A Job is Not
a Job
An Input-Output Model Analysis
of the
Stanislaus County Economy
Kelvin Jasek-Rysdahl
January 1998
Preface
This is a companion report to Critical Links: Employment Growth, Unemployment, and
Welfare-to-Work in Stanislaus County. The analysis contained in this report is based on
information gleaned from a computer generated input-output simulation of the Stanislaus County
economy. This type of model can shed light on the general characteristics of the economy,
exports and imports of the economy, employment multipliers, industry linkages, and impact
estimates.
This report provides an estimate of the Gross County Product, which is similar to the Gross
Domestic Product for the nation, and identifies key exporting sectors in the County. In addition,
the report describes how jobs in particular industry sectors differ in a number of ways including
employee compensation, earnings, and productivity. The main feature of the report is an
examination of employment multipliers and industry sector impacts.
The author of this report wishes to thank Ken Entin and Steve Hughes for their helpful
suggestions and comments. Jan Hansen of the Department of Economics at the University of
Wisconsin-Eau Claire and the staff at the Minnesota IMPLAN Group were very helpful also.
Julie Smulson’s help with the finishing details of the report is also greatly appreciated.
Contents
Input-Output Models
2
Study Area Characteristics
6
Characteristics of Jobs
15
Job Impacts
20
Industry Impacts
29
Concluding Remarks
33
Glossary
36
Appendix A: Technical Description of
Input-Output Models
37
Appendix B: Specific Industry Sectors Operating
In Stanislaus County
43
Appendix C: Industry Sectors in 65 Industry Models
52
Figures
Fig. 1: Example of Goods, Services, and Resource Flows
3
Fig. 2: Industry Output as a Percent of Total Industry Output
8
Fig. 3: Net Exports for Stanislaus County
12
Fig. 4: Net Exports for Merced County
13
Fig. 5: Net Exports for San Joaquin County
13
Fig. 6: Net Exports for the Region
14
Fig. 7: Employee Compensation as a Percent of Total County Compensation
15
Fig. 8: Industry Employment as a Percent of County Employment
17
Fig. 9: Earnings Per Worker
18
Fig. 10: Productivity
19
Tables
Table 1: Industry Sectors
6
Table 2: Number of Industries
6
Table 3: Gross County Product/Gross Region Product
7
Table 4: Stanislaus Industry Exports as a Percent of Total Exports
10
Table 5: Merced Industry Exports as a Percent of Total Exports
11
Table 6: San Joaquin Industry Exports as a Percent of Total Exports
11
Table 7: Region Industry Exports as a Percent of Total Exports
11
Table 8: Stanislaus County Output Multipliers
23
Table 9: Output Multipliers for Other Local Economies (Total Effects)
23
Table 10: Stanislaus County Employment Multipliers
26
Table 11: Employment Multipliers for Other Local Economies
27
Table 12: Top 20 Employment Multipliers
28
Table 13: Bottom 20 Employment Multipliers
28
Table 14: Top Six Industries in Terms of Output
29
Table 15: Total Impacts
30
Table 16: Industries Affected
31
Table 17: Industries Affected by Food Processing $20 million +
31
Table 18: Industries Affected by Farms $20 million +
32
Table 19: Industries Affected by Retail $20 million +
32
Table 20: Industries Affected by Real Estate $20 million +
32
Table 21: Industries Affected by Construction $20 million +
33
Table 22: Industries Affected by Health Services $20 million +
33
Table 1b: IMPLAN Industry Sectors in Stanislaus County
43
Table 1c: Industry Sectors
52
This is a companion report to Critical Links: Employment Growth, Unemployment, and
Welfare-to-Work in Stanislaus County. One of the important findings identified in Critical
Links was that employment growth in Stanislaus County over the past two decades has been
dominated by growth in the retail and service sectors. The report pointed out that jobs created in
the retail and service sectors are generally lower paying, often part-time and temporary, and
require little skill or experience. As a result of these trends income growth in Stanislaus County
has lagged behind other regions of the state and more people are in jobs where they can be easily
replaced.
This report continues to examine how jobs differ in the impact they have on the economy by
employing an input-output model. There are many ways that the jobs created by an industry can
affect the economy. Some industries will have highly productive workers who create products for
export from the County. These employment positions will attract and circulate income in the
local economy. Some industries will purchase many of their needed resources from local
businesses thus creating employment opportunities in the supplying firms. There will be
industries that pay well compared to others. The income spent by people working in these sectors
will be spent, in part, at local businesses, which in turn will generate additional jobs. Industries
will vary in terms of the number of people employed, as well as employee productivity and
compensation levels. They also will differ in terms of the value of total output produced and
exported. In addition, industries will vary in the level of supplies purchased locally or imported
from outside the economy. All of these will impact the magnitude of a number of different
multipliers.
An explanation of input-output (I-O) models and a description of the particular I-O modeling
software used for this study is followed by a description of the models created for this study. This
report then presents the results of the I-O analysis of the Stanislaus County economy and
compares them to the reference areas. The concluding remarks summarize key findings and
outlines areas for future investigation. The appendices provide more detailed descriptions of
various aspects of the study as well as a glossary of terms used in the report.
1
§ Input-Output Models
This section describes what input-output models are and how they work. A more technical
description of I-O modeling is provided in appendix A. This appendix also lists and describes the
limiting assumptions of this modeling procedure. Key terms are defined in this section and in a
glossary at the end of the report.
Input-output models trace the flow of goods, services, and resources within a region1. Businesses
in any economy hire labor and combine it with other resources and raw materials in order to
create and sell goods and services. Some of the production of these firms will be used by other
firms to produce goods and services. Final users of the goods and services, such as households
and governments, also may purchase items directly from local businesses. Some of the goods and
services also may be sold to consumers outside of the region. These exports are important
because they provide an injection of income into a local economy.
Not all of the goods, services and raw materials used in a region come from that region. Firms
within the region will buy products from other firms in the same region, but they will also
purchase raw materials and resources from businesses located outside the region. Final
consumers such as households also will buy goods and services from businesses located outside
the region. This importing behavior is important because it serves as a leakage of income from
the local economy.
1
For the purposes of I-O modeling the term region can refer to an area that includes a nation or group of nations. It
can also refer to a city or county economy. For this study the term region usually refers to a county economy.
Anything done in the region takes place in the county while anything outside the region is outside the county. There
is one model of a three county economy which is referred to as 'Region'.
2
Figure 1 represents a simplified example of the flow of goods, services and resources that are
identified in the input-output modeling process. The manufacturing/food & kindred sector, for
instance, uses labor from households and buys raw materials and other resources from firms
outside and inside the region. In addition to buying from other sectors, this sector will sell some
of its output to other industrial sectors in the region where it will be used to produce some other
good or service. A portion of the output of the manufacturing/food & kindred sector will go to
final consumers within the region. In addition, the manufacturing/food & kindred sector will sell
and export its output to producers and consumers in other regions.
Figure 1: Example of goods, services, and resource flows.
Exports
Households
OtherI ndustry
Sec tors in
Loca lE conom y
Ma nufac turing/
Food &K indred
Imports
Flow of Go ods and Serv ices
Flow of La bor
Final
Consumption
In this example manufacturing/food & kindred will purchase raw materials such as fruit and
vegetables from farmers, transportation services from trucking companies, and containers from
can and jar makers. These are just three of the industry sectors from which firms in the
manufacturing/food & kindred sector will buy inputs. Firms in this sector may also secure
supplies from firms outside the region which are shown as imports.
3
Firms in the manufacturing/food & kindred sector will sell the goods they produce to other firms
within the region. Restaurants and hospitals are two sectors that will use the products from the
manufacturing/food & kindred sector as inputs. In addition to selling to other firms within the
region, this sector will also sell to other firms outside the region as exports.
In addition to sales to other businesses, there is a certain level of production for final
consumption. Final consumption is the purchase of goods and services by households,
businesses, and governments. These items are purchased and not used in the production of
anything else. Households will buy goods and services from local firms, but will also buy goods
and services that were produced outside the region. Items purchased from outside the region by
households are also imports.
The IMPLANProTM software
The computer modeling undertaken for this study utilizes the I-O modeling software
IMPLANProTM. The IMPLAN software was originally created by the U.S. Forest Service. The
version used for this study is IMPLANProTM and is created and maintained by the Minnesota
IMPLAN Group.
The data used with the IMPLANProTM software breaks the economy into 528 industry sectors.
These sectors can be aggregated in any number of ways and for this study three different
aggregation schemes were used.
The data set used for this study is created for the IMPLANProTM software and comes from a
number of different data sources: the Bureau of Labor Statistics' ES-202, County Business
Patterns, and the Regional Economic Information System Data (REIS). The sectoring scheme is
an adaptation of a number of government methods including the Standard Industrial
Classification scheme (SIC), the REIS scheme, and the Bureau of Labor Statistics' sectoring
system.
4
The data sets are available for any county in the United States. The Center for Public Policy
Studies at California State University, Stanislaus currently has 1994 data for all counties in
California. One can create models of individual counties for study, but it is also possible to
combine counties in a regional model.
Models Created for this Study
Although the primary regional model created for this report is of the Stanislaus County economy,
models of San Joaquin, Merced, Santa Clara, and Alameda counties were developed as well.
These four counties have a significant commuting relationship with Stanislaus County.
Additionally, a regional model of the Northern San Joaquin Valley (Merced, San Joaquin, and
Stanislaus counties) was prepared.
For each study area, there were two classification schemes used. The first aggregated industries
into 15 broad sectors that correspond closely to those reported by the California Employment
Development Department (EDD). The 15 sectors are listed in Table 1. Government covers all
federal, state, and local agencies, including education. The second did not aggregate industries.
This option was selected so that specific factors within the broadly defined categories could be
explored. For Stanislaus County, industries also were divided into 62 sectors.
5
Table 1
Industry sectors
INDUSTRY GROUP
1
24
27
28
58
104
133
433
447
448
456
469
490
510
516
NAME
Farm
Ser.Farm
Ser.Other
Const/Min
Mfg.F&K
Mfg.OtherND
Mfg.Dur
Tr/Ut
Whls.Trade
R.Trade
F/I/RE
Ser.Bus
Ser.H
Gov't
Other
DESCRIPTION
Farm Production
Farm Services
Services not included elsewhere
Construction and Mining
Manufacturing/Food and Kindred
Manufacturing/Other Nondurable
Manufacturing/Durable
Transportation and Public Utilities
Wholesale Trade
Retail Trade
Finance, Insurance & Real Estate
Business Services
Health Services
Government
Production and services not otherwise listed
§ Study Area Characteristics
For 1994, Stanislaus County had 279 out of 528 industry sectors contained in the IMPLAN data
sectoring system. One model of the County was created that contained all 279 sectors. The list of
the industry sectors which were operating in Stanislaus County is included in Appendix B of this
report. The following table shows the number of industries in Stanislaus County and the
reference areas.
Table 2
Number of Industries
STUDY AREA INDUSTRIES IN STUDY AREA
Merced
186
San Joaquin
296
Stanislaus
279
Region
363
As the numbers in the table suggest, larger counties and regions will have more industries. The
region, which includes all three counties, has 363 industry sectors. When taken as a region, the
local economy is similar to Santa Clara and Alameda counties in terms of number of industry
sectors: Santa Clara has 393 and Alameda has 398. It is very rare that any region or county will
6
have all 528 industry sectors. California, which is one of the largest economies in the world, has
514 of the 528 industry sectors.
Gross Regional Product
It is possible to calculate Gross Regional Product (GRP) and Gross County Product (GCP),
which are analogous to Gross Domestic Product (GDP), from the information contained in an I-O
model. GRP/GCP is a measure of the dollar value of final goods and services produced during a
year. Table 3 reports the Gross County and Gross Regional Product for the study areas.
Table 3
GCP/GRP
STUDY AREA
Merced
San Joaquin
Stanislaus
Region
GCP and GRP (millions
of dollars)
3,293.83
10,758.65
8,369.05
22,421.53
Percent of Total
14.7
48.0
37.3
100.0
The Gross State Product for this same period was over $850 billion. Even though the Region has
a similar number of industry sectors, the economies in it are much smaller than the two Bay Area
counties. The GCP for Santa Clara was a little over $65 billion and Alameda's GCP was just over
$41 billion. Reasons for this include differences in population size between the areas and the
nature of production in the two regions. The value added in the Bay Area economies is greater
than in Merced, San Joaquin, and Stanislaus counties.
Composition of Industry Output
One way to measure the importance of an industry to a region is to look at how much output it
produces. This section will describe the makeup of total industry output, which provides a partial
description of the importance of particular industries. Total industry output (TIO) is the total
production of goods and services in the economy. The difference between TIO and GCP/GRP is
that TIO includes both the production of goods and services for final sales and goods and
services produced to be included as ingredients to final goods and services. GRP/GCP only
counts the dollar value of final goods and services.
7
Figure 2 below shows the shares of each industry's total output as a percent of the total
production in each study area. Several observations should be noted. Farm production accounts
for 23.6% of TIO in Merced and 10.1% of TIO in Stanislaus. Manufacturing/food & kindred
accounts for 17.4% of TIO in Merced and 19.9% of TIO in Stanislaus. Together these two
sectors account for 41% and 30%, respectfully, of TIO in Merced and Stanislaus. These numbers
are significant in themselves because they show that both of these sectors account for a
substantial proportion of each region's output. One can expect that they will show up as
important in other areas of the analysis. These two sectors account for 27.1% of TIO in the three
county region.
Figure 2: Industry Output as a Percent of Total Industry Output
G o v e rn m e n t
H e a lt h S e r v ic e s
B u s in e s s S e r v ic e s
F in . , I n s . , & R e a l E s t a t e
R e ta il T r a d e
W h o le s a le T r a d e
T r a n s & P u b lic U t ilit ie s
M f g / D u r a b le
M f g / O t h e r N o n d u r a b le
M f g /F o o d a n d K in d r e d
M in in g a n d C o n s t r u c t io n
O t h e r S e r v ic e s
F a rm
F a rm
S e r v ic e s
P r o d u c t io n
0 .0 %
M e rc e d
5 .0 %
S a n J o a q u in
1 0 .0 %
1 5 .0 %
S ta n is la u s
2 0 .0 %
2 5 .0 %
R e g io n
The individual service sectors account for small shares of TIO but they do warrant attention.
When all services are added together they account for 10.6% of TIO in Merced, 15.2% of TIO in
San Joaquin, 15.5% of TIO in Stanislaus, and 14.8% of TIO in the three county region. One
service sector that is important for Stanislaus County is health services. This sector accounts for
6.9% of TIO in the County, compared to 5.3% in San Joaquin and 3.8% in Merced.
8
Figure 2 reveals that the counties are not identical in terms of production levels. In spite of these
differences, there is also quite a bit of similarity between the three counties. They all have
production concentrated in farm production and manufacturing/food & kindred. The importance
of this is that if these industries start to reduce the number of employees as a result of changes in
technology or seasonal employment patterns, the employees that lose jobs do not have many
other equivalent job alternatives. This is true for the local county economy and for the three
county region. People would have to travel substantial distances in order to find work in some
alternate industry sector.
The Bay Area economies are significantly different from Stanislaus County and its neighbors.
Farm production and manufacturing/food and kindred each account for less than 4% of TIO in
these two counties. Manufacturing/durable was the leader in these two counties, accounting for
39.5% of TIO in Santa Clara and 14.4% of TIO in Alameda. In Santa Clara,
manufacturing/durable was followed by F.I.R.E. (11.8%), other services (9.8%), business
services (7.8%), and retail trade (5.5%). In Alameda, manufacturing/durable was followed by
F.I.R.E. (13.2%), other services (10.6%), government (9.9%), and transportation & public
utilities (8.9%). As for the state as a whole, F.I.R.E. contributed the largest share of TIO at
17.6%. This sector was followed by other services, manufacturing/durable (both at 13%), retail
trade (7.7%), and government (7.5%).
9
Imports and exports
The I-O model also estimates the values of exports and imports for the various industry sectors. It
is important to understand which industry sectors export goods and services out of the local
economy and which industry sectors import goods and services into the economy. Exports are a
source of new dollars which will circulate throughout the local economy and generate additional
income. Imports are a leakage of dollars out of the economy. When companies or individuals buy
goods and services from outside the area, they are adding to income elsewhere
The tables below list, for each county, the order of exporting sectors as a percent of total exports
from largest to smallest. In Stanislaus County, manufacturing/food and kindred, has the largest
share of the county's exports, followed by manufacturing/durable, farm production, and health
services. The manufacturing/food and kindred sector also has the largest share of exports in the
three other economies. Even though the largest exporter is the same in the various regions, the
sectors that follow are different. In Merced County manufacturing/food and kindred is followed
by farm production, and manufacturing/durable. In San Joaquin County manufacturing/food and
kindred is followed by manufacturing durable, finance, insurance & real estate, and farm
production.
Table 4
Stanislaus Industry Exports as a
Percent of Total Exports
Exports as a % of Total
Industry Sector
County Exports
Mfg/Food & Kindred
48.84
Mfg/Durable
14.62
Farm Production
12.69
Health Services
5.71
F.I.R.E
5.38
Retail Trade
4.46
Government
2.86
Farm Services
2.09
The remaining sectors each account for less than 2% of total county exports in Stanislaus.
10
Table 5
Merced Industry Exports as a
Percent of Total Exports
Exports as a % of
Industry Sector
Total County
Exports
Mfg/Food &Kindred
41.93
Farm Production
37.29
Mfg/Durable
6.95
Mfg/Other Nondurable
3.36
Farm Services
3.15
Retail Trade
2.43
The remaining sectors each account for less than 2% of total county exports in Merced.
Table 6: San Joaquin Industry Exports as a
Percent of Total Exports
Exports as a % of
Industry Sector
Total County Exports
Mfg/Food &Kindred
33.71
Mfg/Durable
15.77
F.I.R.E
13.45
Farm Production
11.54
Trans & Public Utilities
6.98
Retail Trade
4.67
Wholesale Trade
3.99
Farm Services
3.68
The remaining sectors each account for less than 2% of total county exports in San Joaquin.
Table 7
Region Industry Exports as a
Percent of Total Exports
Industry Sectors
Exports as a % of
Total County Exports
Mfg/Food &Kindred
41.03
Farm Production
17.34
Mfg/Durable
14.15
F.I.R.E
8.43
Retail Trade
4.33
Farm Services
3.17
Health Services
3.06
Trans & Public Utilities
2.4
The remaining sectors each account for less than 2% of total Region exports.
11
Net exports identify the magnitudes of the injections of a sector relative to the leakages of the
sector. Net exports of each sector are equal to its exports minus its imports. The higher the
number the greater the injection into the economy from a sector. The figures that follow show
which industries were net exporters in each of the economies.
Figure 3
Net Exports for Stanislaus County (millions $)
G overn m en t
H ealth S ervic es
B u s in es s S ervic es
F in ., In s ., & R eal E s tate
R etail T rad e
W h oles ale T rad e
T ran s & P u b lic U tilities
M f g /D u rab le
M f g /O th er N on d u rab le
M f g /F ood an d K in d red
M in in g an d C on s tru c tion
O th er S ervic es
F arm S ervic es
F arm P rod u c tion
-5 0 0 .0 0
0 .0 0
5 0 0 .0 0
1 ,0 0 0 .0 0
1 ,5 0 0 .0 0
2 ,0 0 0 .0 0
2 ,5 0 0 .0 0
Once again one sees the importance of manufacturing/food & kindred to the Stanislaus County
economy. It is, by far, the largest net exporter, meaning that this sector is bringing dollars into the
local economy from the outside. Other net exporters include farm production,
manufacturing/durable, health services, farm services, retail trade, F.I.R.E., and government.
12
Figure 4
Net Exports for Merced County (millions $)
Government
Health Services
Business Services
Fin., Ins., & Real Estate
Retail Trade
Wholesale Trade
Trans & Public Utilities
Mfg/Durable
Mfg/Other Nondurable
Mfg/Food and Kindred
Mining and Construction
Other Services
Farm Services
Farm Production
-200.00
-100.00
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
Figure 5
Net Exports for San Joaquin County (millions $)
Government
Health Services
Business Services
Fin., Ins., & Real Estate
Retail Trade
Wholesale Trade
Trans & Public Utilities
Mfg/Durable
Mfg/Other Nondurable
Mfg/Food and Kindred
Mining and Construction
Other Services
Farm Services
Farm Production
-400.00
-200.00
0.00
200.00
400.00
600.00
800.00 1,000.00 1,200.00 1,400.00 1,600.00
The other counties are different from Stanislaus. In Merced, manufacturing/food & kindred and
farm production are the largest net exporters. The only other positive net exporters are farm
services, manufacturing durable, and government. San Joaquin County has a number of positive
net exporting sectors. The region as a whole is once again reliant on manufacturing/food and
kindred as an injector of dollars to the regional economy. It is, by far, the largest net exporter in
13
the region. This sector is followed by farm production, manufacturing durable, F.I.R.E., farm
services, retail trade, government, and health services.
Figure 6
Net Exports for the Region (millions $)
Government
Health Services
Business Services
Fin., Ins., & Real Estate
Retail Trade
Wholesale Trade
Trans & Public Utilities
Mfg/Durable
Mfg/Other Nondurable
Mfg/Food and Kindred
Mining and Construction
Other Services
Farm Services
Farm Production
-1,000.00
0.00
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
The top net exporting industry sectors in the two Bay Area economies are business services and
manufacturing/durable in Santa Clara and wholesale trade, business services, and transportation
& public utilities in Alameda. The top net exporting sectors in the state as a whole are other
services, F.I.R.E., and business services.
14
§ Characteristics of Jobs
So far this report has examined the importance of industry sectors in a macro sense, meaning
overall levels of output and net exports of industry sectors. The I-O model provides information
that can be used to better understand how industry sectors and the employment associated with
them differ in a micro sense, including numbers of employees in industry sectors, earnings and
productivity.
Employment and Productivity
The first three figures in this section relate to employment and compensation levels. Figure 7
shows the level of employment compensation as a percent of total compensation in each region.
Employee compensation measures wage, salary and fringe benefits, but it does not include
proprietor income or corporate profits.
Figure 7
Employee Compensation as a Percent of Total County Compensation
G overn m ent
H ealth S ervic es
B us in es s S ervic es
F in ., Ins ., & R eal E s tate
R etail T rade
W holes ale T rade
T rans & P ublic U tilities
M fg/D urab le
M fg/O ther N ond urab le
M fg/F ood and K in dred
M ining and C ons truc tion
O ther S ervic es
F arm S ervic es
F arm P rod uc tion
0.0 0
5.0 0
10.00
M ec e d
15
15 .00
20 .00
S a n J oa q u in
25 .00
S tan isla u s
30 .00
3 5.00
As is the case in other indicators, the three counties are similar, but not identical. Figure 7 shows
that government claims the largest share of employee compensation in all study areas. In
addition, it constitutes a larger percent of total compensation in Merced County than in the other
two counties. In Stanislaus County, government comprises the largest share of employee
compensation. This is followed by manufacturing/food & kindred, health services, retail trade,
and other services in that order. Interestingly, if all services are aggregated in the Stanislaus
County economy they surpass the government sector.
In Merced County, government is followed by manufacturing/food & kindred, retail trade, health
services, farm production, and other services. In the case of Merced, all services do not add up to
the level of the government sector. In San Joaquin County, government is the largest followed by
retail trade, other services, health services, wholesale trade, and manufacturing durable.
There are a number of reasons why a sector will have a large level of total employee
compensation. One is that it employees many people while another is that each employee is well
compensated. Figure 8 shows the employment in each industry as a percent of total employment
in the study area. Figure 9 shows earnings per employee, which includes wage and salary and the
monetary value of nonwage compensation items such as health insurance.
16
Figure 8
Industry Employment as a Percent of County Employment
Government
Health Services
Business Services
Fin., Ins., & Real Estate
Retail Trade
W holesale Trade
Trans & Public Utilities
Mfg/Durable
Mfg/Other Nondurable
Mfg/Food and Kindred
Mining and Construction
Other Services
Farm Services
Farm Production
0.00
5.00
Merced
10.00
15.00
San Joaquin
20.00
25.00
Stanislaus
In Stanislaus County government makes up the largest share of county compensation, but is
second in terms of percent of employment. Retail trade has the largest share of total county
employment. This is followed by government, other services, health services,
manufacturing/food & kindred, and mining and construction.
The fact that the order is different is important. Retail trade is fourth in terms of employee
compensation but number one in employment. This suggests that employees in this sector have
lower earnings per employee relative to the other sectors. The opposite occurs in the
manufacturing/food & kindred sector. This sector is number two in employee compensation but
is fifth in employment levels. This suggests that earnings per employee in this sector are high
relative to the other sectors in the economy. The conclusions are similar for all regions examined.
17
Figure 9 does show earnings per worker in each sector and supports the previous conclusions. In
Stanislaus County earnings per worker are highest for employees in health services, followed by
manufacturing durable, manufacturing/food & kindred, manufacturing/other nondurable, and
mining and construction.
Figure 9: Earnings Per Worker
G overn m en t
H ealth S ervic es
B u s in es s S ervic es
F in ., In s ., & R eal E s tate
R etail T rad e
W h oles ale T rad e
T ran s & P u b lic U tilities
M fg /D u rab le
M fg /O th er N on d u rab le
M fg /F ood an d K in d red
M in in g an d C on s tru c tion
O th er S ervic es
F arm S ervic es
F arm P rod u c tion
-
M erc ed E arn in g s /em p loyee
5 ,0 0 0
1 0 ,0 0 0
1 5 ,0 0 0
2 0 ,0 0 0
S an J oaq u in E arn in g s /em p loyee
2 5 ,0 0 0
3 0 ,0 0 0
3 5 ,0 0 0
4 0 ,0 0 0
4 5 ,0 0 0
S tan is lau s E arn in g s /em p loyee
Productivity is a measure of the output of an industry per employee and is an important
determinant of incomes and well-being. People who are most productive are generally better
paid. The data, as illustrated in Figure 10, reveal that the manufacturing sectors have the highest
productivity levels. These are sectors that require large amounts of capital and technology. There
are some differences in productivity levels amongst the counties, but these are not significant in
the majority of industries.
18
Figure 10
Productivity
G overnm ent
H ealth S ervic es
B us ines s S ervic es
F in., Ins ., & R eal E s tate
R etail T rade
W holes ale T rade
T rans & P ublic U tilities
M fg/D urable
M fg/O ther N ondurable
M fg/Food and K indred
M ining and C ons truc tion
O ther S ervic es
F arm S ervic es
Farm P roduc tion
M erc ed O utput/em ployee
50,000
100,000
150,000
S an J oaquin O utput/em ployee
200,000
250,000
300,000
S tanis laus O utput/em ployee
Productivity levels in each sector are similar across all study areas, with manufacturing at the top.
The I-O model does not provide enough information to explain why productivity levels vary
from industry to industry or from place to place, but there are a number of factors that affect
productivity and knowing what they are can shed some light to help explain some of the
differences.
The type of product and production techniques will affect productivity levels. Many of the
industries with low productivity levels are that way because they are labor intensive. Health
services is an example. The quality of a doctor's care, in part, depends upon the doctor spending
time with the patient. This reasoning holds for other industry sectors including retail trade and
government. In addition, many of these industries cannot use technology to replace the human
contact. As a result they will have lower productivity levels compared to more capital intensive
manufacturing.
19
Productivity differences between study areas can be explained by a number of factors. First, is
quality of labor: workers with more experience, education, and training will be more productive,
assuming all else is the same. Second, workers in one area may be less productive than in another
because they are using old technology or equipment. Third, management practices may differ.
§ Job Impacts
The first section described the importance of different industry categories to the local economy in
terms of output and net exports. This was followed by a description of how jobs in those industry
sectors differ in terms of employment, earnings, and productivity. One of the principle
advantages of input-output models is that one can derive estimates of multipliers which make it
possible to examine how jobs have different impacts on the economy. Jobs in some sectors may
be tied to many or few jobs in other sectors and multipliers reflect how jobs created in particular
sectors impact employment in others. Multipliers offer yet another way to understand the
importance of, and differences among, jobs in an economy.
Going back to Figure 1, on page 3, it is possible to illustrate how a change in final consumption
will be multiplied throughout the economy. An increase in the demand for the products of
manufacturing/food & kindred will cause production in that industry, and other industries to
increase. For example, farmers will have to grow more produce. The initial increase in
consumption will ripple or multiply throughout the economy. The multipliers allow one to
estimate all of these effects on the economy.
Multipliers are estimated according to direct, indirect, induced and total effects. The direct
effects are the changes in employment or output that are caused by an increase in the demand for
a firm's or sector's product. Take, for example, a firm that expands as a result of increased
demand. Assume that the firm adds 20 workers in order to meet the increased demand. The 20
workers hired by the firm are the direct employment effects resulting from the increased demand.
The indirect effects are the changes that take place in other sectors of the economy. More output
in the food processing sector will mean that suppliers will have to expand production. This may
mean that they will hire more employees. The induced effects are the changes that occur because
20
people in the area have more income. When incomes increase, so does spending. Firms in
various sectors may need to expand production to meet the increased demand. This change will
be captured in the induced effects. The total effects are the sum of the direct, indirect and induced
effects.
Multipliers will vary from one sector to another and will vary from region to region. While it is
difficult to make any broad generalizations regarding the size of multipliers, it is possible to
identify some features of the local economy that will impact the magnitude of multipliers.
Population and geographic size: Areas with lower populations will have lower multipliers.
Businesses in these areas must sell to the export markets and purchase ingredients from
businesses outside the area. It is also likely that people will purchase goods and services from
other areas. As a result fewer dollars circulate within the economy. The size of the area has much
the same impact.
Transportation networks: Easy access to other regions makes it easier for households to shop
outside the area and for firms to purchase inputs from other areas, thus lowering the values of the
multipliers.
Income levels: Increases in local incomes may increase the multiplier or cause them to fall. If
increases in incomes attract people, it could lead to new retail establishments, which could keep
spending local. Increases in incomes without population increases could result in higher savings
levels and/or more nonlocal shopping.
21
Output Multipliers
Output multipliers show the effect of a $1 change in the final demand for one industry’s output.
An output multiplier of 1.5 means that a $1 change in sector X output will actually increase all
output in the economy by $1.50.
The output multiplier can be of use in studying and understanding intra-regional linkages. When
a firm buys and sells from firms within an area, that firm's activity will have a larger impact on
output levels in that area. Larger output multipliers will result from more connections between
sectors within the region. Thus, a more diverse regional economy will have larger multipliers
while a highly specialized economy will have smaller ones.
When looking at the output multipliers, one should focus on the indirect, induced and total
effects. The indirect effects are estimates of the output in other sectors that are created for use in
the original sector. For example, (see Table 8, below) the wholesale trade sector in Stanislaus
County will require production of $.35 of output in other sectors for every dollar in final sales in
wholesale trade. The induced effects in this sector are equal to .49. This means that every dollar
in final sales in the wholesale sector will result in $.49 in output in other sectors in the economy.
Once again, the induced effects are the result of the income generated by production in the
wholesale sector. Workers in the wholesale sector and in the sectors that supply that industry earn
income. They will use this income to purchase goods and services and will therefore generate
output. The output required to supply this demand is measured by the induced effects.
22
Table 8
Stanislaus County Output Multipliers
1
24
27
28
58
104
133
433
447
448
456
469
490
510
Industry
Farm Production
Farm Services
Other Services
Mining and Construction
Mfg/Food and Kindred
Mfg/Other Nondurable
Mfg/Durable
Trans & Public Utilities
Wholesale Trade
Retail Trade
Fin., Ins., & Real Estate
Business Services
Health Services
Government
Indirect Effects
0.35
0.21
0.34
0.29
0.45
0.47
0.31
0.55
0.36
0.25
0.35
0.19
0.24
0.14
Induced Effects
0.33
0.69
0.59
0.49
0.30
0.35
0.37
0.43
0.49
0.54
0.20
0.61
0.67
0.82
Total Effects
1.67
1.91
1.93
1.78
1.75
1.82
1.67
1.98
1.85
1.79
1.55
1.80
1.91
1.96
The total effect is equal to the sum of the direct, indirect, and induced effects. In
Stanislaus County, the total effects multipliers range from a low of 1.67 for farm
production and manufacturing/durable to a high of 1.98 for transportation & public
utilities. Overall the output multipliers are smaller in Merced than in Stanislaus. The
output multipliers are a little larger in San Joaquin than in Stanislaus. The total effects of
multipliers in Merced ranges from 1.43 to 1.95. While in San Joaquin County, they range
from 1.62 to 2.03. The San Joaquin economy is the largest and will have more
intracounty supply linkages than the other counties.
Table 9
Output Multipliers for other local economies (Total Effects)
1
24
27
28
58
104
133
433
447
448
456
469
490
510
23
Farm Production
Farm Services
Other Services
Mining and Construction
Mfg/Food and Kindred
Mfg/Other Nondurable
Mfg/Durable
Trans & Public Utilities
Wholesale Trade
Retail Trade
Fin., Ins., & Real Estate
Business Services
Health Services
Government
Merced
1.72
1.80
1.78
1.65
1.83
1.96
1.55
1.76
1.72
1.67
1.43
1.70
1.79
1.82
San Joaquin
1.62
1.69
1.98
1.80
1.74
1.95
1.72
1.99
1.90
1.82
1.58
1.86
1.95
2.03
Region
1.71
1.82
1.96
1.79
1.80
1.95
1.71
1.99
1.89
1.82
1.56
1.84
1.94
2.01
Employment Multipliers
An important question is how many jobs are created by the various sectors of the economy. To
this point, this has been addressed by looking at the number of employees in each sector. While
this is an important way to understand employment, it represents an incomplete understanding of
job creation. As has already been pointed out in this report, the various industries in a region are
connected to one another. This is true with output and with regard to employment. Employment
multipliers give an indication of the degree to which employment in one industry affects
employment in other industries. In addition, employment multipliers estimate how much
employment will increase or decrease as the result of a change in the output of a particular sector.
As with the output multipliers one can examine direct, indirect and induced employment changes
that result from changes in the final purchases of an industry. It is also possible to calculate the
number of jobs that are connected to each job in a particular industry sector, which is referred to
as the employment multiplier.2
The direct employment effect measures the number of employees in an industry from one million
dollars in final sales. A direct effect of 20 means that every one million dollars in final sales will
result in the employment of 20 workers in that sector. The size of the direct effect is largely
determined by the nature of the work. Service industries will have high direct effects because
they are labor intensive. Manufacturing industries will have smaller direct effects because they
use more capital intensive production techniques.
The indirect employment effects measure the number of jobs in other sectors that are created by
one million dollars of final demand in some other industry sector. If a new restaurant opens up, it
will hire workers. These are measured as the direct effects. This restaurant will also need to
purchase supplies from other businesses. These businesses will need employees. The number of
the employees required in the other sectors is measured as the indirect effect.
24
The size of the indirect effects are affected by the degree of supply linkages to local producers.
Industries that purchase a large volume of supplies from local businesses will have larger indirect
effects. The size of the indirect effects will also be impacted by the labor requirements of the
suppliers.
The induced employment effects measure the income effects on employment. When workers in
the various industries get paid, they will use their income to buy goods and services. Some of the
workers from the restaurant will buy groceries. The grocery store will need to hire people to
service these shoppers. The size of the induced effect will be influenced by all the factors
described in the section on output multipliers, including the amount of income spent, the amount
of local purchases, and the labor requirements of the businesses involved.
The direct, indirect, and induced effects measure the number of jobs created when an industry
sector's output expands. It is possible to calculate how many jobs are associated with each job in
a particular industry sector. The employment multipliers for the 14 industry sectors in Stanislaus
County are reported below. The employment multiplier for farm production in Stanislaus County
is 2.03. This means that every job in the farm production sector is connected to 1.03 jobs in other
sectors in the economy.
2
The employment multiplier is a Type II multiplier and is calculated by dividing the sum of the direct, indirect, and
25
Table 10
Stanislaus County Employment Multipliers
1
24
27
28
58
104
133
433
447
448
456
469
490
510
Industry
Farm Production
Farm Services
Other Services
Mining and Construction
Mfg/Food and Kindred
Mfg/Other Nondurable
Mfg/Durable
Trans & Public Utilities
Wholesale Trade
Retail Trade
Fin., Ins., & Real Estate
Business Services
Health Services
Government
Direct
Employment
Effects*
7.79
52.64
23.05
11.84
4.67
5.56
7.05
8.72
11.06
25.62
5.49
26.64
15.46
24.11
Indirect
Employment
Effects*
3.31
3.09
5.02
4.03
4.15
4.86
3.42
6.84
5.20
3.19
3.90
2.77
2.86
1.70
Induced
Employment
Effects*
4.68
9.96
8.44
7.08
4.25
4.98
5.26
6.17
7.07
7.78
2.88
8.78
9.60
11.84
Employment
Multipliers
2.03
1.25
1.58
1.94
2.80
2.77
2.23
2.49
2.11
1.43
2.24
1.43
1.81
1.56
*Per Million dollars of
output
These multipliers may be used to estimate the impact of a firm entering or leaving the area. If a
firm in the manufacturing/food and kindred sector enters the economy, it will hire workers. The
multiplier of 2.80 for that sector implies that every worker it hires will add 1.8 workers in other
sectors of the economy.
The service industries have the highest direct employment effects. Among these are farm
services, business services, government, and retail trade. The direct effects measure the number
of employees that a particular industry employs per million dollars of output. In relation to the
high direct employment effects, these industries have low indirect and induced effects. This
means that they will have relatively low employment multipliers. These industries require quite a
bit of labor to provide the product to the public, but do not require a great deal of employment
from other sectors.
The manufacturing and transportation sectors have the highest employment multipliers. Other
sectors with high employment multipliers are F.I.R.E. and wholesale trade. This means that every
induced effects by the direct effect.
26
job in these sectors will add relatively more jobs in other sectors of the economy than the sectors
with low employment multipliers. These sectors are not labor intensive, meaning they do not
require as much labor per unit of output as the sectors listed in the previous paragraph. The direct
employment effects for this group of industries is lower, but for each job in the sector there are a
relatively large number of jobs in other sectors to support it.
The next set of tables show the employment multipliers for the other local study areas. When
comparing the different economies, one sees that the multipliers in each sector are similar in size,
but the multipliers do vary among the industry sectors.
Table 11
Employment Multipliers for other Local Economies.
1
24
27
28
58
104
133
433
447
448
456
469
490
510
Farm Production
Farm Services
Other Services
Mining and Construction
Mfg/Food and Kindred
Mfg/Other Nondurable
Mfg/Durable
Trans & Public Utilities
Wholesale Trade
Retail Trade
Fin., Ins., & Real Estate
Business Services
Health Services
Government
Merced
2.27
1.21
1.46
1.69
2.63
3.09
1.86
2.34
1.90
1.35
1.94
1.33
1.67
1.37
San Joaquin
1.81
1.28
1.62
2.02
3.43
2.74
2.16
2.73
2.18
1.46
2.37
1.44
1.82
1.54
Region
2.07
1.27
1.59
1.96
3.04
2.92
2.19
2.65
2.14
1.44
2.28
1.43
1.81
1.52
The next set of tables shows the top 20 and bottom 20 detailed non-government sector
employment multipliers in Stanislaus County. These multipliers are from the 279 sector model of
Stanislaus County and only include industries with total industry output greater than $10 million.
As one can see, the pattern is similar to that already described. Appendix B lists the industry
sectors operating in the Stanislaus County economy with the total industry output, employment,
and employment multiplier for each sector.
27
Table 12
Top 20 Employment Multipliers
Industry
58
62
202
76
2
384
65
511
93
444
170
254
59
459
273
446
5
89
60
100
Meat Packing Plants
Cheese, Natural and Processed
Nitrogenous and Phosphatic Fertilizers
Wet Corn Milling
Poultry and Eggs
Motor Vehicles
Fluid Milk
State and Local Electric Utilities
Wines, Brandy, and Brandy Spirits
Gas Production and Distribution
Sanitary Paper Products
Blast Furnaces and Steel Mills
Sausages and Other Prepared Meats
Insurance Carriers
Metal Cans
Sanitary Services and Steam Supply
Cattle Feedlots
Animal and Marine Fats and Oils
Poultry Processing
Potato Chips & Similar Snacks
Employment
Multiplier
5.77
4.13
3.57
3.54
3.53
3.51
3.44
3.12
3.00
2.90
2.87
2.84
2.82
2.69
2.65
2.65
2.64
2.57
2.54
2.53
Table 13
Bottom 20 Employment Multipliers
Industry
480
465
27
491
472
454
505
467
489
488
452
499
449
501
455
474
476
26
466
13
525
28
Electrical Repair Service
Portrait and Photographic Studios
Landscape and Horticultural Services
Nursing and Protective Care
Services To Buildings
Eating & Drinking
Religious Organizations
Funeral Service and Crematories
Membership Sports and Recreation Clubs
Amusement and Recreation Services, N.E.C.
Apparel & Accessory Stores
Child Day Care Services
General Merchandise Stores
Residential Care
Miscellaneous Retail
Personnel Supply Services
Detective and Protective Services
Agricultural, Forestry, Fishery Services
Beauty and Barber Shops
Hay and Pasture
Domestic Services
Employment
Multipliers
1.37
1.37
1.34
1.34
1.33
1.32
1.32
1.31
1.31
1.30
1.28
1.27
1.27
1.27
1.26
1.23
1.23
1.19
1.18
1.16
1.09
Industry Impacts
Another way to look at the importance of an industry is to look at the impact it has on the
economy and the other industries in the region. This section examines the impact of the top six
industries in the county and the linkages with other local industries. In order to do this, a model
was created that aggregated the industry sectors by their two digit SIC code. This resulted in a
total of 62 industry sectors in Stanislaus County out of a possible 65 industry sectors. The list of
industries using this classification scheme is provided in appendix C.
The top six sectors in the County in terms of total industry output are listed in table 14. The table
also lists the employment levels for each industry sector. All of these sectors have over one
billion dollars of direct output. There is a significant drop off in the dollar value of output after
health services. The next sector is wholesale trade with output equaling $657 million.
Table 14
Top Six Industries in Terms of Output.
Industry
Industry Output
Employment
Food Processing
$2,977,410,000
13,915
Farms
1,510,570,000
11,771
Retail Trade
1,226,360,000
31,416
Real Estate
1,200,380,000
3,670
Construction
1,072,960,000
12,754
Health Services
1,040,180,000
16,085
The numbers in the table above report the direct impact of each industry sector on the economy.
From the discussion on multipliers, it should be clear that this is not the full extent of the impact
each of these sectors has on the economy. In fact, the total impact each of these sectors has on the
economy includes the indirect and induced effects. The total impacts of each of these sectors with
regard to total output, employment, and personal income are listed in the table below.
29
Industry
Food Processing
Farms
Retail Trade
Real Estate
Construction
Health Services
Table 15
Total Impacts
Output
Employment
$4,875,443,578
2,527,270,356
2,037,567,053
1,625,967,892
1,772,011,606
1,797,514,519
36,333
26,566
42,608
8,650
23,256
26,654
Personal
Income
$1,134,079,559
705,774,817
872,554,484
142,874,892
695,038,867
902,993,806
When the indirect and induced effects are included, the order of largest output impact is changed
somewhat. Health services ranks fourth, followed by construction and real estate. This is because
real estate does not have as many linkages in the economy as the other sectors as will be shown
below.
It is also important to note that while retail trade generates the largest amount of employment, the
gap between it and food processing narrows substantially when all effects are included. This is
one of the reasons it is important to consider the induced and indirect effects of industry sectors.
As jobs are added to the retail sector they do not mean as much in terms of employment in other
parts of the economy as jobs added to sectors such as food processing.
One of the byproducts of estimating the impact of an industry with an I-O model is a list of
industries impacted and the degree to which they are impacted. Table 16 once again lists the top
six output sectors in Stanislaus County, and lists the number of other industry sectors that each of
these six industries affect. The table reports the number of industries with more than $20 million
and $10 million of output produced as a result of demand from each of the six sectors. So, for
example, food processing required more than $10 million in output from 22 different industry
sectors and more than $20 million in output from 15 different industry sectors.
30
Industry
Food Processing
Farms
Retail Trade
Real Estate
Construction
Health Services
Table 16
Industries Affected
Industries with 10+
22
15
18
7
16
16
Industries with 20+
15
9
10
3
8
7
The next table lists the industries that have greater than $20 million in total effects from the food
processing sector. Also listed is the output impact for each industry as well as the employment
impact in each sector.
Table 17
Industries affected by Food Processing $20 million +
Industry
Output
Employment
Farms
$611,593,280
4,765
Ag Services
28,312,210
1,478
Construction
39,430,400
468
Motor Freight Transport & Warehouse
64,391,528
758
Communications
29,763,526
161
Utilities
29,230,562
89
Wholesale Trade
177,573,328
1,963
Retail Trade
147,107,024
3,768
Banking
43,738,216
308
Insurance Carriers
23,643,278
196
Real Estate
147,030,848
449
Business Services
47,849,676
1,274
Health Services
112,231,040
1,735
Professional Services
23,618,200
404
State & Local Non-ed. Government
26,246,778
462
The next five tables do the same thing for the each of the other five top output producing industry
sectors.
31
Table 18
Industries affected by Farms $20 million +
Industry
Output
Employment
Ag Services
$79,768,904
4,164
Construction
24,577,220
292
Food Processing
44,128,160
206
Motor Freight Transport & Warehouse
24,509,620
288
Wholesale Trade
60,664,456
670
Retail Trade
91,699,024
2,349
Banking
27,865,032
196
Real Estate
120,491,728
368
Health Services
71,632,984
1,107
Table 19
Industries affected by Retail $20 million +
Industry
Output
Employment
Construction
$37,135,536
441
Food Processing
36,656,052
171
Communications
23,601,640
127
Wholesale Trade
51,772,488
572
Banking
32,673,804
230
Real Estate
141,933,712
433
Business Services
32,189,908
857
Health Services
85,778,056
1,326
Legal Services
20,746,908
292
Professional Services
24,094,042
412
Construction
Retail Trade
Banking
32
Table 20
Industries affected by Real Estate $20 million +
Industry
Output
$72,022,552
27,477,616
27,710,706
Employment
856
704
195
Table 21
Industries affected by Construction $20 million +
Industry
Output
Employment
Wood Products
40,690,236
492
Motor Freight Transport & Warehouse
21,810,928
257
Wholesale Trade
54,769,080
605
Retail Trade
133,749,408
3,426
Banking
28,581,562
201
Real Estate
79,160,848
242
Health Services
68,356,912
1,057
Professional Services
39,582,024
678
Table 22
Industries affected by Health Services $20 million +
Industry
Construction
Communications
Wholesale Trade
Retail Trade
Banking
Real Estate
Business Services
Output
Employment
$27,837,960
331
22,053,936
119
46,449,944
513
113,217,016
2,900
28,237,604
199
142,734,992
436
27,168,404
723
These tables reinforce the idea that more connections result in greater impacts. Food processing
is connected to many more sectors than real estate, which is one more reason it is so important to
the county.
§ Concluding Remarks
This analysis employed an input-output modeling technique to examine the local economy. The
Gross County Product of Stanislaus County in 1994 was $8.369 billion. This was 37.3% of the
Gross Regional Product (Stanislaus, San Joaquin, Merced)
The economies of Stanislaus, Merced, and San Joaquin are similar but not identical. Farm
production is far more important to Merced (close to 25% of TIO) than to the other two counties.
Health services and manufacturing/food & kindred represent larger percentages of TIO in
Stanislaus than in the other two counties. Government has the largest percentage of employment
and employee compensation in all three counties, but is more important in Merced than in the
other two counties.
33
Manufacturing/food & kindred is the most significant industry in Stanislaus County in terms of
production but not in terms of employee compensation or employment. Manufacturing/food &
kindred is the largest share of total industry output in the county (20%). Government represents a
greater share of employee compensation and employment than manufacturing/food & kindred.
Retail trade and other services employ a greater percent of total employees in the county.
Manufacturing/food & kindred brings significant amounts of money into the economy and is the
largest net exporter in the county. It is also the largest net exporter in Merced, but farm
production is a close second.
Food processing has the largest impact on the Stanislaus County economy in terms of industry
output, followed by farms, retail trade, real estate, construction, and health services. The dollar
value of output in food processing is double that of the second largest output producer which are
farms. When direct, indirect, and induced effects are included, food processing is tied to almost
$5 billion in output.
Retail trade employs the largest number of people in the county, followed by health services,
food processing, construction and farms. When direct, indirect, and induced effects are included,
retail trade is still the largest but it is followed by food processing, health services, farms, and
construction.
Of the largest output producers, food processing affects the largest number of other industries in
the County. This observation comes from the fact that it has among the highest multipliers and
from looking at the number of industries that it buys from.
Health services are more important to Stanislaus County than to Merced and San Joaquin. It
produces a larger share of TIO in Stanislaus than in the other two counties. It employs a greater
share of the work force in Stanislaus than in the other two counties. It provides a greater share of
employee compensation in Stanislaus than in the other two counties. It is a net exporting sector
for the county.
Future areas of study from this portion of the project:
Based on the findings of the input-output analysis, the following would be particularly fruitful
areas of study:
·
The health care sector of the economy to discover what makes it so important to the economy
and what if anything can be done to support it.
·
Update the IMPLAN data. This means continuing to purchase the data for the state and all
counties within the state each year. It also means getting information from local firms in
order to make the data better reflect local production and purchasing practices.
34
·
Continue to use this modeling technique to examine how the structure of the economy
changes over time.
·
Use this model as a tool to examine the impact of different development strategies in the
County. It can aid in the process of targeting development and insuring the largest return
from economic development activities.
·
Use the social accounting matrix from the IMPLAN software to develop a general
equilibrium model of the county. This could be used to evaluate the impact of price changes,
tax changes, economic development packages, and more.
35
Glossary of terms
Direct Effects: Changes in employment or output that are derived from some initial change in
the economy such as the startup of a new firm.
Employee Compensation: Includes wages, salaries, and fringe benefits such as employer
provided health insurance.
Employment: Number of part- and full-time jobs.
Employment Multiplier: In this report this term refers to Type II employment multipliers which
are the sum of the direct, indirect, and induced effects divided by the direct effects.
Exports: Dollar value of goods and services produced locally that are sold to buyers outside of
the region.
Gross County Product (GCP): The dollar value of all final goods and services produced within
the boundaries of the county during a given year.
Indirect Effects: Changes in employment and output that result from the second round of
spending changes that result from changes in the economy.
Induced Effects: Represents the impacts on all local industries caused by the expenditures of
new income generated by the direct and indirect effects resulting from a change in the economy.
Imports: Dollar value of goods and services purchased within a region that are produced outside
of the region.
Net Exports: Exports minus imports.
Personal Income: Represents all forms of employment income and is the sum of employee
number of employees in an industry.
Productivity: Output per employee. Is calculated by dividing total industry output by the number
of employees in an industry.
Proprietor’s Income: Income from self employment.
Total Effect: Total multiplier effect is the sum of the direct, indirect and induced effects.
Total Industry Output (TIO): Dollar value of output produced by a firm or industry.
Total Value Added: The sum of employee compensation, proprietor’s income and indirect
business taxes.
36
Technical coefficients.
Technical coefficients in effect reflect fixed proportion production functions for the
industries in the model. They are calculated by dividing the expenditures in each sector’s column
by the total sales of that row. (One can use the value of total production costs, which are the sum
of inputs and value added, instead of the value of total sales since total production will equal
total sales.) The technical coefficients matrix determines the multipliers in the matrix of total
requirements. One calculates the Leontief inverse in order to solve for the new levels of output in
each sector when given a new final demand figure.
The matrix of technical coefficients is a table of each sector’s costs as a proportion of its
sales. This matrix indicates, for each sector, how a sales dollar is divided among the other sectors
for input costs. Technical coefficients are regionalized in the IMPLAN ProTM software to take
into account the proportion of local production that serves as an input to local production. This
means that at the county level these measure the amount of inputs purchased locally, and will
usually be small because the area is small and depends on inputs from outside the area.
This system of linear equations is used to further develop the transactions table by
developing the matrix of technical coefficients. The terms in the equations above all refer to
dollar values of sales, purchases and output. Equation (4) shows how the technical coefficients
are calculated.
4.
aij =
zij
Xj
aij represents the ratio of sales from industry i to industry j to the total output of industry j. An aij
of .04 means that $.04 of input from industry i is used to make $1 of output in industry j. The
technical coefficients are assumed to be constant. Equations 2 can be rewritten as:
37
X 1 = a11 X 1 + a12 X 2 + × × × + a1i X i + × × × + a1n X n + Y1
X 2 = a21 X 1 + a22 X 2 + × × × + a2i X i + × × × + a2 n X n + Y2
X 3 = a31 X 1 + a32 X 2 + × × × + a3i X i + × × × + a3n X n + Y3
5.
×
×
×
X i = ai1 X 1 + ai 2 X 2 + × × × + aii X i + × × × + ain X n + Yi
×
×
X n = an1 X 1 + an 2 X 2 + × × × + ani X i + × × × + ann X n + Yn
Using matrix notation this becomes
6.
X = A· X +Y
Rearranging these terms gives:
7.
X - (A · X ) = Y
8.
( I - A) · X = Y
and,
where I is an n x n identity matrix, A is an n x n matrix of the technical coefficients, X is the 1 x
n matrix of industry outputs and Y is the matrix of final demands. The values in the A and Y
matrices are known and the values of X are not. The equation that needs to be solved is
9.
X = (1-A)-1 Y
where (I - A)-1 is what is known as the Leontief inverse and is the basis of all multipliers.
Multipliers.
Generally multipliers are used to predict or forecast the overall impact of a change in the
final demand for an industry’s output. There are a variety of multipliers, but all are based on the
same ideas and have similar mathematical structures. Multipliers are derived from the Leontief
inverse matrix and take several different forms including output multipliers, income multipliers,
and employment multipliers. Type I and II multipliers can be derived in each of these categories
of multipliers. Multipliers represent one of the key outputs from I-O modeling. This section will
define the types of multipliers, review the interpretation of the multipliers and explain their
importance.
38
Before discussing the specific multipliers it is important to understand initial, total, direct,
indirect and induced effects. The initial effect is the effect of some exogenous change to the
economy. Reduced government purchases of medical equipment would be an example of an
exogenous change. If the government reduces spending by $10 billion, the initial effect is that
reduction. This is not the extent of the impact this will have on the economy though. Reduced
government purchases from one industry will also reduce the output produced by other
industries. The total effect from the change in government purchases from one sector will include
the initial change plus all of the changes it causes in the other industries.
The total changes in the economy can be divided into the direct and indirect effects which
make up the elements of the Leontief inverse matrix. The direct effects of the change are the
changes in output in the sector that experiences the exogenous change. The diagonal elements of
the Leontief inverse measure the direct effects and will usually be greater than one. Let’s assume
that the government reduces its purchases of medical equipment and that the diagonal element of
the Leontief inverse is 1.3. The one in this number shows the change in output in the medical
equipment sector caused by the reduction of government purchases. A dollar reduction in
government demand will translate into a dollar reduction in production. Other sectors will also
be affected by this change. The output of the medical equipment sector may also be used as
inputs in other sectors. The .3 shows how the output of the medical equipment sector will change
as a result of the changes in the output produced by the other sectors.
The indirect effects are the changes in output in the other sectors of the economy that
result from the changes in output in the initial sector. The medical equipment sector will use the
output of other industries to produce its final output. When the government buys less from the
medical equipment sector, that sector will buy less from other sectors. This means that other
sectors will produce less output. These changes in the other sectors are indirectly related to the
initial change in government purchases. The indirect changes are calculated from the off-diagonal
elements of the Leontief inverse matrix. The sum of the direct and indirect effects are used to
derive simple multipliers.
39
Total multipliers are derived from the direct, indirect, and induced effects. It is possible to
extend the analysis to capture the impact that changes have on households. The impact of
changes on households are called the induced effects. Induced effects are found when the
coefficients matrix is closed with respect to households. This just means that households are
considered to be endogenous to the model. The induced effects then are the changes in household
income that come from a change in the demand in a given sector. When this is done, the
measured effects of changes will be larger meaning larger multipliers.
Output Multipliers
The preceding discussion leads directly to the definition of output multipliers. Output
multipliers show the effect of a $1 change in the final demand of one industry’s output. It can be
broken into simple and total multipliers. To calculate the simple multiplier one sums the indirect
and direct effects of the change and divides it by the initial change. The total multiplier is
calculated by summing the direct, indirect, and induced effects and dividing by the initial change.
An output multiplier of 1.5 means that a $1 change in sector X will increase all output by $1.50.
Employment Multipliers
Employment multipliers estimate how much employment will change as the result of a
change in the output of a particular sector. In a process similar to that of the income multipliers
one can derive household employment multipliers (employment effects) and type I and II
employment multipliers calculate the change in total employment to the initial change in
employment.
Assumptions and Limitations of I-O Models
This type of modeling procedure does have some limitations. One is that it assumes that
the production techniques and technology that are used in Stanislaus County are the same as the
national average. As far as the model is concerned, the firms in Stanislaus County use the same
production techniques as firms anywhere else in the country. This means that the model assumes
that firms in the county use the same amount of labor to produce a given amount of output as
40
firms elsewhere in the nation. This assumption can have important results. If companies in
Stanislaus County use more labor than the nation average, the employment estimates will be
underestimated. If the opposite is true, the estimates will be overstated. It is possible to change
the input ratios in the IMPLAN Pro™ software. This would require information about local firms
that at the present time is unavailable.
A second limitation of this model is that the technology is assumed to be constant even
when there is a change in the economy. For example, if labor becomes more expensive firms
usually will change the amount of labor they employ. In the input-output model this change will
not take place. While this is a limitation of the model, it generally takes some time for firms to
change behavior and the technology used does hold over a number of years (Miller and Blair
1985).
A third feature of I-O models is that they employ a constant returns to scale technology.
This means that as a firm or industry produces more output it will continue to add resources at a
constant rate. A more realistic model would probably employ increasing returns to scale, which
means that output can expand faster than the number of inputs.
Another important issue is that this model calculates local supply ratios based ont eh
characteristics of the local economy that is being studied. The IMPLAN Pro™ software estimates
based on the characteristics of the county or region, how much of the raw materials and other
resources used by business come from local suppliers. These ratios can be modified in the
IMPLAN Pro™ software when the information is available. There have not been any studies of
the Stanislaus County economy that would provide this information.
It must also be noted that this model is not a predictive model. This means that is cannot
predict competitor reactions, effects of demand changes or how a change to the economy will
continue to shape the economy in future years. It only estimates the potential impact on an
economy at one point in time.
41
Even though the model has limitations it is still widely used and accepted as an important
tool for estimating economic impacts (Bergstrom et. al, 1990).
References
Miller, R.E. and Blair, P.D. (1985). Input-Output Analysis: Foundations and Extensions.
Englewood Cliffs, New Jersey: Prentice Hall.
Minnesota IMPLAN Group, Inc. (1997) IMPLAN Professional™ Social Accounting & Impact
Analysis Software. Stillwater, Minnesota.
Douglas, Aaron J. and Harpmman, David A. (1995). Estimating Recreation Employment Effects
with IMPLAN for the Glen Canyon Dam Region. Journal of Environmental Management
44, 233-247.
Richardson, Harry W. (1972). Input-Output and Regional Economics. London: Weidenfeld and
Nicolson.
42
Appendix B: Specific Industry Sectors Operating in Stanislaus County
This is a list of the 279 industries that do operate in Stanislaus County. It is followed by a list of
the remaining IMPLANProTM sectors that do not exist within the county. This table also includes
total industry output, employment, and employment multiplier for each industry sector.
Table 1b: IMPLAN Industry Sectors in Stanislaus County.
Industry Sector
1
2
3
4
5
6
7
8
9
10
11
12
13
14
16
17
18
19
20
21
22
23
24
26
27
28
31
33
34
36
37
38
41
48
49
50
51
52
53
54
55
43
Dairy Farm Products
Poultry and Eggs
Ranch Fed Cattle
Range Fed Cattle
Cattle Feedlots
Sheep, Lambs and Goats
Hogs, Pigs and Swine
Other Meat Animal Products
Miscellaneous Livestock
Cotton
Food Grains
Feed Grains
Hay and Pasture
Grass Seeds
Fruits
Tree Nuts
Vegetables
Sugar Crops
Miscellaneous Crops
Oil Bearing Crops
Forest Products
Greenhouse and Nursery Products
Forestry Products
Agricultural, Forestry, Fishery Serv
Landscape and Horticultural Services
Iron Ores
Gold Ores
Ferroalloy Ores
Metal Mining Services
Metal Ores, Not Elsewhere Classified
Coal Mining
Natural Gas & Crude Petroleum
Sand and Gravel
New Residential Structures
New Industrial and Commercial Buildings
New Utility Structures
New Highways and Streets
New Farm Structures
New Mineral Extraction Facilities
New Government Facilities
Maintenance and Repair, Residential
Industry Output
532.036743
249.881622
47.154381
41.388126
18.466618
0.306733
5.618701
0.027983
4.17016
1.71758
6.98846
1.682536
41.348289
2.600405
77.497337
196.402496
230.412369
2.801012
2.619004
0.617453
1.952907
44.875172
3.455844
126.478935
11.446945
0.5851
2.811112
0.015273
0.009273
0.052777
0.647143
2.43646
3.770192
330.410675
192.102097
46.35397
38.277367
3.193161
4.990192
96.369682
72.927521
Employment
2,592
854
638
623
72
19
57
1
123
9
138
20
1,573
49
859
1,977
1,612
34
42
10
40
429
14
6,826
375
3
12
Employment
Multiplier
2.295
3.528
1.488
1.464
2.639
1.433
1.617
1.277
1.172
5.158
1.404
1.582
1.162
1.405
2.337
1.686
1.892
1.298
1.322
1.606
1.570
1.982
8.574
1.193
1.341
2.648
2.757
1
6
9
29
4,631
3,016
602
369
14
85
136
879
1.564
1.681
3.469
1.878
1.686
1.579
1.647
1.861
2.561
1.534
7.212
1.888
Industry Sector
56
57
58
59
60
62
63
64
65
67
68
70
71
76
77
78
79
83
85
88
89
90
93
95
96
100
103
108
122
124
125
128
130
136
137
138
140
141
142
143
144
145
146
147
148
149
151
156
157
158
164
44
Maintenance and Repair Other Facilities
Maintenance and Repair Oil and Gas
Meat Packing Plants
Sausages and Other Prepared Meats
Poultry Processing
Cheese, Natural and Processed
Condensed and Evaporated Milk
Ice Cream and Frozen Desserts
Fluid Milk
Canned Fruits and Vegetables
Dehydrated Food Products
Frozen Fruits, Juices and Vegetables
Frozen Specialties
Wet Corn Milling
Dog, Cat, and Other Pet Food
Prepared Feeds, N.E.C
Bread, Cake, and Related Products
Chocolate and Cocoa Products
Salted and Roasted Nuts & Seeds
Vegetable Oil Mills, N.E.C
Animal and Marine Fats and Oils
Shortening and Cooking Oils
Wines, Brandy, and Brandy Spirits
Bottled and Canned Soft Drinks & Water
Flavoring Extracts and Syrups, N.E.C
Potato Chips & Similar Snacks
Food Preparations, N.E.C
Broadwoven Fabric Mills and Finishing
Cordage and Twine
Apparel Made From Purchased Material
Curtains and Draperies
Canvas Products
Automotive and Apparel Trimmings
Special Product Sawmills, N.E.C
Millwork
Wood Kitchen Cabinets
Structural Wood Members, N.E.C
Wood Containers
Wood Pallets and Skids
Mobile Homes
Prefabricated Wood Buildings
Wood Preserving
Reconstituted Wood Products
Wood Products, N.E.C
Wood Household Furniture
Upholstered Household Furniture
Mattresses and Bedsprings
Public Building Furniture
Wood Partitions and Fixtures
Metal Partitions and Fixtures
Paperboard Containers and Boxes
Industry
Output
288.334259
1.196476
28.672565
19.632677
305.896942
83.824989
3.846224
4.937447
86.844566
802.727661
8.928352
144.262421
221.640976
11.07101
5.818068
162.182938
0.900261
152.405029
23.371902
3.872296
35.290642
3.834848
625.257629
4.5217
56.074825
169.546188
12.049333
1.273362
0.789382
0.304083
0.123852
0.06062
0.456874
0.849053
7.480117
12.036604
13.435206
0.816692
18.646637
20.294241
0.16185
0.437053
3.01713
0.123737
7.037911
0.413096
0.539165
12.26533
4.135042
0.394699
143.769913
Employment
3,022
27
78
92
2,430
191
9
20
258
4,150
58
840
1,215
15
19
445
6
765
73
7
140
8
2,125
16
238
651
66
16
10
7
2
1
4
15
94
191
130
12
270
204
1
2
13
2
100
8
7
115
61
5
798
Employment
Multiplier
1.729
1.389
5.765
2.816
2.536
4.133
3.408
2.763
3.445
2.434
2.080
2.298
2.277
3.535
2.455
2.299
1.933
2.227
2.433
3.213
2.566
2.766
2.996
2.641
2.114
2.530
2.051
1.405
1.490
1.178
1.406
1.429
1.591
1.579
1.529
1.452
1.609
1.563
1.516
1.612
2.008
2.162
2.561
1.464
1.537
1.307
1.445
1.722
1.569
1.585
1.951
Industry Sector
167
170
173
174
175
178
179
180
182
186
190
191
195
197
200
202
203
204
205
210
211
218
220
229
230
231
232
234
241
242
243
244
247
254
265
268
273
275
276
277
278
279
280
281
282
283
284
285
286
287
289
45
Bags, Plastic
Sanitary Paper Products
Converted Paper Products, N.E.C
Newspapers
Periodicals
Miscellaneous Publishing
Commercial Printing
Manifold Business Forms
Blankbooks and Looseleaf Binder
Alkalies & Chlorine
Cyclic Crudes, Interm. & Indus.
Plastics Materials and Resins
Drugs
Polishes and Sanitation Goods
Paints and Allied Products
Nitrogenous and Phosphatic Fertilize
Fertilizers, Mixing Only
Agricultural Chemicals, N.E.C
Adhesives and Sealants
Petroleum Refining
Paving Mixtures and Blocks
Gaskets, Packing and Sealing Devices
Miscellaneous Plastics Products
Leather Goods, N.E.C
Glass and Glass Products, Exc Containers
Glass Containers
Cement, Hydraulic
Ceramic Wall and Floor Tile
Pottery Products, N.E.C
Concrete Block and Brick
Concrete Products, N.E.C
Ready-mixed Concrete
Cut Stone and Stone Products
Blast Furnaces and Steel Mills
Aluminum Rolling and Drawing
Aluminum Foundries
Metal Cans
Cutlery
Hand and Edge Tools, N.E.C.
Hand Saws and Saw Blades
Hardware, N.E.C.
Metal Sanitary Ware
Plumbing Fixture Fittings and Trim
Heating Equipment, Except Electric
Fabricated Structural Metal
Metal Doors, Sash, and Trim
Fabricated Plate Work (Boiler Shops)
Sheet Metal Work
Architectural Metal Work
Prefabricated Metal Buildings
Screw Machine Products and Bolts, Etc.
Industry
Output
0.479237
262.427216
5.548827
50.125618
0.509892
5.246709
28.54994
23.969337
0.311078
1.111409
2.856289
6.586168
6.63647
15.378379
6.55253
15.383699
3.516044
1.618469
1.617514
7.065386
7.464522
30.45063
43.86013
0.329603
3.59851
127.622261
0.851829
0.246684
0.087746
5.122283
0.199364
28.195505
4.301661
26.677711
20.735556
7.022675
265.613281
0.115359
1.806553
1.73901
0.149665
0.573748
2.809108
1.33475
10.717139
21.287121
28.978611
24.978168
1.085822
4.146225
1.219706
Employment
3
506
35
832
4
43
324
195
4
18
8
17
51
109
28
32
15
6
9
6
22
328
303
11
36
1,048
3
3
2
43
2
211
59
101
82
77
799
1
16
13
1
11
24
10
73
216
285
196
11
26
12
Employment
Multiplier
1.928
2.868
1.957
1.405
1.864
1.709
1.567
1.634
1.494
1.408
2.766
2.916
1.833
1.722
2.033
3.566
2.094
2.686
2.003
3.224
3.201
1.656
1.949
1.200
1.752
1.948
2.962
1.726
1.420
1.820
1.733
1.859
1.576
2.845
2.156
1.624
2.647
1.755
1.788
1.818
2.069
1.458
1.651
1.921
1.929
1.681
1.808
1.823
1.671
1.935
1.782
Industry Sector
293
294
295
296
298
303
304
305
306
309
310
311
312
315
321
327
329
330
332
333
335
338
344
351
352
353
354
359
368
370
378
384
385
386
387
397
399
402
403
404
406
408
411
412
413
415
418
419
429
432
433
46
Crowns and Closures
Metal Stampings, N.E.C.
Plating and Polishing
Metal Coating and Allied Services
Ammunition, Except For Small Arms
Pipe, Valves, and Pipe Fittings
Miscellaneous Fabricated Wire Produc
Metal Foil and Leaf
Fabricated Metal Products, N.E.C.
Farm Machinery and Equipment
Lawn and Garden Equipment
Construction Machinery and Equipment
Mining Machinery, Except Oil Field
Conveyors and Conveying Equipment
Special Dies and Tools and Accessories
Woodworking Machinery
Printing Trades Machinery
Food Products Machinery
Pumps and Compressors
Ball and Roller Bearings
Packaging Machinery
General Industrial Machinery, N.E.C
Typewriters and Office Machines N.E.C.
Fluid Power Cylinders & Actuators
Fluid Power Pumps & Motors
Scales and Balances
Industrial Machines N.E.C.
Relays & Industrial Controls
Wiring Devices
Radio and TV Receiving Sets
Electronic Components, N.E.C.
Motor Vehicles
Truck and Bus Bodies
Motor Vehicle Parts and Accessories
Truck Trailers
Travel Trailers and Camper
Transportation Equipment, N.E.C
Automatic Temperature Controls
Mechanical Measuring Devices
Instruments To Measure Electricity
Optical Instruments & Lenses
Surgical Appliances and Supplies
Electromedical Apparatus
Ophthalmic Goods
Photographic Equipment and Supplies
Jewelry, Precious Metal
Musical Instruments
Dolls
Signs and Advertising Displays
Manufacturing Industries, N.E.C.
Railroads and Related Services
Industry
Output
5.182477
13.497684
0.230113
1.407807
20.549025
2.359795
2.137042
1.055866
5.625167
17.513729
1.360568
10.317909
0.756613
1.327519
3.502331
5.726479
5.373186
7.855542
2.803976
1.479456
32.698841
6.944836
0.257047
24.156273
1.739345
12.601504
28.813686
18.231514
0.710192
11.901639
12.661002
25.13764
0.668855
5.840059
6.727959
4.788054
1.349433
1.249925
2.805202
3.070504
3.279934
0.258628
0.942716
11.082405
1.001137
0.84049
0.112615
1.277579
3.671766
3.731316
0.176166
Employment
34
106
5
12
218
21
23
1
39
104
6
51
6
11
64
51
45
72
15
13
207
57
3
175
30
118
325
127
8
76
70
46
5
32
47
42
7
30
30
30
30
2
5
146
5
12
4
40
40
36
1
Employment
Multiplier
2.040
1.890
1.376
1.661
1.663
1.815
1.631
6.953
1.931
2.161
2.251
2.182
1.891
1.890
1.478
1.757
1.825
1.799
2.162
1.802
1.981
1.764
1.509
2.054
1.580
1.705
1.674
2.177
1.647
2.001
2.030
3.510
1.665
2.076
1.971
1.659
1.987
1.350
1.675
1.736
1.895
1.824
2.162
1.644
1.962
1.474
1.189
1.356
1.717
1.766
2.744
Industry Sector
434
435
436
437
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
47
Local, Interurban Passenger Transit
Motor Freight Transport and Warehouse
Water Transportation
Air Transportation
Arrangement Of Passenger Transportation
Transportation Services
Communications, Except Radio and TV
Radio and TV Broadcasting
Electric Services
Gas Production and Distribution
Water Supply and Sewerage Systems
Sanitary Services and Steam Supply
Wholesale Trade
Building Materials & Gardening
General Merchandise Stores
Food Stores
Automotive Dealers & Service Station
Apparel & Accessory Stores
Furniture & Home Furnishings Stores
Eating & Drinking
Miscellaneous Retail
Banking
Credit Agencies
Security and Commodity Brokers
Insurance Carriers
Insurance Agents and Brokers
Owner-occupied Dwellings
Real Estate
Hotels and Lodging Places
Laundry, Cleaning and Shoe Repair
Portrait and Photographic Studios
Beauty and Barber Shops
Funeral Service and Crematories
Miscellaneous Personal Services
Advertising
Other Business Services
Photofinishing, Commercial Photography
Services To Buildings
Equipment Rental and Leasing
Personnel Supply Services
Computer and Data Processing Service
Detective and Protective Services
Automobile Rental and Leasing
Automobile Parking and Car Wash
Automobile Repair and Services
Electrical Repair Service
Watch, Clock, Jewelry and Furniture
Miscellaneous Repair Shops
Motion Pictures
Theatrical Producers, Bands Etc.
Bowling Alleys and Pool Halls
Industry
Output
33.99332
313.326172
5.922822
13.893867
5.829714
11.417836
180.412231
45.619919
9.911799
97.827888
3.85237
36.724644
657.078308
68.987778
135.734406
203.811417
208.347534
37.577389
67.903847
321.991791
182.003159
286.149536
33.257057
60.656693
151.684845
44.404835
599.817078
600.56134
35.450863
45.057438
10.731078
30.804808
17.319895
24.819536
4.430138
52.659729
7.63824
24.929836
40.70686
26.628021
9.218854
14.138936
7.709532
23.764442
121.554192
19.092764
2.410721
76.148186
20.900852
7.552763
11.206158
Employment
Employment
Multiplier
811
3,689
32
110
152
152
875
346
26
187
24
215
7,266
1,392
4,216
4,540
3,270
1,115
1,443
9,326
6,114
2,019
1,194
448
1,261
1,153
1.445
2.093
2.470
2.171
1.410
1.753
2.514
2.201
3.257
2.898
2.877
2.646
1.885
1.436
1.271
1.389
1.576
1.278
1.410
1.316
1.257
2.294
1.475
2.317
2.693
1.370
3,670
814
1,478
360
1,594
432
516
147
1,047
159
791
460
1,287
105
808
74
447
1,538
272
40
1,060
247
110
281
1.918
1.469
1.373
1.365
1.179
1.312
1.606
1.267
1.381
1.470
1.329
1.705
1.230
1.712
1.228
2.113
1.605
1.692
1.369
1.434
1.508
1.775
1.873
1.476
Industry Sector
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
519
520
522
523
525
528
Employment
Commercial Sports Except Racing
Racing and Track Operation
Amusement and Recreation Services, N.E.C.
Membership Sports and Recreation Clubs
Doctors and Dentists
Nursing and Protective Care
Hospitals
Other Medical and Health Services
Legal Services
Elementary and Secondary Schools
Colleges, Universities, Schools
Other Educational Services
Job Trainings & Related Services
Child Day Care Services
Social Services, N.E.C.
Residential Care
Other Nonprofit Organizations
Business Associations
Labor and Civic Organizations
Religious Organizations
Engineering, Architectural Services
Accounting, Auditing and Bookkeeping
Management and Consulting Services
Research, Development & Testing Services
Local Government Passenger Transit
State and Local Electric Utilities
Other State and Local Govt Enterprise
U.S. Postal Service
Federal Government - Military
Federal Government - Non-Military
State & Local Government - Education
State & Local Government - Non-Education
Domestic Services
Inventory Valuation Adjustment
0.969015
0.797489
33.201717
17.517344
487.88678
67.940956
385.026764
99.329872
80.979477
13.774079
3.125996
15.537225
15.289513
14.18848
27.924389
15.945305
3.982046
25.283831
35.899178
21.60648
35.124371
63.208862
39.949463
29.830555
2.263046
175.824066
67.619545
43.502319
7.142108
20.40674
348.967987
304.509491
11.840626
-15.437882
46
45
1,121
640
5,705
2,208
6,554
1,618
1,141
364
91
431
449
435
922
649
101
322
911
778
520
1,122
548
690
18
586
315
610
916
438
11,735
8,772
1,440
Total:
14,974.84
178,117
Industry Output is in millions of dollars.
48
Industry
Output
Employment
Multiplier
1.219
1.099
1.301
1.310
1.832
1.339
1.567
1.519
1.697
1.469
1.378
1.374
1.380
1.275
1.343
1.266
1.408
1.718
1.414
1.315
1.815
1.623
1.740
1.481
2.934
3.115
3.171
1.906
1.089
1.534
1.341
1.398
1.094
IMPLAN industry sectors not in Stanislaus County.
15
25
29
30
32
35
39
40
42
43
44
45
46
47
61
66
69
72
73
74
75
80
81
82
84
86
87
91
92
94
97
98
99
101
102
104
105
106
107
109
110
111
112
113
114
115
116
117
118
119
120
121
123
126
127
49
Tobacco
Commercial Fishing
Copper Ores
Lead and Zinc Ores
Silver Ores
Uranium-radium-vanadium Ores
Natural Gas Liquids
Dimension Stone
Clay, Ceramic, Refractory Minerals, N.E.C.
Potash, Soda, and Borate Minerals
Phosphate Rock
Chemical, Fertilizer Mineral Mininig, N.E.C.
Nonmetallic Minerals (Except Fuels) Service
Misc. Nonmetallic Minerals, N.E.C.
Creamery Butter
Canned Specialties
Pickles, Sauces, and Salad Dressings
Flour and Other Grain Mill Products
Cereal Preparations
Rice Milling
Blended and Prepared Flour
Cookies and Crackers
Sugar
Confectionery Products
Chewing Gum
Cottonseed Oil Mills
Soybean Oil Mills
Malt Beverages
Malt
Distilled Liquor, Except Brandy
Canned and Cured Sea Foods
Prepared Fresh Or Frozen Fish Or Seafood
Roasted Coffee
Manufactured Ice
Macaroni and Spaghetti
Cigarettes
Cigars
Chewing and Smoking Tobacco
Tobacco Stemming and Redrying
Narrow Fabric Mills
Womens Hosiery, Except Socks
Hosiery, N.E.C
Knit Outerwear Mills
Knit Underwear Mills
Knit Fabric Mills
Knitting Mills, N.E.C.
Yarn Mills and Finishing Of Textiles, N.E.C.
Carpets and Rugs
Thread Mills
Coated Fabrics, Not Rubberized
Tire Cord and Fabric
Nonwoven Fabrics
Textile Goods, N.E.C
Housefurnishings, N.E.C
Textile Bags
129
131
132
133
134
135
139
150
152
153
154
155
159
160
161
162
163
165
166
168
169
171
172
176
177
181
183
184
185
187
188
189
192
193
194
196
198
199
201
206
207
208
209
212
213
214
215
216
217
219
221
222
223
224
225
Pleating and Stitching
Schiffi Machine Embroideries
Fabricated Textile Products, N.E.C.
Logging Camps and Logging Contractors
Sawmills and Planing Mills, General
Hardwood Dimension and Flooring Mills
Veneer and Plywood
Metal Household Furniture
Wood Tv and Radio Cabinets
Household Furniture, N.E.C
Wood Office Furniture
Metal Office Furniture
Blinds, Shades, and Drapery Hardware
Furniture and Fixtures, N.E.C
Pulp Mills
Paper Mills, Except Building Paper
Paperboard Mills
Paper Coated & Laminated Packaging
Paper Coated & Laminated N.E.C.
Bags, Paper
Die-cut Paper and Board
Envelopes
Stationery Products
Book Publishing
Book Printing
Greeting Card Publishing
Bookbinding & Related
Typesetting
Plate Making
Industrial Gases
Inorganic Pigments
Inorganic Chemicals Nec.
Synthetic Rubber
Cellulosic Man-made Fibers
Organic Fibers, Noncellulosic
Soap and Other Detergents
Surface Active Agents
Toilet Preparations
Gum and Wood Chemicals
Explosives
Printing Ink
Carbon Black
Chemical Preparations, N.E.C
Asphalt Felts and Coatings
Lubricating Oils and Greases
Petroleum and Coal Products, N.E.C.
Tires and Inner Tubes
Rubber and Plastics Footwear
Rubber and Plastics Hose and Belting
Fabricated Rubber Products, N.E.C.
Leather Tanning and Finishing
Footwear Cut Stock
House Slippers
Shoes, Except Rubber
Leather Gloves and Mittens
226
227
228
233
235
236
237
238
239
240
245
246
248
249
250
251
252
253
255
256
257
258
259
260
261
262
263
264
266
267
269
270
271
272
274
288
290
291
292
297
299
300
301
302
307
308
313
314
316
317
318
319
320
322
323
324
325
326
50
Luggage
Womens Handbags and Purses
Personal Leather Goods
Brick and Structural Clay Tile
Clay Refractories
Structural Clay Products, N.E.C
Vitreous Plumbing Fixtures
Vitreous China Food Utensils
Fine Earthenware Food Utensils
Porcelain Electrical Supplies
Lime
Gypsum Products
Abrasive Products
Asbestos Products
Minerals, Ground Or Treated
Mineral Wool
Nonclay Refractories
Nonmetallic Mineral Products, N.E.C.
Electrometallurgical Products
Steel Wire and Related Products
Cold Finishing Of Steel Shapes
Steel Pipe and Tubes
Iron and Steel Foundries
Primary Copper
Primary Aluminum
Primary Nonferrous Metals, N.E.C.
Secondary Nonferrous Metals
Copper Rolling and Drawing
Nonferrous Rolling and Drawing, N.E.C.
Nonferrous Wire Drawing and Insulating
Brass, Bronze, and Copper Foundries
Nonferrous Castings, N.E.C.
Metal Heat Treating
Primary Metal Products, N.E.C
Metal Barrels, Drums and Pails
Miscellaneous Metal Work
Iron and Steel Forgings
Nonferrous Forgings
Automotive Stampings
Small Arms Ammunition
Small Arms
Other Ordnance and Accessories
Industrial and Fluid Valves
Steel Springs, Except Wire
Steam Engines and Turbines
Internal Combustion Engines, N.E.C.
Oil Field Machinery
Elevators and Moving Stairways
Hoists, Cranes, and Monorails
Industrial Trucks and Tractors
Machine Tools, Metal Cutting Types
Machine Tools, Metal Forming Types
Industrial Patterns
Power Driven Hand Tools
Rolling Mill Machinery
Welding Apparatus
Metalworking Machinery, N.E.C.
Textile Machinery
328
331
334
336
337
339
340
341
342
343
345
346
347
348
349
350
355
356
357
358
360
361
362
363
364
365
366
367
369
371
372
373
374
375
376
377
379
380
381
382
383
388
389
390
391
392
393
394
395
396
398
400
401
405
407
409
410
414
Paper Industries Machinery
Special Industry Machinery N.E.C.
Blowers and Fans
Power Transmission Equipment
Industrial Furnaces and Ovens
Electronic Computers
Computer Storage Devices
Computer Terminals
Computer Peripheral Equipment,
Calculating and Accounting Machines
Automatic Merchandising Machine
Commercial Laundry Equipment
Refrigeration and Heating Equipment
Measuring and Dispensing Pumps
Service Industry Machines, N.E.C.
Carburetors, Pistons, Rings, Valves
Transformers
Switchgear and Switchboard Apparatus
Motors and Generators
Carbon and Graphite Products
Electrical Industrial Apparatus, N.E.C.
Household Cooking Equipment
Household Refrigerators and Freezers
Household Laundry Equipment
Electric Housewares and Fans
Household Vacuum Cleaners
Household Appliances, N.E.C.
Electric Lamps
Lighting Fixtures and Equipment
Phonograph Records and Tape
Telephone and Telegraph Apparatus
Radio and Tv Communication Equipment
Communications Equipment N.E.C.
Electron Tubes
Printed Circuit Boards
Semiconductors and Related Devices
Storage Batteries
Primary Batteries, Dry and Wet
Engine Electrical Equipment
Magnetic & Optical Recording Media
Electrical Equipment, N.E.C.
Motor Homes
Aircraft
Aircraft and Missile Engines and Parts
Aircraft and Missile Equipment,
Ship Building and Repairing
Boat Building and Repairing
Railroad Equipment
Motorcycles, Bicycles, and Parts
Complete Guided Missiles
Tanks and Tank Components
Search & Navigation Equipment
Laboratory Apparatus & Furniture
Analytical Instruments
Surgical and Medical Instrument
Dental Equipment and Supplies
X-Ray Apparatus
Watches, Clocks, and Parts
416
417
420
421
422
423
424
425
426
51
Silverware and Plated Ware
Jewelers Materials and Lapidary Work
Games, Toys, and Childrens Vehicles
Sporting and Athletic Goods, N.E.C.
Pens and Mechanical Pencils
Lead Pencils and Art Goods
Marking Devices
Carbon Paper and Inked Ribbons
Costume Jewelery
427
428
430
431
438
514
515
Fasteners, Buttons, Needles, Pins
Brooms and Brushes
Burial Caskets and Vaults
Hard Surface Floor Coverings
Pipe Lines, Except Natural Gas
Federal Electric Utilities
Other Federal Government Enterprises
Appendix C: Industry Sectors in 65 Industry Model
Table 1c: Industry Sectors
Industry
1 Farms
24 Forestry Products
25 Commercial Fishing
26 Ag Services
28 Metal mining
37 Coal Mining
38 Oil mining
40 Non-metal mining
48 Construction
58 Food processing
104 Tobacco mfg
108 Textiles
124 Apparel
133 Wood products
148 Furniture
161 Pulp and paper
174 Printing and publishing
186 Chemicals and allied
210 Petroleum products
215 Rubber products
221 Leather products
230 Stone, glass and clay
254 Primary metals
273 Fabricated metal
307 Industrial machinery
383 Electrical equipment
384 Transportation equipment
400 Scientific instruments
415 Miscellaneous mfg
433 Railroads and Related Services
434 Local, Interurban Passenger Transit
435 Motor Freight Transport and Warehousing
436 Water Transportation
437 Air Transportation
438 Pipe Lines, Except Natural Gas
439 Transportation Services
441 Communications
443 Utilities
447 Wholesale Trade
448 Retail Trade
456 Banking
52
Total Industry
Output*
1,510.57
3.455844
0
137.925873
3.473535
0.647143
3.632936
3.770192
1,072.96
2,977.41
0
2.062743
0.945428
77.298317
24.785242
412.225189
108.712578
61.256973
14.529907
74.31076
0.329603
170.225845
54.435944
418.599243
165.228836
43.504349
44.512001
23.690451
9.633766
0.176166
33.99332
313.326172
5.922822
13.893867
0
17.247551
226.03215
148.316696
657.078308
1,226.36
286.149536
Employment
11,771
14
0
7,201
16
6
36
29
12,754
13,915
0
26
14
934
296
1,342
1,402
293
28
631
11
1,407
260
2,153
1,353
281
179
278
132
1
811
3,689
32
110
0
304
1,221
452
7,266
31,416
2,019
Industry
457 Credit Agencies
458 Security and Commodity Brokers
459 Insurance Carriers
460 Insurance Agents and Brokers
461 Real estate
463 Hotels and Lodging Places
464 Personal services
469 Business services
477 Automotive services
480 Repair services
483 Motion Pictures
484 Recreation services
490 Health services
494 Legal Services
495 Education services
498 Social services
502 Non-profit organizations
506 Professional services
510 State & local non-ed government
516 Special sectors
519 Federal Government - Military
520 Federal non-military
522 State & Local Government - Education
525 Domestic Services
Total:
*Millions of Dollars
53
Total Industry
Output*
33.257057
60.656693
151.684845
44.404835
1,200.38
35.450863
128.732758
180.350616
153.028168
97.651672
20.900852
71.244484
1,040.18
80.979477
32.437302
73.347687
86.77153
168.113251
550.216125
-15.437882
7.142108
63.909058
348.967987
11.840626
14,974.84
Employment
1,194
448
1,261
1,153
3,670
814
4,380
4,804
2,059
1,372
247
2,243
16,085
1,141
886
2,455
2,112
2,880
9,691
0
916
1,048
11,735
1,440
178,117