.
Be sure you have room on your hard drive to store it!
- Exported files will be stored in your hard drive's "C:\Window\Temp\History" folder.
- Since most PC software limit you to 255 fields, the export program will divide queries with
more than 230 fields into separate files (up to three).
- The export program will replace SAS variable names with longer, more meaningful field
names ("labels"). The labels used will depend on which format you selected (dBase labels
are limited to 10 characters).
- ASCII files are in comma-delimited format with field names comprising the first record in
the file (you may need to tell the importing software this fact). Character fields (e.g., ID
and government name) are placed inside double-quote marks (e.g., "011001001").
You will see this screen only if your query was exported. Write down the filename(s) listed.
Choose whether to EXIT the application, do a NEW Query, or VIEW the query you just did.
If you choose to view the current query, it will open SAS' "ViewTable" feature. To exit it,
click on File-End (or press the END function key, F3).
The following keywords can be used in addition to SAS variable names:
ALL 500+ data items
Major totals for revenue, expenditure, debt and cash & securities.
All employee retirement data (revenue, expenditure, and cash and securities)
UserGuide.Xls (8. Query Application) Page 204 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
All revenue data
All major revenue totals
All tax data (T01--T99)
All sales tax data (T09--T19)
All license tax data (T20--T29)
All intergovernmental revenue (B01--D89)
All intergovernmental revenue from Federal Govt (B01--B89)
All intergovernmental revenue from State Govt (C21--C89)
All intergovernmental revenue from Local Govts (D11--D89)
All general charges (A01--A89)
All miscellaneous general revenue (U01--U99)
All utility revenue (A91--A94)
All insurance trust revenue
All expenditure data
All major expenditure totals
Total expenditure for every function
Total intergovernmental expenditure for every function*
Intergovernmental expenditure detail for every function
Direct expenditure for every function
Current operation expenditure for every function ("E" codes")*
Capital outlay expenditure for every function
Construction expenditure for every function ("F" codes")
All other capital outlays for every function ("G" codes")*
All education expenditure (including subfunctions)
All health and hospital expenditure (including hospital subfunctions)
All highway expenditure (including subfunctions)
All public welfare expenditure (including subfunctions)
All utility expenditure
All insurance trust expenditure
All debt data
All major debt totals
All long-term debt issued data
All long-term debt retired data
All long-term debt outstanding data
All cash and securities data
KeyWord will create variables that are not in the data base.
UserGuide.Xls (8. Query Application) Page 205 of 209
8. Using the SAS Query Application to Extract Data
from the Historical Finance Data Base (IndFin)
Query Application Update Log
As of: 6-Sep-2001
Description
Tweaked some of the special KeyWords.
Fixed error where certain requests to export query to dBase format exported the data into
Access format instead.
Updated to add FY99 data.
Revised to run under Windows 2000 (as well as other Windows versions).
Updated to add FY98 data.
Corrected error in program for specialized query "B" (per capita version). Prevously, if the
population was zero, raw data figures (in $000) were used. Corrected to show zero per
capita amount in these cases.
Corrected error in program for all per capita versions where special districts might be
extracted if user selected specific states. Program now excludes special districts from
all per capita queries.
Specialized queries "B" now sorted in ID order.
Results2 screen revised to tell user where exported files are stored.
Added feature to export data into two additional formats: Access97 and Excel97 (Excel97
export limited to queries selecting 25,000 or fewer records). Feature requires SAS version
8.01 or later.
Improved speed of exporting data into ASCII format (Txt)
Added "response" variables to Special Query B indicating for each year whether government
was in survey panel for that year (1 = Yes 0 = No)
Fixed these problems with the special sort option:
- Sort did not work if user chose a sort key that was not in the list of variables selected
earlier in the query
- If user selected a per capita query, the query program would sort the file based on the
dollar amounts, not per capita figures
Original release
UserGuide.Xls (8. Query Application) Page 206 of 209
Go to Contents
Changes to User Guide Covering the Historical Data Base
on Individual Local Government Finances
As of: 16-July-2001
Version Date Changes
Beta (3) 7/16/2001 Revised to reflect addition of 1999 data.
Beta (3) 6/19/2001 Clarified that "all other general function, NEC" debt codes include "T" debt
(public debt for private purposes). Applies to C1253, C1422, and C1591.
Beta (3) 4/11/2001 Revised to reflect addition of 1998 data.
Beta (2) 2/26/2001 1997 data now Version B, reflecting updated source file dated 1-29-2001.
Added Data Flag code "Q" to indicate school districts where Q11 was
extracted from M12 using Q11 data from school finance file.
Description of "ALLIds" reference table revised to show inclusion of incorpor-
ation and disincorporation dates from GID.
Data User Notes added (19) to show how to obtain data for state and
Federal governments in comparable format. Please see important caveats.
Added Query Application Update Log to show changes to this program.
Added new sample program to export data from your own SAS program into
an ASCII comma-delimited file.
Added Data User Note (20h) on IndFin's coverage of individual finance codes
Beta (1) 8/30/2000 Revised to reflect removal of educational service agencies (ESAs) from 1987 -
1991, 1993, and 1994 data base files. These entities are not independent
governments and therefore should have been excluded when the data base
was created. The 4,503 ESA records removed were relocated to a special
dataset, named IndFin.ESAs.
Beta (1) 8/21/2000 Revised to reflect addition of 1997 census of governments data.
Revised to reflect that missing school district enrollment data for 1974-1976
and 1978 were replaced with those from employment files.
Alpha (3) 6/7/2000 Revised query application to store exported files in a folder called:
C:\Windows\Temp\History
Alpha (3) 6/1/2000 Revised references to historical data server to point to new volume label.
Minor editorial changes.
Alpha (2) 9/29/1999 Added sample program to section 6 to create county area totals for census
of government years.
Alpha (2) 9/13/1999 Guide to Variables and User Notes revised to show that weights for FY 1993,
originally described as missing, were substituted with weights from FY 1994
survey since the latter year's were the same.
Alpha 9/9/1999 Original release of alpha version of documentation
