Economic Impacts of Contract Employment at Contra Costa County

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Economic Impacts of Contract Employment at Contra Costa County Powered By Docstoc
					 Assessment of Economic Impacts
      of Out-of-Area Workers at
Major Contra Costa County Refineries.




                 PRODUCED BY:

              Nadya Chinoy Dabby
               Melissa Edwards
                Alex Lantsberg

        University of California, Berkeley
     Department of City and Regional Planning




           SUBMITTED JUNE 2, 2003 TO:

                Dennis Barry
        Community Development Director
            Contra Costa County
TABLE OF CONTENTS
TABLE OF CONTENTS ............................................................................................................. 1
TABLE OF FIGURES.................................................................................................................. 2
EXECUTIVE SUMMARY .......................................................................................................... 3
SECTION 1. OVERVIEW AND METHODOLOGY .............................................................. 4
     PURPOSE OF REPORT                                                                             4
     METHODS                                                                                       4
           Literature Review                                                                       4
           Secondary Data                                                                          5
           Economic Modeling                                                                       7
           Employment and Payroll Scenarios                                                        8
           Defining Out-of-Area Workers                                                            9
           Interviews                                                                              9
     ASSUMPTIONS AND LIMITATIONS                                                                 10
SECTION 2. ECONOMIC IMPACT OF REFINING INDUSTRY EMPLOYMENT IN
           CONTRA COSTA COUNTY ............................................................................ 14
     ASSUMPTIONS                                                                                            14
           Base Level Employment and Payroll Scenarios                                                      14
     IMPACTS                                                                                                14
           Employment:                                                                                      14
           Labor Income                                                                                     14
           Industry Output                                                                                  15
           Indirect Business Taxes:                                                                         15
SECTION 3. OCCUPATIONAL PROFILE OF OUT-OF-AREA CONTRACT
           WORKERS.......................................................................................................... 16
     WORK OPPORTUNITIES FOR OUT-OF-AREA WORKERS                                                                              16
     PROPORTIONS OF OUT-OF-AREA WORKERS                                                                                      16
SECTION 4. ESTIMATING ECONOMIC IMPACT OF OUT-OF-AREA HIRING ....... 17
     ASSUMPTIONS                                                    17
           Area-Worker Scenarios                                    17
           Consumer Expenditure Patterns                            17
           Impact Scenarios                                         17
     IMPACTS                                                        18
SECTION 5. CONCLUSIONS ................................................................................................. 22
     AREAS FOR FURTHER RESEARCH                                                                                          22
APPENDIX ............................................................................................................................... 23
     SUPPLEMENTAL DATA TABLES                                                                                                            23
     LIST OF INTERVIEWEES                                                                                                                27
            Key Interviewees                                                                                                             27
            Union Interviewees                                                                                                           27



Final Report—June 2003                                                                                                             1
Department of City and Regional Planning, UC Berkeley
TABLE OF FIGURES
Table 1. Base Level Payroll and Employment Scenarios .............................................................. 9

Table 2. Local v Non-Local Consumer Expenditure Categories................................................. 11

Table 3. Economic Impacts from Refinery Employee Household Expenditures ........................ 15

Table 4. Average Expenditures by Income.................................................................................. 17

Tables 5 & 6. Total Estimated FTE of Out-of-Area Workers in Refinery Turnarounds............. 18

Figure 1. Estimated Employment Impacts of Hiring Out-of-Area Workers at One Refinery per
          Year .............................................................................................................................. 19

Figure 2. Estimated Impacts of Out-of-Area Workers on Output ............................................... 19

Figure 3. Estimated Impacts of Hiring Out-of-Area Workers on Business Taxes ...................... 20

Tables 7 & 8. Total Estimated Expenditure Impacts of Out-of-Area vs. Local Workers............ 20

Table A-1. Petroleum Refining Self-Reported Employment, Occupations, and Wages in Contra
           Costa County ............................................................................................................. 23

Table A-2. Aggregate Income by Annual Income Category for Baseline Impact Calculation
           Scenarios ................................................................................................................... 24




Final Report—June 2003                                                                                                                  2
Department of City and Regional Planning, UC Berkeley
EXECUTIVE SUMMARY
        This report was prepared by the University of California Department of City and
Regional Planning at the request of the Contra Costa Community Development Department and
the Contra Costa County Board of Supervisors. Its purpose is to examine the economic impact
of out-of-area contract employment at the county’s four largest refineries.

        This report shows that the petroleum refining industry plays a significant role in Contra
Costa County’s economy and that use of out-of-area workers at major refinery construction or
“turnaround” projects can have moderate to significant “leakage” impacts as expenditures that
that normally occur within the study area now occur elsewhere. This diminished local spending
in turn reduces the industry’s positive impacts on the Contra Costa County economy.

        It should be noted that the use of out-of-area workers occurs primarily during temporary
construction projects and for a variety of reasons. These may include, among others, the
inability to fill demand from the local labor pool and the decreased costs from hiring from areas
with lower wage rates. It may not always be possible to have a 100% local labor workforce at
major projects.

        The most significant reductions are to output and business taxes. For example, a
“turnaround” project in one refinery lasting only 4 weeks and using only 250 additional workers
results in a leakage of $640,000 dollars of output and almost $30,000 in indirect business taxes,
while a more intense activity level of all four major refineries performing large turnarounds in
one year results in a leakage of over $12 million in output and over $700,000 in indirect business
taxes.

        Overall, refining is the County’s largest industrial spender, sixth in indirect business tax
payments, and ninth in employee compensation—all the more impressive because of its
relatively small share of the County’s total employment. The household expenditures of refinery
employees reverberate throughout the Contra Costa County economy, contributing significantly
to countywide output, employment, labor income, and indirect business taxes. Skilled trade and
labor positions, which are the subject of the Industrial Safety Ordinance, provide about 26.5% of
these total impacts. Depending on total employment in various scenarios, the impact of all
spending is responsible for an additional:

           $265 to $493 million in total output by county businesses;
           2061 to 3838 jobs within the county;
           $72 to $134 million in labor income that is additionally respent in the area; and
           $12 to 23 million in indirect business taxes.

       This study provides a framework for further research into economic impacts to Contra
Costa County from the hiring of out-of-area workers. Findings from this study could be
supplemented by additional relevant primary data with the cooperation of all relevant
stakeholders, such as unions, contractors, refineries, and public agencies.



Final Report—June 2003                                                                         3
Department of City and Regional Planning, UC Berkeley
SECTION 1. OVERVIEW AND METHODOLOGY
Purpose of Report

        At the request of the Contra Costa County Board of Supervisors, the Contra Costa
County Community Development Department (hereafter referred to as “the Community
Development Department”) undertook a study of the economic impact of out-of-area contract
employment at the county’s four largest refineries. In turn, the Community Development
Department contacted the Department of City and Regional Planning (DCRP) at the University
of California at Berkeley; DCRP agreed to conduct this study pro bono under the direction of the
Community Development Department in April and May of 2003. This report presents the
findings from this study.

        The four refineries analyzed for the purpose of this report are Chevron (Richmond),
Phillips (Rodeo), Shell (Martinez) and Tesoro Golden Eagle (Avon). This report presents data
regarding out-of-area contract workers and then uses this information to describe the socio-
economic impact of out-of-area contract employment. Where certain data were not available,
this report utilizes ranges and depicts possible scenarios; these ranges and scenarios can then be
used for policy-making where appropriate. Before outlining the economic impacts of out-of-area
workers, this report describes the study methodology, assumptions, and data limitations.

Methods

Literature Review
        Several recent studies have been done in various states concerning the impacts of
refineries on local economies. Studies in Alaska (2001), Louisiana (2001) and Delaware (2002)
assess the impact of the refineries on state and local tax revenues, local spending, income and
employment. Due to the size of the refining industries in these locations, they provide a sizeable
portion of the tax revenue and employment, not only in the cities in which they are located, but
also across the state. The study in the available literature whose purpose is most comparable to
this one was completed in Lake Charles, Louisiana. That study looked at the impacts of out-of-
area contract workers on local spending. They found that the contract workers greatly increased
local spending in Lake Charles, and boosted the local economy. A 2001 study commissioned by
the Western States Petroleum Association (WSPA) also found substantial economic benefits
from the petroleum industry, although it analyzed overall direct and indirect job creation from
the refineries rather than the specific impact of out-of-area workers.1

        Both of these aforementioned studies—the Western State Petroleum Association study
and the Lake Charles study—looked at the financial contributions made to charitable institutions
by the refineries. A review of the literature indicates that the existence of refineries in a locale
can result in both benefits and losses for the local and regional economies. The purpose of this


1
    The WSPA report stated that there were 3, 800 employees at the Contra Costa County refineries in 1997; the three
     different employment estimates used in this report (described later in this section) encompass this figure.
     WSPA’s 1997 figure was estimated to generate from 1 to 3 indirect jobs in support of refining, transportation and
     marketing for every direct job in refining (the 3, 800 referenced above).

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Department of City and Regional Planning, UC Berkeley
study, notwithstanding, is decidedly narrower: it explores the economic impact on Contra Costa
County and on the nine-county Bay Area of out-of-area employment at the refineries.

        A less recent study is often referenced in the context of Contra Costa County refineries: it
was produced for the Contra Costa County Board of Supervisors in 1990. This report is entitled
The Impact of Out-of-Area Workers in Non-Residential Construction on Contra Costa County: A
Case Study of the USS-POSCO Modernization and was conducted by Carlos Davidson at the
Center for Labor Research and Education, Institute of Industrial Relations, University of
California at Berkeley. There are significant differences between the methodologies of that prior
report and this study. In particular, these differences relate to the definition out-of-area-workers,
the secondary data sources utilized and the understanding of relevant economic impacts. The
methodologies of this study are discussed in greater detail in the following sections on secondary
data, interviews, and models used. Because the methodologies are not strictly comparable,
caution should be used when attempting to compare the reports’ results.

Secondary Data
        Various secondary data sources were used for this report. Secondary sources are data
that have been produced for a variety of different purposes other than the project at hand. These
data are then used to extrapolate relevant information for the specific project. The bulk of these
secondary data sources were used to develop an understanding of employment at the four
refineries. In particular, it was necessary to determine the number of employees, the positions
occupied by those employees and the estimated earnings of those employees. These sources
were also used to understand expected spending patterns and the resultant economic impacts.

         The specific secondary data sets examined for this report are as follows: 2

         (1) California Employment Development Department (EDD)—The EDD tracks historic
             average monthly employment by industry group at the county and Metropolitan
             Statistical Area (MSA) levels,3 identifies the prevalence of specific occupations
             within industry groups, and tracks average wages by occupation at the county and
             MSA levels. This sector is defined according to the North American Industrial
             Classification System (NAICS); the petroleum and coal manufacturing sector is
             NAICS 324. This data was used to (i) develop an estimate of overall employment at
             the four largest refineries in Contra Costa County and (ii) calculate the baseline wage
             income that corresponded to employment figures.
         (2) County Business Patterns (CBP), US Department of Commerce—The CBP data
             reveal the number of employees by industry, the number of establishments, and the
             total wages. All of these figures are for the payroll period that includes March 12th of
             the reference year; CBP also provides an annual payroll figure. The industry
             analyzed for CBP data was NAICS 32411, petroleum refineries. These data were
             used to determine the total number of employees at the four largest refineries.
             According to the CBP, Contra Costa County had five refineries operating in 2001—


2
  It should be noted that attempts to get more precise secondary data from the Contra Costa County Assessor’s
   Office regarding employment figures were unsuccessful due to legal restrictions preventing release of the data.
3
  The MSA is a US Census Bureau category that represents multiple counties.

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Department of City and Regional Planning, UC Berkeley
             the four refineries which are the subject of this study and one small firm with between
             20 and 49 employees. It should be noted that the CBP employment figures were
             provided as ranges, not as exact figures. The “median convention” technique, where
             the number of employees per firm is estimated to be the category median, was used to
             translate those ranges into actual numbers. The fifth refinery in the CBP data was
             given a value of 34.5 and subtracted from the overall employment figure to arrive at
             the total employment by the four refineries. This proportion was then used to
             calculate the other employment scenarios, as described below.
       (3)   IMPLAN—IMPLAN is a proprietary economic modeling package used to measure the
             economic impacts of specific events through input-output analysis and is further
             described below. IMPLAN’s industry employment estimate is based on three data
             sources. In general, Bureau of Labor Statistics (BLS) Covered Employees and Wages
             (ES202) data provides the county-level industry structure for the IMPLAN database.
             CBP data is used to make non-disclosure adjustments to ES202 data, while Regional
             Economic Information System data is used for control totals. Wages are given and
             include all payroll costs, including employee benefits. Average wages for the
             baseline impact scenarios (see below) are based on IMPLAN data. IMPLAN’s
             estimate of employment is higher than that calculated solely through the EDD
             occupation and wage data. It is also based on all payroll costs, including employee
             benefits. Wage income had to be calculated from this aggregate figure by discounting
             the total by the BLS estimate of employee benefit expenses mentioned above.
       (4)   Public Use Microdata Sample (PUMS), US Census Bureau—This 2000 data set
             presents detailed self-reported information regarding employee residence, commute
             and migration patterns, race, gender, industry and occupation, wage and income,
             household, educational, and other demographic data for a 1% sample of the
             households within a geographic reference area. Following an examination of these
             data, however, it was concluded that it would not be very useful for this particular
             study. Specifically, the PUMS data provided an employment estimate somewhere
             between the CBP and IMPLAN data; therefore it was not used for this report, because
             it fell between the low and middle scenarios (see below). Also of note, the PUMS
             occupational composition was significantly different than proved by the EDD data.
             The data is provided for informational purposes in an appendix to this report.
       (5)   Employer Costs for Employee Compensation 1986-1999, Bureau of Labor Statistics—
             This data set was used to calculate the additional employee benefit expense incurred
             by the refineries. Because IMPLAN (see below) includes employee benefits as part
             of its total employee compensation value, it is important to distinguish between direct
             wages and benefits so that income effects can be accurately modeled throughout the
             economy.
       (6)   Consumer Expenditure Data, Bureau of Labor Statistics (BLS)—The Consumer
             Expenditure Data uses national information to produce a report that details how
             consumers spend their money. These spending patterns are presented by income
             category as well as by occupation type. These data were used to develop a model of
             how out-of-area contract workers at the refineries could be expected to spend their
             wages. This report does not analyze the impact of these out-of-area workers’
             spending in their “home” regions (i.e., outside of the nine-county Bay Area).



Final Report—June 2003                                                                         6
Department of City and Regional Planning, UC Berkeley
Economic Modeling
        IMPLAN economic modeling software extrapolates a specific economic event’s impact
on a region from national input-output data that is supplemented by state and county level data to
correct for regional differences. Economic modeling is particularly useful to policymakers
because it allows them to see how their decisions are likely to reverberate throughout the
economy. Since, economic modeling fundamentally relies on a series of assumptions, this
report’s use of conservative estimates of base levels for the modeling scenarios provides
confidence that projections capture the overall range of possibilities.

        Input-output accounting describes the commodity flows from producers to intermediate
and final consumers. The total industry inputs of commodities, services, employment
compensation, value added, and imports are equal to the total value of the commodities
produced. Purchases for final use (final demand), drive the model as producers purchase goods
and services from other producers who, in turn, must purchase commodities to provide for the
producers who are selling to final demand. Outside impacts, such as purchases from out-of-area
suppliers or out-of-area household expenditures are referred to as leakages. This cycle of
indirect purchases continues until leakages from the region stop the cycle.

        IMPLAN’s detailed county level input-output matrices make it an ideal package for
analyzing changes resulting from discrete economic events. Data files include annual
information for up to 528 different industries—generally to the 3 or 4 digit SIC code level, and
21 different economic variables. IMPLAN also includes a “social account matrix” that allows
the modeling of household and government expenditures and revenues. This ensures that any
impact analysis considers effects throughout the county’s economy.

        This method was used to assess the multiplier effect of the hiring of out-of-area contract
workers at the four refineries. In the input-output model, mathematically derived multipliers
uniquely describe the change of output for each and every industry as a result of producing one
dollar of final demand, which are unique to each industry. In this case, impacts solely within
Contra Costa County were computed. Impacts outside of the region are not included in the
multiplier effect, based on the notion that economic development is regional in nature. In this
study, leakages would primarily include spending in workers’ “home” region (i.e., outside of the
Contra Costa County).

        Multipliers can be calculated for a variety of impacts such as employment, total business
output, personal and total income, and business taxes among others. The total multiplier effect
refers to the impact of an initial round of spending—in this case, the wages paid to out-of-area
contract workers—and the impact of the subsequent re-spending of those initial dollars within
the region. Each “round” of spending generated by the initial round contributes to the total
multiplier effect is made up of three components. The first and largest is the “direct” impact and
simply the spending by the refinery employees. The “indirect” impact is the business-to-
business spending resulting from the direct expenditures and considerably smaller. The
household expenditures of the employees of indirect spenders make up the “induced” portion of




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Department of City and Regional Planning, UC Berkeley
the multiplier and can be larger than the indirect multiplier. In general, the greater the interaction
with the regional economy, the greater is the multiplier.4

Employment and Payroll Scenarios
        As alluded to above, data from the aforementioned secondary data sources yielded a wide
range of estimates for total employment. This variability in estimates can be caused by a number
of factors, such as different reporting requirements and non-disclosure agreements, among
others, and should not be considered out-of-the-ordinary. In order to address this issue, a range
of employment scenarios were developed to ascertain more accurately the range of possible
economic impacts resulting from refinery payrolls. These scenarios were created based on the
varying estimates of employment and payroll expenses provided by the County Business
Patterns, IMPLAN, and EDD data, then used to establish baseline payroll amounts and the
ranges of impacts from the household expenditures of refinery employees.5

             Scenario 1 is based on the County Business Patterns estimate of total employment
             and EDD industry occupational and wage data and is the most conservative for the
             three employment and wage scenarios. Overall employment was calculated by
             applying the employment proportions estimated from the County Business Patterns
             for the petroleum-refining portion of the petroleum and coal manufacturing sector.
             Payroll income amounts were calculated by applying the occupational proportions to
             the overall employment estimates and multiplying those values by the average annual
             income for the occupation. This constitutes the “low” scenario for employment.
             Scenario 2 is calculated based on IMPLAN’s proprietary input-output database
             described in Section 1. EDD wage estimates are not used in this scenario. Income
             categories are instead developed by applying the proportion of wage income accruing
             to each occupation to IMPLAN’s total estimated wages. Average incomes for all
             positions are higher than in scenarios 1 and 3
             Scenario 3 is based on EDD industry specific employment, occupational, and income
             data and uses the same methods as Scenario 1.

        Total wage expense for employees at Contra Costa County’s four largest refineries ranges
between $207.5 and $386.3 million, depending on the employment scenario. Skilled trade and
labor positions earn about 85% of the industry average wage. Together they comprise 31% of
the overall refinery employment but receive only 26% of the total wages. Their total annual
earnings range from $54.2 million to $100.8 million. The large number of lower paid workers
earning less than the industry average causes this discrepancy. Table 1 summarizes the values
used to calculate the baseline impacts of the major refiners’ payroll expenditures. Detailed tables
by occupation and projected aggregate annual income can be found in the appendix at the end of
this report.



4
  A detailed description of the IMPLAN model and how multipliers are calculated is available at the website of the
  Minnesota IMPLAN Group at www.implan.com.
5
  The interviewees gave the impression that many of these skilled trade workers earn wages higher that the
  occupational average, however a conservative approach was chosen to use the average value due to the absence of
  any other corroborating industry specific data.

Final Report—June 2003                                                                                      8
Department of City and Regional Planning, UC Berkeley
                            Table 1. Base Level Payroll and Employment Scenarios
                                                               Scenario 1       Scenario 2       Scenario 3
        Employees at major Contra Costa refineries                     3,421            5,546            6,371
        Total Payroll for refinery employees                    $207,498,485     $384,275,106     $386,431,109
                 Payroll with Benefits                          $275,142,992     $509,548,791     $512,407,651
        Average Annual Income for refinery employees                 $60,654          $69,290          $60,654
        Skilled Trade Workers at refineries                             1,056           1,713            1,967
        Total Payroll for skilled trade workers and laborers      $54,137,233    $100,259,001     $100,821,511
                  Payroll with Benefits                           $71,785,970    $132,943,435     $133,689,324
        Average annual income for skilled trade workers and
          laborers                                                   $51,248          $58,545          $51,248
        Benefits expense                                               32.6%            32.6%            32.6%
              Sources -Scenarios (1) US Census & CA EDD, (2) IMPLAN & CA EDD, and (3) CA EDD;
                                             Bureau of Labor Statistics


Defining Out-of-Area Workers
        For the purposes of this report, out-of-area workers are defined as workers from outside
of the nine-county Bay Area.6 There are two principal reasons for utilizing this definition of out-
of-area workers: (i) this definition acknowledges the interconnected nature of the Bay Area
economy and (ii) it represents a standardized definition/criteria, which is thus compatible with
other potential data sources and relevant analyses.

Interviews
         The intended design of this study entailed telephone interviews with four different key
groups. These four groups are as follows: (i) refinery representatives from each of the four
refineries; (ii) union contractors that represent the union out-of-area workers at the refineries;
(iii) independent/nonunion contractors who hire out-of-area workers at the refineries; and (iv)
other persons who have relevant expertise and/or knowledge regarding these refineries.

        Attempts to interview these four groups, however, were not entirely successful. In fact,
DCRP was only able to complete interviews with two of these four groups: the union contractors
and the other persons who have relevant expertise and/or knowledge. Interviews with refinery
representatives and independent/nonunion contractors were attempted but ultimately
unsuccessful, despite multiple efforts from DCRP. It is likely that a confluence of factors
prohibited the completion of these interviews, including the following: difficulty in collecting the
data that was requested, worries about revealing what was perceived as confidential information,
concerns about the intent of the study in the current political environment of Contra Costa
County, and/or time constraints. In the absence of some essential data that would have been
gathered from these interviews—particularly, the proportion and number of
independent/nonunion contract workers who are from out-of-area, and the total hours worked by
contract workers (both union and independent/nonunion) over the course of a year—some



6
    In other words, out-of-area-workers are those from outside of Alameda, Contra Costa, Marin, Napa, San Francisco,
     San Mateo, Santa Clara, Solano and Sonoma counties.

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Department of City and Regional Planning, UC Berkeley
assumptions were made about possible ranges into which these figure fall. Using those ranges,
computations were made for low, medium, and high scenarios.

        Ten telephone interviews were conducted with unions who represent refinery workers.
While data from the Contra Costa County Building Trades Council Data indicated that there are
14 unions who represent workers from the refineries, four of these unions could not be contacted;
they are thus not included in this report. These unions were asked to respond to questions
regarding positions occupied by out-of-area contract workers, the number and proportion of
those workers relative to local workers, the wage level/range associated with those positions, the
duration of the position (year-round or a shorter duration) and the benefits afforded to these out-
of-area contract workers. The data gathered from these interviews regarding contract union
workers’ occupational positions and wages is not utilized in this report, however. Originally, it
was anticipated that comparable data from both the unions and the refineries would be available.
Because data from the refineries was not made available, it was determined that reliance on
union data would result in an incomplete data and would not be relied upon for this report.
Instead, figures from the EDD for wage levels were used and various scenarios regarding the
proportion of out-of-area workers were developed.

         DCRP also contacted various people who have regular contact with the refineries to gain
a fuller picture of the situation. These people included: a refinery public relations contractor, a
refinery lobbyist, a Contra Costa County Building Trades Council staff member, a Building
Trades Council attorney, the Contra Costa County Assessor, Contra Costa County Community
Development Department staff, and a Philadelphia-based refinery worker. These conversations
took place over the phone and did not follow an established protocol. Instead, information was
elicited that was particular to each contact. This information included: basic descriptions of how,
when and why the refineries use contract workers; particular issues that were of concern to the
refineries, their contractors and/or the county as a whole; suggestions regarding available data;
and/or recommendations of other potential contacts. Because the information elicited was not
designed to be representative, a content analysis of these conversations was not performed.
Instead, this information served to inform the evolution of the research design. The list of
interviewees is provided in the appendix.

Assumptions and Limitations
       Certain assumptions were made in order to produce meaningful analysis of the existing
data. Making these assumptions explicit helps ensure that the study remains replicable, and
elucidates potential limitations. The assumptions of this study include:

           Consumer expenditure patterns—Because out-of-area workers are, by definition,
           transitory and rooted in another community, certain assumptions were made about
           what out-of-area workers would purchase locally, and what they would purchase in
           their region of origin. Purchases in their region of origin represent “leakage” and are
           not included in the multiplier effect. The following table (1) presents the categories




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Department of City and Regional Planning, UC Berkeley
               that are included as local expenditures and those that were understood to represent
               non-local expenditures.7

                             Table 2. Local v Non-Local Consumer Expenditure Categories
               Local Expenditures (included in multiplier)       Non-Local Expenditures (not included in multiplier)
                o   Alcoholic beverages                           o   Apparel and services
                o   Entertainment                                 o   Cash contributions
                o   Food                                          o   Education
                o   Housekeeping supplies                         o   Health care
                o   Housing (rented, other)                       o   Household operations
                o   Personal care, products and services          o   Housing (owned, household furnishings and
                o   Tobacco products and smoking supplies             equipment)
                o   Transportation (gas and motor oil)            o   Personal insurance and pensions (life and other
                o   Utilities, fuels and public services              personal insurance, pensions and Social
                                                                      Security)
                                                                  o   Reading
                                                                  o   Transportation (vehicle purchases, other vehicle
                                                                      expenses, public transportation)
                                                                  o   Miscellaneous



               Cost burdens and savings due to out-of-area workers—Various potential cost
               burdens/savings incurred by the County were explored due to the presence of out-of-
               area workers. These included educational costs borne by the county for children of
               out-of-area workers; health care costs borne by the county for out-of-area workers
               who may not have health care; and unemployment costs for supporting unemployed
               local residents who could potentially be employed by the refineries, but which instead
               hire out-of-area workers.

               It was determined that these cost burdens would be minimal based on the following
               information:

                    o Education—Reports from union contractors indicate that out-of-area workers
                      do not tend to bring their children with them. It was thus assumed that the
                      costs of educating out-of-area workers’ children would thus be insignificant.
                      Moreover, this research indicated that even if this were to be an issue, the data
                      regarding school children’s residency status (i.e., how long the child has lived
                      in the local area) is only available on an individual school basis. Collecting
                      that data from each school in the county would therefore also have been
                      beyond the scope of this project.
                    o Health costs—Due to the temporary nature of the turnarounds, these workers
                      were unlikely to generate a significant impact on the health care system in
                      Contra Costa County.
                    o Unemployment benefits—Under direction of the Community Development
                      Department, it was assumed that the local unemployed persons would not


7
    These categories are based on the BLS Consumer Expenditure Survey, as expounded upon earlier.

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Department of City and Regional Planning, UC Berkeley
                        have the qualifications for employment at the refineries. Potential costs to the
                        County for unemployment insurance payments were not calculated.

               IMPLAN modeling—IMPLAN’s model is based on national trends, supplemented
               with state and MSA level data in order to adjust for local patterns. Except where
               noted, IMPLAN’s assumptions were used as applicable to Contra Costa County.
               Industry Structure—Based on knowledge of the structure of the refining industry in
               Contra Costa County, it was assumed that the four largest firms in the CBP data were,
               in fact, the four largest refineries on which this study is focused. The proportions
               developed using CBP data were applied to calculate employment from the EDD data.
               Employee benefits were assumed to be identical for each scenario.
               Occupational composition of contract workforce—For the purposes of this report, it
               was assumed that contract workers occupy only the blue-collar occupational positions
               within the refineries (i.e., no contract workers in higher-level management or
               technical positions). These occupational positions are as follows:

                    o   Boilermakers
                    o   Control and Valve Installers and Repairers
                    o   Electricians
                    o   First-Line Supervisors/Managers of Mechanics, Installers, and Repairers
                    o   First-Line Supervisors/Managers of Production and Operating Workers
                    o   General Maintenance and Repair Workers
                    o   Heavy and Tractor-Trailer Truck Drivers
                    o   Inspectors, Testers, Sorters, Samplers and Weighers
                    o   Installation, Maintenance, and Repair Workers
                    o   Machinists
                    o   Petroleum Pump System Operators, Refinery Operators and Gaugers
                    o   Plumbers, Pipefitters, and Steamfitters

               The employment figures for blue-collar workers were then used as the basis for
               computing various proportions of out-of-area workers. Implicitly, then, it was also
               assumed that the relative proportions of each occupation are the same among contract
               workers (local and out-of area) as among the overall workforce (contract and non-
               contract).
               2080-hour work-year—Annual figures for out-of-area contract workers’ earnings and
               their impacts on the region (i.e., multiplier effects) are computed based on a 2080-
               hour work year.8
               Types of contract-worker projects—There are various types of refinery projects that
               require contract workers, including turnarounds, construction, maintenance, and/or
               follow-up work after a refinery accident. As mentioned previously, however, t data
               from the refineries regarding the nature of these projects was unavailable —
               particularly, the average duration and frequency of these projects per year. For the
               purposes of this report, then, certain assumptions about these projects were made. All


8
    This computation was necessary because original wage figures are calculated on an annual basis while construction
     projects generally last for only a fraction of a year.

Final Report—June 2003                                                                                       12
Department of City and Regional Planning, UC Berkeley
                of the calculations in this report analyze only the impact of turnarounds (and not of
                the other projects), the most conservative approach.9 One turnaround per year per
                refinery was assumed ( a total of four turnarounds per year) with durations of four,
                six, or twelve weeks.

       This study is thus limited by the aforementioned assumptions. There are, furthermore,
some additional limitations that should be clarified. Regarding secondary data sources, it should
be noted that 2002 data are not available at the time of writing this report. The majority of the
data used in this report are for 2001, the most recent year available; the exceptions are the
Consumer Expenditure Survey data, which is an average for 2000-01, and the IMPLAN data is
for 1999.

        The following sections provide a picture of the refinery industry’s overall contribution to
the County’s economy and how the economy is impacted by the use of use of non-local labor at
major refinery projects. Specifically, Section 2 will outline the overall economic contribution of
refinery employees’ household expenditures to the output, employment, labor income, and
business taxes. Section 3 discusses how the total number of workers was calculated. Section 4
discusses the economic impact of out-of-area workers at refinery projects in relation to the
impacts of an all-local workforce.




9
    Because less is known about the nature of contract-worker projects that are not turnarounds, it was not possible to
    make reasonable assumptions upon which to base calculations.

Final Report—June 2003                                                                                           13
Department of City and Regional Planning, UC Berkeley
SECTION 2. ECONOMIC IMPACT OF REFINING INDUSTRY
           EMPLOYMENT IN CONTRA COSTA COUNTY
        The purpose of this section is to establish an overall picture of the economic impacts to
Contra Costa County’s economy resulting from the wages paid to refinery employees. Economic
modeling is conducted using IMPLAN software, as described in Section 1 above. The
calculation includes employment, labor income, and indirect business tax impacts resulting from
the industry’s normal operations, as well as the impacts attributable solely to the skilled trade and
laborer positions affected by the ISO.

Assumptions

Base Level Employment and Payroll Scenarios
       The baseline payroll amounts established in the three scenarios described in Section 1
were used to calculate the range of impacts from the household expenditures of refinery
employees. These figures are used to compare and contrast the relative significance of the
impact of out-of-area workers.

Impacts

       The household expenditures of refinery employees reverberate throughout the local and
regional economy, adding new jobs, local income, countywide industry output, and tax revenue.
These are summarized in Table 3 below.

Employment:
        The total indirect and induced employment resulting from the household expenditures of
the employees of Contra Costa’s major refineries ranges between 2,061 and 3, 838 jobs, with
between 537 and 1005 of those jobs attributable to skilled trades and laborer positions. The
industry’s employment impacts in this analysis are significantly lower than the findings of the
Western States Petroleum Association report, which estimated nearly 50,000 direct and indirect
jobs resulting from the refineries in Contra Costa and Solano Counties. This is likely the result
of more conservative assumptions.10

Labor Income
        As a result these expenditures total labor income from all refinery workers ranges
between $71.7 million and $133.5 million dollars, depending on the scenario. Labor income
from the skilled trades and laborer employees is between $18.8 million and $35.2 million. This
constitutes about 26.5% of the total labor income effect resulting from the employees of the four
major refineries.




10
     For example, the WSPA report considered retail gasoline station workers and marketing positions to be related to
     the presence of the refining industry while IMPLAN limited employment effects strictly to the employment
     increases resulting from the expenditures of refinery wage income throughout the economy.

Final Report—June 2003                                                                                         14
Department of City and Regional Planning, UC Berkeley
Industry Output
        This figure shows the increases in total output as a result of employee household
spending. This effect is most pronounced on county industries that sell a large proportion of
their goods or services to local residents. Refinery payrolls spur between $12.1 and $22.6
million of additional output. Skilled trades and laborers contribute between $3.2 and $5.9
million of this impact.

Indirect Business Taxes:
       Total taxes generated as a result of employee household spending are between $12.1 and
$22.6 million, with skilled trades people and laborers contributing between $3.2 and $5.9 million
The calculation of indirect business taxes is based upon the Bureau of Economic Analysis's
Gross State Product series, which gives state-level estimates of taxes by industry classification.

          Table 3. Economic Impacts from Refinery Employee Household Expenditures
                                                                 Scenario 1     Scenario 2     Scenario 3
   Total Employment                                                     2,061          3,817          3,838
       Total Employment from STL* Household Spending                      537          1,005          1,000

   Total Labor Income                                            $ 71,713,196 $ 132,808,666 $ 133,553,799
       Total Labor Income from STL Household Spending              18,883,593    35,320,946    35,169,579

   Total Output                                                   264,951,135    490,674,080    493,427,039
       Total Output from STL Household Spending                    69,200,619    129,429,197    128,874,532

   Total Indirect Business Tax                                     12,149,125     20,499,472     22,625,706
       Total Indirect Business Tax from STL Household Spending      3,182,894      5,953,118      5,927,605
  Sources - (1) US Census & CA Employment Development Department; (2) IMPLAN & CA EDD; (3) CA EDD
                                    *-STL: Skilled Trades and Laborers




Final Report—June 2003                                                                                  15
Department of City and Regional Planning, UC Berkeley
SECTION 3. OCCUPATIONAL PROFILE OF OUT-OF-AREA CONTRACT
           WORKERS
Work Opportunities for Out-of-Area Workers

        Out-of-area workers are employed in Contra Costa refineries for a variety of reasons.
Without interviews with the refineries themselves, it is not possible to be exhaustive about all of
the different mechanisms and reasons out-of-area contract workers come to work in the
refineries. Nonetheless, some of the basics regarding this process were determined through
interviews from other sources.

       The refineries may need contract workers for a variety of projects, including turnarounds
(where refinery operations—or a certain part of those operations—are temporarily halted so that
cleaning and maintenance can be performed), construction projects, and general maintenance. It
is assumed that additional skilled trades workers and laborers are brought on in the same
proportions as they deployed throughout the refinery.

        There are two primary paths of entry into contract employment for out-of-area workers:
independent/nonunion contractors and union contractors. It is not clear as to how the
independent/nonunion contractors locate their workers. It is known that the unions interviewed
share a common policy on the hiring of out-of-area workers (meaning union members from
outside of the nine-county Bay Area). Under this policy, the unions first attempt to fill all
positions locally. If there are not enough members locally to meet the refineries’ stated need for
workers, then the unions pull in out-of-area workers. Primarily, the reason that there may not be
sufficient numbers of local union members to meet the refineries’ need is because the refineries
sometimes need a large number of workers quite immediately. There is no reason to believe that
the independent/nonunion contractors have different reasons for hiring out-of-area workers, but
no definitive data on their policies was available at the time of writing.

Proportions of Out-of-Area Workers

        Based upon information from key interviews, it was estimated that approximately 50% of
all workers brought in for a turnaround were considered out-of-area. This assumption was used
for both union and non-union workers. As mentioned above, it was assumed that contract
workers occupy only the blue-collar positions listed in Section 1. Based on occupational wage
data from the Bureau of Labor Statistics, those occupations fell into three income categories:
10% are in the $30,000 to $39,999 category, 12% in the $40,000 to $49,999 category, and 78%
in the $50,000 to $69,999 category. It was assumed that these proportions were also valid for
workers hired for the turnarounds. These income categories were used with the 2000-2001
Consumer Expenditure Survey to calculate the impact of local spending of out-of-area workers.

       The following section presents analysis regarding the economic impact of the hiring of
these out-of-area workers. This analysis takes into account the occupational positions, and
wages of these workers.



Final Report—June 2003                                                                        16
Department of City and Regional Planning, UC Berkeley
SECTION 4. ESTIMATING ECONOMIC IMPACT OF OUT-OF-AREA
           HIRING
Assumptions

Area-Worker Scenarios
        To determine the economic impact of out-of area hiring due to consumer expenditures,
several scenarios were used. Overall, two area-worker scenarios were used. The first scenario
(the “out-of-area worker” scenario) assessed the value of consumer expenditures assuming that
50% of the workers were out-of-area. The second scenario (the “all local worker” scenario)
assessed the value of consumer expenditures assuming that 100% of the workforce was hired
locally. The difference between these area-worker scenarios represents the “leakage” of
expenditures and other revenues due to out-of-area hiring. Additional impact scenarios devised
within these two larger scenarios are discussed later in this section.

Consumer Expenditure Patterns
         As previously shown in Table 2, assumptions were made about which goods and services
out-of-area workers were likely to purchase locally and which goods and services they were
likely to purchase in their region of origin. Table 4 shows the average expenditures made by
local and out-of-area workers based on these assumptions. The table shows, as would be
expected, that out-of-area workers spend a much smaller proportion of their income locally than
local workers. In fact, the workers that hold positions used by the refineries during turnaround
spend less than 40% of their total income in Contra Costa County. Further analysis will show
that this disparity in expenditures results in significant revenue leakages for Contra Costa
County.

                              Table 4. Average Expenditures by Income
                        Income            Total Avg. Income All Local Workers OOA Workers
                   $30,000 to $39,999           $34,113          $29,762        $11,587
                   $40,000 to $49,999           $43,732          $35,383        $12,947
                   $50,000 to $69,000           $57,331          $41,676        $13,565
                     Source: Consumer Expenditure Survey, Bureau of Labor Statistics.

Impact Scenarios
         As previously mentioned, since precise data was not available from the refineries about
their turnaround processes, several impact scenarios were developed to estimate impacts of out-
of-area hiring on Contra Costa County. Based on information from key informants, it was
estimated that a turnaround at a refinery typically lasts anywhere from 1 to 3 months, with an
average of 6 weeks, and can employ from 500 to 1000 workers.

         As mentioned above, it was assumed there was only one turnaround per refinery, per
year. Assuming for the out-of-area scenario that 50% of all turnaround workers were out-of-
area, from 250 to 500 workers would be employed in a typical refinery turnaround. Also
included is a mid-range estimate of 350 workers, for a total of three scenarios. These figures
were multiplied by four to get the impacts of a turnaround at the four refineries in one year.


Final Report—June 2003                                                                      17
Department of City and Regional Planning, UC Berkeley
These figures were adjusted to estimate the number of full-time-equivalency workers (FTE) for
these short-term employees. Impacts were also estimated for the all-local-worker scenario where
all of these workers were hired locally. The following tables illustrate the total FTE estimated
for each of the above scenarios.

      Tables 5 & 6. Total Estimated FTE of Out-of-Area Workers in Refinery Turnarounds
                                                   One Refinery
                                                                       Number of Workers
             Length of Turnaround in Work Hours*                     250     350       500
             4 weeks (160 wk hrs)                                    19       27       38
             6 weeks (240 wk hrs)                                    29       40       58
             12 weeks (480 wk hrs)                                   58       81       115

                                              Four Refineries
                                                                        Number of workers
             Length of Turnaround in Work Hours*                     1000    1400      2000
             4 weeks (160 wk hrs)                                     77      108       154
             6 weeks (240 wk hrs)                                     115     162       231
             12 weeks (480 wk hrs)                                    231     323       462
                                         *2080 work hours per year

Impacts

        The impacts of hiring out-of-area workers as opposed to local workers can result in
significant leakages for the Contra Costa County economy. Figures 1 through 3 show the
leakage of jobs, output and business taxes from hiring 50% out-of-area workers as opposed to
hiring all of the workers locally in various scenarios. These charts represent the impacts of one
refinery. They show that the leakage impacts of out-of-area workers in employment, business
taxes, and output increase as the size and duration of the turnaround increases. A similar linear
increase was found when measuring the impact at all four refineries.

        On the low end, one turnaround in one refinery lasting only 4 weeks and using only 250
workers would result in a leakage of 5 jobs, $640,000 dollars of output and almost $30,000 in
indirect business taxes. The high-end scenario, which involves all four refineries performing
large turnarounds in one year, would result in a leakage of 121 jobs, over $12 million in output
and over $700,000 in indirect business taxes.




Final Report—June 2003                                                                        18
Department of City and Regional Planning, UC Berkeley
Figure 1. Estimated Employment Impacts of Hiring Out-of-Area Workers at One Refinery per Year
                                  50

                                  45
                                              Out of Area Impacts
                                  40
                                              Contra Costa Impacts
                                  35

                                  30
     Jobs




                                  25

                                  20

                                  15

                                  10

                                      5

                          -
                                                4 (250)                  6 (250)           6 (500)        12 (500)
                                                                     Weeks in Turnaround (#of Workers)


                                              Figure 2. Estimated Impacts of Out-of-Area Workers on Output

                                          7


                                          6
                                                Out of Area Impact
      Output in Millions of Dollars




                                                Contra Costa Impacts
                                          5


                                          4


                                          3


                                          2


                                          1


                                          0
                                                 4 (250)                  6 (250)          12 (500)        12 (500)
                                                                     Weeks in Turnaround (# of Workers)




Final Report—June 2003                                                                                                19
Department of City and Regional Planning, UC Berkeley
                                               Figure 3. Estimated Impacts of Hiring Out-of-Area Workers on Business Taxes

      Business Taxes in Thousands of Dollars   300



                                               250
                                                          Out of Area Impacts

                                                          Contra Costa Impacts
                                               200



                                               150



                                               100



                                                50



                                               -
                                                           4 (250)                 6 (250)                 6 (500)              12 (500)
                                                                                Weeks in Turnaround (# Workers)



       Tables 7 and 8 provide the total impacts for all scenarios. On the low end, one
turnaround in one refinery lasting only 4 weeks and using only 250 workers would result in a
leakage of 5 jobs, $640,000 dollars of output and almost $30,000 in indirect business taxes. The
high-end scenario, which involves all four refineries performing large turnarounds in one year,
would result in a leakage of 121 jobs, over $12 million in output and over $700,000 in indirect
business taxes.

                          Tables 7 & 8. Total Estimated Expenditure Impacts of Out-of-Area vs. Local Workers
                                                                                            One Refinery
  Weeks in                                                                                                                                 Indirect Business
Turnaround (#                                             Labor Income                         Jobs                    Output
                                                                                                                                                 Taxes
 of Workers)
                                                     50% OOA         100% Local      50% OOA      100% Local    50% OOA     100% Local     50% OOA    100% Local

  4 (250)                                            $88,208          $263,439          3              8        $322,885     $964,947      $14,843     $44,373
  4 (350)                                            $125,348         $296,361          4             11        $458,838    $1,371,240     $21,093     $63,058
  6 (250)                                            $134,093         $402,092          4             12        $492,827    $1,472,814     $22,655     $67,728
  4 (500)                                            $176,416         $526,878          5             15        $645,773    $1,869,894     $29,686     $88,748
  6 (350)                                            $185,700         $554,608          5             16        $679,760    $2,031,468     $31,248     $93,417
  6 (500)                                            $269,266         $804,183          8             23        $985,653    $2,945,629     $45,311    $135,455
  12 (250)                                           $269,266         $804,183          8             23        $985,653    $2,945,629     $45,311    $135,455
  12 (350)                                           $376,044        $1,123,082        11             32       $1,376,516   $4,113,722     $63,279    $190,171
  12 (500)                                           $533,890        $1,594,469        15             45       $1,954,314   $5,840,469     $89,840    $268,576




Final Report—June 2003                                                                                                                           20
Department of City and Regional Planning, UC Berkeley
                                               Four Refineries
  Weeks in                                                                                        Indirect Business
Turnaround (#         Labor Income                    Jobs                    Output
                                                                                                        Taxes
 of Workers)
                 50% OOA       100% Local   50% OOA      100% Local    50% OOA      100% Local   50% OOA        100% Local

  4 (1000)       $357,473     $1,067,621      10              30      $1,308,538    $3,910,575    $60,154 $179,829
  4 (1400)       $501,392     $1,497,623      14              43      $1,835,354    $5,484,964    $84,372 $252,228
  6 (1000)       $533,890     $1,594,500      15              45      $1,954,314    $5,840,469    $89,840 $268,576
  4 (2000)       $714,947     $2,135,244      20              61      $2,617,079    $7,821,151   $120,307 $359,658
  6 (1400)       $752,086     $1,976,165      21              64      $2,753,030    $7,227,444   $126,558 $378,342
  6 (2000)      $1,072,419    $3,202,864      31             91       $3,925,617   $11,731,727   $180,461 $539,488
  12 (1000)     $1,072,419    $3,202,864      31             91       $3,925,617   $11,731,727   $180,461 $539,488
  12 (1400)     $1,499,531    $4,478,374      43             127      $5,489,066   $16,403,769   $252,333 $754,333
  12 (2000)     $2,144,839    $6,405,730      61             182      $7,851,232   $20,463,452   $360,923 $1,078,975



        While the multiplier effects on employment may at most only contribute to 121 extra
jobs, the impacts on output and business taxes are more pronounced. Most significant are the
losses to Contra Costa County through output. By hiring workers locally, local businesses could
stand to gain millions in output. The high-end figure of $12 million would only result from
large, 3-month turnarounds at all 4 refineries, but substantial leakage figures of $3-5 million
would occur on moderately sized 4 to 6 week projects.

        An increase in output from local businesses would also result in a substantial increase in
taxes to the county. Increased local spending primarily generates sales taxes for a host of public
services and moderate estimates put the amount of leakage between roughly $50,000 and
$250,000, again depending on the length and intensity of the construction project.




Final Report—June 2003                                                                                     21
Department of City and Regional Planning, UC Berkeley
SECTION 5. CONCLUSIONS
      By examining the major impacts of out-of-area workers, this study provides a solid
framework for gauging the impacts of out-of-area workers in Contra Costa County.

        Overall, it is clear that the petroleum refining industry plays a significant role in Contra
Costa County’s economy11. The data suggests that the hiring of more local workers during
temporary construction projects would increase the gains in employment, business taxes, and
output to Contra Costa County and the cities within Contra Costa County through leakage
reductions. The most significant impacts would come from increases in business taxes and
output. It should be noted that the reasons for hiring out-of-area workers by the refineries may
include, among others, the inability to fill demand from the local labor pool and the decreased
costs from hiring from areas with lower wage rates. However, as mentioned in Section 3, this is
also an assumption that cannot be confirmed without more information from the refineries.

Areas for further research

       Due to the limitations of this and any study, there are several areas that could benefit
from further research. Impacts from this study could be supplemented by a study to collect
additional relevant primary data. This study could be one designed with the cooperation of all
relevant stakeholders, such as unions, contractors, refineries, and public agencies.

       Overall, further research should take into account additional information from the
stakeholders to make more precise estimates of the following:

           1)   Length and scale of turnarounds
           2)   Percent of out-of-area workers in a typical turnaround
           3)   Occupational and wage composition of turnaround workers
           4)   Spending patterns and service demands of out-of-area turnaround workers

        This could even allow the research to be tailored to estimate impacts over a particular
year. In addition, a larger study might also include estimates of any potential impacts on the
schools and health care system of Contra Costa County. While this study estimated that these
impacts are likely to be small, further investigation should be done to assess the actual scale of
these factors.




11
     Refining is the County’s largest industrial spender, sixth in indirect business tax payments, and ninth in employee
     compensation—a figure all the more impressive because of its relatively small share of the County’s total
     employment.

Final Report—June 2003                                                                                           22
Department of City and Regional Planning, UC Berkeley
APPENDIX
Supplemental Data Tables

  Table A-1. Petroleum Refining Self-Reported Employment, Occupations, and Wages in Contra
                                        Costa County
                                                                           Number in     Average Wage      Aggregate
                                Occupation                                  Industry        Income        Wage Income
 Marketing and sales managers                                                       65           86,000       5,590,000
 Purchasing managers                                                               118           60,000       7,080,000
 Managers, all other                                                               290           78,669      22,814,000
 Management analysts                                                               238           65,597      15,612,000
 Accountants and auditors                                                           92          138,000      12,696,000
 Computer scientists and systems analysts                                          263           77,779      20,456,000
 Computer programmers                                                              291           64,914      18,890,000
 Computer software engineers                                                       172           82,238      14,145,000
 Network and computer systems administrators                                        92           57,000       5,244,000
 Chemical engineers                                                                224           72,746      16,295,000
 Computer hardware engineers                                                       131           60,000       7,860,000
 Industrial engineers, including health and safety                                 119           60,000       7,140,000
 Chemists and materials scientists                                                 159           64,000      10,176,000
 Paralegals and legal assistants                                                    79           61,000       4,819,000
 Miscellaneous media and communication workers                                      79           18,000       1,422,000
 Other healthcare practitioners and technical occupations                           79           58,000       4,582,000
 Sales representatives, wholesale and manufacturing                                 79           34,300       2,709,700
 First-line supervisors/managers of office and administrative                      158           12,000       1,896,000
 Court, municipal, and license clerks                                               27           50,000       1,350,000
 Customer service representatives                                                  106           43,000       4,558,000
 Receptionists and information clerks                                              132           32,700       4,316,400
 Production, planning, and expediting clerks                                       106           68,000       7,208,000
 Office clerks, general                                                             79           36,500       2,883,500
 Office and administrative support workers, all other                               92          125,000      11,500,000
 First-line supervisors/managers of construction trades and extraction
    industries                                                                     158          69,000       10,902,000
 Electricians                                                                       39          61,000        2,379,000
 First-line supervisors/managers of mechanics, installers, and repairers            53          71,000        3,763,000
 Industrial and refractory machinery mechanics                                      79          72,000        5,688,000
 First-line supervisors/managers of production and operating                       593          49,730       29,490,000
 Computer control programmers and operators                                        106          70,000        7,420,000
 Machinists                                                                         79         112,000        8,848,000
 Welding, soldering, and brazing workers                                           145          75,000       10,875,000
 Miscellaneous plant and system operators                                          475          74,459       35,368,000
 Chemical processing machine setters, operators, and tenders                       198          65,000       12,870,000
 Production workers, all other                                                     185          77,081       14,260,000
 Driver/sales workers and truck drivers                                             79          43,000        3,397,000
 Laborers and freight, stock, and material movers, hand                             80          35,000        2,800,000
 Machine feeders and offbearers                                                    225          72,000       16,200,000
    TOTAL                                                                        5,764          65,146      375,502,600
    TOTAL STW                                                                    2,494          65,862      164,260,000
                              Source: US Census Bureau, 1% Public Use Microdata Sample




Final Report—June 2003                                                                                            23
Department of City and Regional Planning, UC Berkeley
    Table A-2. Aggregate Income by Annual Income Category for Baseline Impact Calculation
                                         Scenarios
                                                      20,000 –   30,000 –    40,000 –     50,000 –
      Occupation Description             Scenario                                                   Over 70,000
                                                       29,999     39,999      49,999       69,999
  Accountants and Auditors               Scenario 1                                      9,195,525
                                         Scenario 2                                      17,029,576
                                         Scenario 3                                      17,125,122
  Boilermakers                           Scenario 1               915,331
                                         Scenario 2              1,695,139
                                         Scenario 3              1,704,650
  Bookkeeping, Accounting, and           Scenario 1              1,889,286
     Auditing Clerks                     Scenario 2              3,498,848
                                         Scenario 3              3,518,479
  Business Operations Specialists, All   Scenario 1                                      14,812,339
     Other                               Scenario 2                                      27,431,589
                                         Scenario 3                                      27,585,495
  Chemists                               Scenario 1                                       1,499,406
                                         Scenario 2                                       2,776,812
                                         Scenario 3                                       2,792,391
  Compliance Officers, Except            Scenario 1                                       1,356,448
    Agriculture, Construction, Health    Scenario 2                                       2,512,063
    and Safety, and Transportation       Scenario 3                                       2,526,157
  Computer Programmers                   Scenario 1                                                   3,918,343
                                         Scenario 2                                                   7,256,543
                                         Scenario 3                                                   7,297,256
  Computer Specialists, All Other        Scenario 1                                      1,601,264
                                         Scenario 2                                      2,965,448
                                         Scenario 3                                      2,982,086
  Computer Systems Analysts              Scenario 1                                                   11,186,593
                                         Scenario 2                                                   20,716,918
                                         Scenario 3                                                   20,833,152
  Control and Valve Installers and       Scenario 1                          1,228,938
     Repairers, Except Mechanical        Scenario 2                          2,275,922
     Door                                Scenario 3                          2,288,691
  Customer Service Representatives       Scenario 1              1,752,292
                                         Scenario 2              3,245,143
                                         Scenario 3              3,263,350
  Drafters, Engineering, and Mapping     Scenario 1                          3,499,830
     Technicians, All Other              Scenario 2                          6,481,480
                                         Scenario 3                          6,517,845
  Electricians                           Scenario 1                                      1,695,284
                                         Scenario 2                                      3,139,567
                                         Scenario 3                                      3,157,182
  Engineering Managers                   Scenario 1                                                    5,601,033
                                         Scenario 2                                                   10,372,787
                                         Scenario 3                                                   10,430,984




Final Report—June 2003                                                                                    24
Department of City and Regional Planning, UC Berkeley
                                                       20,000 –   30,000 –    40,000 –    50,000 –
      Occupation Description              Scenario                                                    Over 70,000
                                                        29,999     39,999      49,999      69,999
  Engineers, All Other                    Scenario 1                                                  14,131,609
                                          Scenario 2                                                  26,170,916
                                          Scenario 3                                                  26,317,750
  Executive Secretaries and               Scenario 1                          2,161,064
     Administrative Assistants            Scenario 2                          4,002,165
                                          Scenario 3                          4,024,620
  Financial Analysts                      Scenario 1                                      3,392,624
                                          Scenario 2                                      6,282,943
                                          Scenario 3                                      6,318,194
  Financial Managers                      Scenario 1                                                   2,349,515
                                          Scenario 2                                                   4,351,165
                                          Scenario 3                                                   4,375,577
  Financial Specialists, All Other        Scenario 1                                      4,747,890
                                          Scenario 2                                      8,792,817
                                          Scenario 3                                      8,842,149
  Financial, Information, & Record        Scenario 1               971,220
     Clerks, All Other                    Scenario 2              1,798,642
                                          Scenario 3              1,808,734
  First-Line Supervisors/Managers of      Scenario 1                                      3,269,818
      Mechanics, Installers, and          Scenario 2                                      6,055,512
      Repairers                           Scenario 3                                      6,089,487
  First-Line Supervisors/Managers of      Scenario 1                                                   1,961,999
      Non-Retail Sales Workers            Scenario 2                                                   3,633,507
                                          Scenario 3                                                   3,653,893
  First-Line Supervisors/Managers of      Scenario 1                          1,280,420
      Office and Administrative Support   Scenario 2                          2,371,264
      Workers                             Scenario 3                          2,384,568
  First-Line Supervisors/Managers of      Scenario 1                                      4,291,646
      Production and Operating            Scenario 2                                      7,947,878
      Workers                             Scenario 3                                      7,992,470
  General and Operations Managers         Scenario 1                                                   2,383,905
                                          Scenario 2                                                   4,414,853
                                          Scenario 3                                                   4,439,623
  Geological and Petroleum                Scenario 1                          1,147,667
     Technicians                          Scenario 2                          2,125,413
                                          Scenario 3                          2,137,337
  Geoscientists, Except Hydrologists      Scenario 1                                                   1,803,594
     and Geographers                      Scenario 2                                                   3,340,152
                                          Scenario 3                                                   3,358,892
  Human Resources Assistants,             Scenario 1               991,370
    Except Payroll and Timekeeping        Scenario 2              1,835,960
                                          Scenario 3              1,846,261
  Human Resources Managers                Scenario 1                                                   2,007,184
                                          Scenario 2                                                   3,717,187
                                          Scenario 3                                                   3,738,043
  Industrial Engineers                    Scenario 1                                                   3,708,045
                                          Scenario 2                                                   6,867,084
                                          Scenario 3                                                   6,905,612



Final Report—June 2003                                                                                    25
Department of City and Regional Planning, UC Berkeley
                                                       20,000 –     30,000 –   40,000 –     50,000 –
      Occupation Description              Scenario                                                      Over 70,000
                                                        29,999       39,999     49,999       69,999
  Inspectors, Testers, Sorters,           Scenario 1               1,712,094
      Samplers, and Weighers              Scenario 2               3,170,698
                                          Scenario 3               3,188,487
  Installation, Maintenance, and Repair   Scenario 1                           1,165,633
      Workers, All Other                  Scenario 2                           2,158,685
                                          Scenario 3                           2,170,796
  Lawyers                                 Scenario 1                                                     5,156,843
                                          Scenario 2                                                     9,550,172
                                          Scenario 3                                                     9,603,754
  Life, Physical, and Social Science      Scenario 1                           3,773,661
      Technicians, All Other              Scenario 2                           6,988,600
                                          Scenario 3                           7,027,810
  Machinists                              Scenario 1                           2,210,208
                                          Scenario 2                           4,093,176
                                          Scenario 3                           4,116,141
  Maintenance and Repair Workers,         Scenario 1               1,009,953
     General                              Scenario 2               1,870,375
                                          Scenario 3               1,880,868
  Management Analysts                     Scenario 1                                                    11,223,373
                                          Scenario 2                                                    20,785,033
                                          Scenario 3                                                    20,901,649
  Managers, All Other                     Scenario 1                                                     6,263,129
                                          Scenario 2                                                    11,598,950
                                          Scenario 3                                                    11,664,026
  Marketing Managers                      Scenario 1                                                     2,492,112
                                          Scenario 2                                                     4,615,247
                                          Scenario 3                                                     4,641,141
  Office Clerks, General                  Scenario 1   2,153,688
                                          Scenario 2   3,988,504
                                          Scenario 3   4,010,882
  Paralegals and Legal Assistants         Scenario 1                                       1,306,740
                                          Scenario 2                                       2,420,006
                                          Scenario 3                                       2,433,584
  Payroll and Timekeeping Clerks          Scenario 1                958,754
                                          Scenario 2               1,775,556
                                          Scenario 3               1,785,518
  Petroleum Engineers                     Scenario 1                                                     6,693,851
                                          Scenario 2                                                    12,396,622
                                          Scenario 3                                                    12,466,174
  Petroleum Pump System Operators,        Scenario 1                                       34,122,315
     Refinery Operators, and Gaugers      Scenario 2                                       63,192,539
                                          Scenario 3                                       63,547,085
  Physical Scientists, All Other          Scenario 1                                                     4,024,494
                                          Scenario 2                                                     7,453,129
                                          Scenario 3                                                     7,494,945
  Plumbers, Pipefitters, and              Scenario 1                                       1,374,260
     Steamfitters                         Scenario 2                                       2,545,050
                                          Scenario 3                                       2,559,329



Final Report—June 2003                                                                                      26
Department of City and Regional Planning, UC Berkeley
                                                      20,000 –     30,000 –     40,000 –    50,000 –
      Occupation Description             Scenario                                                        Over 70,000
                                                       29,999       39,999       49,999       69,999
  Public Relations Specialists           Scenario 1                                         1,377,730
                                         Scenario 2                                         2,551,476
                                         Scenario 3                                         2,565,791
  Pump Operators, Except Wellhead        Scenario 1                             110,801
     Pumpers                             Scenario 2                             205,197
                                         Scenario 3                             206,348
  Purchasing Agents, Except              Scenario 1                                         1,392,715
     Wholesale, Retail, and Farm         Scenario 2                                         2,579,226
     Products                            Scenario 3                                         2,593,697
  Receptionists and Information Clerks   Scenario 1    667,776
                                         Scenario 2   1,236,682
                                         Scenario 3   1,243,621
  Sales and Related Workers, All         Scenario 1                                         2,709,360
     Other                               Scenario 2                                         5,017,577
                                         Scenario 3                                         5,045,729
  Sales Managers                         Scenario 1                                                       2,429,039
                                         Scenario 2                                                       4,498,438
                                         Scenario 3                                                       4,523,677
  Training and Development               Scenario 1                                         1,387,523
      Specialists                        Scenario 2                                         2,569,611
                                         Scenario 3                                         2,584,028
  Truck Drivers, Heavy and Tractor-      Scenario 1                            1,030,952
     Trailer                             Scenario 2                            1,909,263
                                         Scenario 3                            1,919,975
                      Total Scenario 1                2,821,464   10,200,300   17,609,174   89,532,887   87,334,660
                      Total Scenario 2                5,225,187   18,890,362   32,611,165 165,809,690 161,738,703
                      Total Scenario 3                5,254,503   18,996,347   32,794,132 166,739,978 162,646,149

List of Interviewees

Key Interviewees
   1. Tom Adams, Attorney for the Contra Costa County Building Trades Council
   2. Dennis Barry, Contra Costa County Community Development Department
   3. Greg Feere, Contra Costa County Building Trades Council
   4. Gus Kramer, Contra Costa County Assessor
   5. Patrick Roche, Contra Costa County Community Development Department
   6. Jeff Small, Sunoco Philadelphia Refinery engineer
   7. Tom Stewart, Inform Public Relations
   8. Eric Zell, Zell and Associates


Union Interviewees
   1. Boilermakers Local 549, Fred Fields and Tom Baca
   2. Brick and Tile Layers Local 3, Greg Miranda
   3. Carpenters Local 152, Dennis McWhorter, negligible OOA workers
   4. Cement Masons Local 300, Leslie Trapps

Final Report—June 2003                                                                                       27
Department of City and Regional Planning, UC Berkeley
   5. Electricians Local 302, Michael Yarbrough, negligible OOA workers
   6. Iron Workers Local 378, Don Zampa, negligible OOA workers
   7. Laborers Local 324, Randy Le Moine
   8. Laborers Local 67, Jerry Rodarte
   9. Sheet Metal Workers Local 104, Kevin Van Buskirk, negligible OOA workers
   10. Steamfitters Local 342, Larry Blevins

   Unable to reach:
   1. Asbestos Workers Local 16, Steve Steele
   2. Operating Engineers Local 3, Walt Powers
   3. Painters Local 741, Elmer Kennessey
   4. Teamsters Local 315, Dale Robbins




Final Report—June 2003                                                           28
Department of City and Regional Planning, UC Berkeley