Regional Analysis Methods by m4N9Vg

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```									Regional Analysis Methods

Benchmarking, Location Quotients,
Shift-share
Agenda

• Review
• Shift-Share
– What is it?
– How do you do it?
– What does it mean?
• Tools for interpreting
– Cautions and limits
• Multipliers
• Policy Map?
First Assignment – Q1

• What was the population of Allegheny
County in 2000 and 2004 (Census or
BEA)?
– 2000: 1,279,817 (BEA - REIS or Census July
1est.)
– or 2000: 1,281,666 (Census 2000 (SF1) -
April 1 estimate)
– 2004: 1,247,512 (BEA-REIS)
First Assignment Q2-4

• How many total jobs were available in
Allegheny County in 2004?
– 861,868 (BEA total employment)
• How many Allegheny County residents
were employed in 2004?
– 604,203      (BLS, CPS/LAUS)
• What was the total "covered" employment
in 2004?
– 685,878     (BLS, QCEW)
Second Assignment - I
• When you are benchmarking one region
against another, there are many factors to
consider in the selection of an appropriate
benchmark. Name two (2):
• If you are studying a region with dynamic
annual changes, what is the best method to
calculate the growth rates?
• You should never use a location quotient for
what purpose?
Second Assignment Part 2
• There a several considerations for
interpreting a location quotient. Name two
(2):
• What is the difference between a firm and
an establishment?
How do we interpret Pgh’s Growth?
Pittsburgh, 1969-2000

1,600,000

1,400,000

State and local
1,200,000
Military
Federal, civilian
1,000,000
Services
Finance, insurance, and real estate

600,000                                                                                                                                                                                                                                    Transportation and public utilities
Manufacturing
Construction
400,000
Mining
Agricultural services
200,000

-
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
-
19

100,000
200,000
300,000
400,000
500,000
600,000
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Services

19
86
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Manufacturing

19
88
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Pittsburgh, 1969-2000

89
19
90
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91
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92
19
93
19
94
19
95
19
We can look at a basic view

96
19
97
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98
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99
20
00
Or a little more complexity
Pittsburgh, 1969-2000

1,000,000

900,000

800,000
Resource based
700,000
Federal
Government
600,000                                    Local Serving

400,000

300,000

200,000

100,000

-
69
70
71
72
73
74
75
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00
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6
9

0.0%
2.0%
4.0%
6.0%

-6.0%
-4.0%
-2.0%
19 -19
70 70
19 -19
71 71
19 -19
72 72
19 -19
73 73
19 -19
74 74
19 -19
75 75
19 -19
76 76
19 -19
77 77
19 -19
78 78
19 -19
79 79
19 -19
80 80
19 -19
81 81
19 -19
82 82
19 -19
83 83
19 -19
84 84
Pittsburgh

19 -19
85 85
19 -19
86 86
19 -19
87 87
19 -19
88 88
19 -19
89 89
19 -19
90 90
19 -19
United States

91 91
19 -19
Annual Employment Growth, 1969-2000

92 92
19 -19
93 93
19 -19
94 94
19 -19
95 95
19 -19
96 96
19 -19
97 97
19 -19
98 98

19 -19
99 99
-2
00
0
Employment Change, 1970-1993

800,000

700,000

600,000

500,000

400,000

300,000

200,000

100,000

0
San Diego   Boise   Tucson      Fresno     Memphis    New Orleans   Toledo   Pittsburgh
But these descriptions still
haven’t explained much
Location Quotients

Formula                                                        Interpretation
High
Important industries   Important growth
that may require       industries
Region

attention

Location Quotient
Industry
Total

Industries of little   Potential emerging
Nation

Industry                                       promise to local       industries
economy
Total

Low

Low               Employment Growth         High
Shift-Share

• What are the 3 components of a shift-share
analysis?
• A competitive industry is defined as
WHAT?
• Explain
– National share
– Industry Mix
– Regional Shift
• What are the limits of shift-share?
Albuquerque, 1970-1990
Albuquerque          1970             1990 Absolute

Region Total       150,901       342,529        191,628
• 127 % total
employment      Target Region   Year 1       Year 2        Ri
growth
AGSVC                 552         2,268           1,716
• +190,000        CON                 9,028        18,634           9,606
Jobs            FARM                1,165         1,729             564
FED                11,193        14,599           3,406
FIRE               12,471        26,569          14,098
• What            MFG                10,453        26,240          15,787
explains this   MIL                 7,600         8,134             534
MIN                 1,388         1,313             -75
growth?
RETAIL             25,424        59,987          34,563
STLGOV             19,322        44,475          25,153
SVC                36,971       107,068          70,097
TRAN                8,253        14,904           6,651
WHSALE              7,081        16,609           9,528
Three factors…

• Growth of the national economy
• Presence of growth industries (or
declining ones)
• Local competitive factors
Employment             Change
Albuquerque          1970      1990 Absolute   Percent
Region Total      150,901   342,529    191,628     127%

Projected     Diff btw
at National   US &       Projected   Regional
Ave.          actual ch. Mix         Shares
83,770      107,858      14,595   93,263
Brief Glossary

•   R = actual regional change
•   N = change due to national growth
•   M = Industry mix effect
•   S = regional shift effect
Growth of the U.S. Economy

• If Alb had grown at the U.S. rate, it would
• The growth of the U.S. economy accounted
for 83,770, or 44% of the actual change.
• Alb in fact added more than 191,000 jobs –
so something else must explain the region’s
growth
The mix of industries in the region

• The presence of growth industries were not
a major factor in the region’s performance.
Growth industries on the whole accounted
for 8% of the actual change, which equaled
14,595 jobs.
• Must add jobs faster than the nation as a
whole to have a positive Mix effect
Local competitive factors

• The shift-share analysis estimates that 49%
of the growth in employment is the result of
local competitive conditions.
• 93, 263 of the jobs created in Albuquerque
were due to these local advantages
industry but one – Mining.
Albuquerque Industry Data

Target Region   Year 2       Ri            Ri pct     Mi            Si

AGSVC                2,268         1,716       311%           668           742
CON                 18,634         9,606       106%           504         4,090
FARM                 1,729           564        48%          -748           665
FED                 14,599         3,406        30%        -5,037         2,229
FIRE                26,569        14,098       113%         2,548         4,627
MFG                 26,240        15,787       151%        -6,287        16,271
MIL                  8,134           534         7%        -5,503         1,818
MIN                  1,313           -75        -5%           135          -981
RETAIL              59,987        34,563       136%         2,266        18,183
STLGOV              44,475        25,153       130%        -1,527        15,953
SVC                107,068        70,097       190%        29,770        19,803
TRAN                14,904         6,651        81%        -1,884         3,954
WHSALE              16,609         9,528       135%          -312         5,909
What are the key industries?

We can combine statistics on
economic growth, the shift-share, and
specialization (LQs) to highlight
Finding Key Industries
Sustain
Identify the
non-competitive                         Innovate

factors
Develop the value chain -
Fix them if possible                  Buyers & Supplier

Not Competitive                        Competitive

Prepare for transition
Lagging
Watch the market
Manage decline
Minimize investment
Do nothing
State and Local Gov

• It is a large industry in the region with
considerable growth.
• It is not a growth industry nationally – but
this industry does not move on strictly
national dynamics.
• It is a desirable goal to growth this
industry?
Manufacturing

• Still somewhat small – only 7% of regional
employment, less then 27,000 employees.
• Potential emerging sector in the region, but
the sector is declining nationally
– Can Alb capture more of this industry and for
how long?
– Are there subsectors in which the region has a
concentration and an advantage that are
growing?
Services

• Employment in Services accounts for 25% of the
region’s employment (comparable to the US
share).
• The industry grew by 70,000 jobs in the region
(190%), well above national and industry growth
• Local factors were positive, but contributed less to
the growth than national and industry factors.
Shift-share + benchmarking
Shift-Share Comparison, 1970-1993

600,000

Regional Shift

400,000
Industry Mix

200,000

0

San Diego   Boise   Tucson     Fresno      Memphis          New           Toledo   Pittsburgh
Orleans
-200,000

-400,000

-600,000
You may need to normalize the data
Regional Shift as a Proportion of Total Change

1.00

0.50

-
San Diego   Boise        Tucson      Fresno     Memphis    New Orleans   Toledo   Pittsburgh

(0.50)

(1.00)

(1.50)

(2.00)

(2.50)

(3.00)

(3.50)
The level of industry detail impacts
the shift-share analysis
2digit 4 digit
Absolute Change          -10132 -10132
National Effect           -9450 -9450
Industry Mix             690.71 -2759
Local Shift               -1373 2075.2

• More detail increases the accuracy of the
industry mix effect and the local shift.
The time frame impacts the shift-
share
1969      2000          R         N       M           S
1969-2000    1,128,141 1,384,664   256,523   991,947   -4,278   -731,146

1969      1988          R         N       M           S
1969-1988    1,128,141 1,205,775    77,634   571,936   -6,419   -487,883

1988      2000          R         N       M           S
1989-2000    1,205,775 1,384,664   178,889   297,892   29,909   -148,912

Aggregated                         256,523   869,827   23,491   -636,795

• If the industry structure changes dramatically then a longer
time frame distorts the industry mix effect.
Strategies for missing data

• Ignore it
• Find an alternative source
• Estimate missing midpoint data with an average or
linear projection
• Use the proportion of the industry from a higher
level of geography
• Project the missing data based on regional growth
• Project the missing data based on national industry
growth
Comparing the 3 "Solutions" to missing data
Comparing the 3 "Solutions" to missing data

R          N          M        S
Complete Data          106,225     67,610      5,990   32,625
Incomplete Data         71,221     67,610      5,990   -2,379
Partial Data            99,926     61,972     11,259   26,695

For Construction         R          N         M        S
Complete Data           10,973      3,694     1,963    5,316
Incomplete Data         10,973      3,694     1,963    5,316
Partial Data            10,973      3,694     1,963    5,316

1 – estimate nondisclosed data
2 – ignore nondisclosed data or assume = 0
3 – exclude missing sectors entirely
Multipliers

• What is a multiplier?
– Based on industry input-output
• How do you use them correctly
– Change in final demand
– Substitution
– Total vs. direct vs. indirect jobs
• Sources
– RIMS II
– IMPLAN
– REMI

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