Economic Impact of the Dairy Industry in Erath County

S. Hussain Ali Jafri, David Buland, and Stacie Randals

Department of Business Systems

Tarleton State University

Stephenville, Texas

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

Paper presented at the annual meeting of the Southwestern Social
Sciences Association, San Antonio, Texas. April 2003

Printed 11/13/2023 6:13 PM

***[Table of Contents]{.underline}***

Summary [4](#summary)

Economic Impact of the Dairy Industry in Erath County
[5](#economic-impact-of-the-dairy-industry-in-erath-county)

Introduction [5](#introduction)

Review of literature: [6](#review-of-literature)

Conceptual Model [7](#conceptual-model)

Data [8](#data)

Methodology: [9](#methodology)

Basic Terms [10](#basic-terms)

Preparing Data for IMPLAN Analysis:
[11](#preparing-data-for-implan-analysis)

Calculations of the Regional Purchase Coefficients and Expenditures:
[11](#calculations-of-the-regional-purchase-coefficients-and-expenditures)

Wages [16](#wages)

Owner's Draw [16](#owners-draw)

Capital Expenses [16](#capital-expenses)

Texas Model [17](#texas-model)

Results and Discussion [17](#results-and-discussion)

Economic Impact at the County Level:
[17](#economic-impact-at-the-county-level)

Employment Impact [19](#employment-impact)

Value-Added [19](#value-added)

Economic Impact at the State level
[22](#economic-impact-at-the-state-level)

Employment Impact at the State Level
[23](#employment-impact-at-the-state-level)

Sensitivity Analysis Modeling [25](#sensitivity-analysis-modeling)

For a \$1 increase/decrease in milk price, what will the impact be on
output, value added, and employment?
[27](#for-a-1-increasedecrease-in-milk-price-what-will-the-impact-be-on-output-value-added-and-employment)

Summary and Conclusions [29](#summary-and-conclusions)

Appendixes [30](#appendixes)

Appendix A, Output and Job Creation Tables
[30](#appendix-a-output-and-job-creation-tables)

References [31](#references)

Table of Figures

Table 1: Total Plant Demand for the Major Metro Areas Supplied by Erath
County in 2000
[5](#table-1-total-plant-demand-for-the-major-metro-areas-supplied-by-erath-county-in-2000)

Figure 1: Conceptual Model [7](#figure-1-conceptual-model)

Table 2: Number of cows in Erath County
[9](#table-2-number-of-cows-in-erath-county)

Table 3: Erath County's Dairy Industry Production Function
[13](#table-3-erath-countys-dairy-industry-production-function)

Table 4: Dairy Expenses from Survey
[14](#table-4-dairy-expenses-from-survey)

Table 5: Adjusted Survey RPCs for IMPLAN Calculations
[15](#__RefHeading___Toc37609809)

Table 6: Margin Adjustments [15](#table-6-margin-adjustments)

Table 7: Estimated Capital Expenses
[16](#table-7-estimated-capital-expenses)

Table 8: Output Creation in Erath County
[19](#table-8-output-creation-in-erath-county)

Table 9: Job-Creation in Erath County
[19](#table-9-job-creation-in-erath-county)

Table 10: Selected Industries in Erath County Impacted by the Dairy
Industry
[20](#table-10-selected-industries-in-erath-county-impacted-by-the-dairy-industry)

Table 11: Employment in Erath County Impacted by the Dairy Industry
[21](#table-11-employment-in-erath-county-impacted-by-the-dairy-industry)

Table 12: Output Creation in the State of Texas
[23](#table-12-output-creation-in-the-state-of-texas)

Table 13: Job-Creation in the State of Texas
[23](#table-13-job-creation-in-the-state-of-texas)

Table 14: Year 2000 Summary Dairy Impacts
[24](#table-14-year-2000-summary-dairy-impacts)

Table 15: Economic Impact of the loss of a 1,000 Cow Operation
[25](#table-15-economic-impact-of-the-loss-of-a-1000-cow-operation)

Table 16: Impacts of Erath County Employment per cow
[27](#table-16-impacts-of-erath-county-employment-per-cow)

Table 17: Impact of a change in price of Milk of \$1.00
[28](#table-17-impact-of-a-change-in-price-of-milk-of-1.00)

Output Creation in Erath County [30](#output-creation-in-erath-county)

Output (Sales) Creation in Texas [30](#output-sales-creation-in-texas)

Job-Creation in Texas [30](#job-creation-in-texas)

Economic Impact of the Dairy Industry

# Summary

Erath County has the highest milk production of any county in Texas.
Erath is the Center of the Cross Timbers dairy region. This single
county accounts for 27% of all milk production within the state.
Revenues from milk production within the county represent 79% of total
agricultural income in 2001. Milk sales for 2000 were estimated to be
close to \$200 million and the total income earned by dairy producers
from all sources was estimated at \$222 million. What impact does the
dairy industry have on the local economy and on the state of Texas? How
many new jobs are created, and how much new income and wages in the area
are added by the presence of the dairy industry in the region? These
questions are important and timely in light of the negative publicity
associated with the environmental issues connected with the dairy
industry.

This study used surveys from forty dairy producers including 47% of
total county production in the year 2000. The data revealed estimates of
detailed farm and non-farm sources of income as well as operating and
capital expenses. The data collected also included proportion of inputs
purchased by producers in the county, and within the state to adjust for
"leakages" at the respective levels. A leakage identifies the portion of
expenditures that leaves an impact area and has no further effect within
an area. The expense data was also cross-examined against production
figures by examining the input-output structure of the local economy.
The adjusted direct expenditures were then processed through a standard
input-output model, IMPLAN, to calculate the re-spending or multiplier
effects.

The overall output multiplier was 1.32. This is a smaller multiplier
compared to those obtained in similar studies for this region and in
other parts of the country. In dollar terms, the dairy industry had an
**economic impact of \$543 million**, representing **36% of the total
output** of the county. The Dairy industry provides 1980 jobs and
supports an additional 3,932 non-dairy jobs for a total of **5,912
jobs** in the county, providing **31% of the county's employment**. The
total value-added (income) in the dairy industry amounts to \$123
million, accounting for **18% of the total personal income** of the
county. The dairy producers paid over **\$900,000 in county taxes** and
an additional **\$9.4 million in taxes** were generated stemming from
all the direct and indirect effects connected with the presence of the
dairy industry in the county.

At the state level, the dairy industry contributes a total **of \$772
million in output** and provides (directly and indirectly) **10,926
jobs**. Once the impacts of Erath County are accounted for, the dairy
industry contributes to the rest of the state \$228 million in output
and creates an additional 5,014 jobs.

Milk production is shifting toward the larger, (\> 700 cows/farm)
production units. These farms represent 95% of production, and pose a
greater risk to the County if they leave. The county has **lost 59
dairies since 1996** and the number of cows has decreased by 3% in the
last four years. From our results, we have estimated that the exodus of
one 1000-cow dairy implies a total loss of \$5.6 million in output,
\$1.35 million in personal income, 61 dairy and dairy-related jobs and
\$113,328 in potential county taxes.

# Economic Impact of the Dairy Industry in Erath County

S. Hussain Ali Jafri, David Buland, and Stacie Randals

## Introduction

Erath County has the highest dairy production in Texas, accounting for
27% of the state's milk production. In 2001, within the county, milk
sales accounted for 79% of the total agricultural income. Overall Texas
milk production peaked in 1994 while Erath County milk production
continued to rise until peaking in 2000. Recent newspaper articles
suggest that dairy producers are leaving the county due to low and
inconsistent prices, uncertainties surrounding environmental
regulations, and the lure of more friendly business environments
elsewhere (Stephenville Empire Tribune). Most producers who are leaving
are believed to be moving to western counties of the state and in New
Mexico. New Mexico exceeded Texas in milk production in 2000. Five years
ago production in New Mexico was only 25% of the total milk output in
Texas (Milk Marketing Administrator).

The number of producers in Erath County has been declining steadily;
from 202 dairies in 1994 to 138 in 2001 (more recent data indicates that
only 113 producers are now left in the county -- Cross Timbers Business
Report). However, during this same period, production of milk increased,
both from increased productivity per cow and an increase in the number
of cows in the county. The combination of these factors has led to
larger dairies and a more concentrated industrial structure. If this
trend continues it may pose an economic risk to the county's well being,
as the impact of the large producers leaving will be greater compared to
the previous exit of small/marginal producers.

Dairy marketing is highly regulated by the Milk Marketing Association.
Local upward linkages are few. The bulk of the milk is shipped to
processing plants in the Dallas-Fort Worth, Houston, San Antonio, and
Austin metro areas (see table 1). One advantage for the Erath County
dairies is their relative closeness to these metro areas, relative to
the New Mexico or High Plains dairies. But that relative closeness is a
two-edge sword. In 1999, a large cheese plant in Stephenville that
utilized seasonally surplus milk temporarily closed. Since Erath County
milk is closer to the Texas processing plants, it is the New Mexico
dairies at the far end of the supply chain whose surplus milk is now
used for making cheese.

##### Table 1: Total Plant Demand for the Major Metro Areas Supplied by Erath County in 2000

  ------------------------------------------------- ---------------------
  Metro Area                                        Percent

  Dallas/Fort Worth                                 30%

  Houston/Brenham                                   46%

  San Antonio/Austin                                29%
  ------------------------------------------------- ---------------------

Source: Milk Marketing Administrator, Carrolton, Texas (personal
correspondence)

At the state level, a report by Max Sudweeks of Texas A& M University
summarizes the growth and change in the dairy industry. This report
provides a summary of the statewide industry and traces the historical
development of the dairy industry in Texas. The study notes Erath
County's transition to becoming the State's top-producing county in
1996. It reaffirms the trends taking place nationwide with the
increasing productivity of cows, decreasing number of farms, increasing
herd size, and fluctuating prices and profits in the dairy industry at
the state level (Sudweek).

##  Review of literature:

Using 1995 data from secondary sources, a study by Nielsen et.al
estimated the economic impact of Erath County's dairy industry. No
adjustments for local purchases of inputs were made explicitly and the
analysis relied primarily on the IMPLAN data set for the county's dairy
industry in estimating the impacts. The analysis was also restricted to
milk sales as sources of revenue without taking into account additional
sources of income for dairy producers such as the sales of calves,
heifers, crops, government payments and off-farm income. The Nielsen
et.al study reports an output multiplier of 1.44 and an employment
multiplier of 2.03. According to this report, Erath County dairies
produced \$185 million in milk sales in 1995, with an additional \$265
million in indirect and induced effects. The model results concluded
that the industry generated nearly \$49 million in personal income and
created 3,157 additional jobs, representing 22% of total income and 25%
of total jobs in the county.

At the regional level, a Texas A&M team led by Dr. Lonnie Jones et.al
researched the economic impact of the dairy industry in the Cross
Timbers Region of Texas (which includes Erath and surrounding counties).
This 1991 report covers most aspects of the then expanding dairy
industry, including production costs and returns, purchasing patterns,
and an economic impact analysis. Using an input-output, computer-based
model for the region (IMPLAN), the direct and secondary effects of the
dairy industry were estimated. For milk, the multiplier for total sales
was 1.52, and for employment 2.22. The multiplier for livestock sales
was higher with 1.85 for sales, 1.94 for income, and 3.8 for employment.
Using a three-year average of milk sales (1990-1992), the dairy industry
is estimated to account directly and indirectly for approximately \$337
million or one-fifth of region's sales and \$136 million or 18% of
personal income, while it employs 5,150 people or 16.5% of the regions
civilian labor force.

Two similar studies estimated the economic impact of the dairy industry
at the county level, one in Florida and the other in Arizona. In 1991,
David Mulkey and Rodney Clouser (Mulkey and Clouser) examined the
economic impact of the dairy industry in Okeechobee County, Florida.
Like Erath County in Texas, Florida's Okeechobee County dairy production
accounts for 85% of total farm sales in this county where agriculture
accounts for 18% of total employment and 16.6% of total income. One of
the main goals of this study (as with the others) was to estimate income
and employment reductions resulting from overall declining milk
production, often a result of stricter environmental laws.

Using sales of dairy products in Okeechobee County, Mulkey and Clouser
estimated the direct, indirect, and induced effects using multipliers
generated by the U.S. Department of Commerce's Regional Input-Output
Modeling Systems (RIMS). The output multiplier for the dairy sector was
estimated at 1.58, and each one million dollar in sales generated an
additional 15 full-time equivalent jobs in the county. The earnings
multiplier was 1.29, suggesting that every dollar of milk sales creates
an additional \$.29 of earnings for other sectors in the county. Besides
calculating the overall impacts, the reports also includes the impact on
the county in terms of lost output and jobs from the loss of a
hypothetical dairy farm with 1,000 cows. This paper provides a good
foundation for assessing the economic impacts (costs and benefits) of
regulations that may ultimately displace economic activity in a region.

In 1998, a USDA/NRCS study by Ronald Hemmer examined the impact of
environmental changes in Maricopa County, Arizona. He analyzed the loss
of a 1,000 dairy operation in terms of costs and benefits to Maricopa
County. Using the IMPLAN model, the study estimates short-run losses to
the county in terms of lost output, earnings and employment from the
loss of a 1,000 dairy operation. The strength of this study lies in its
attempt to model the local dairy industry by using farm enterprise
budgets and in estimating the variable and fixed costs of a dairy
operation. Unlike previous studies, Hemmer also attempted to estimate
both the short-and long-run impacts of a dairy operation in a defined
region. Using selected discount rates, the study projects the costs to a
community (in present-value terms) resulting from the loss of a 1,000
dairy-head operation. This analysis was used in a Natural Resource
Conservation Service (NRCS) Small Watershed Project to justify technical
and financial assistance of environmental and conservation practices for
the affected dairy farms.

From this brief review of literature, we note that impact studies are
becoming more common. Typically, the economic impact will be higher when
the impact region is bigger and more inputs are bought locally (greater
backward linkages involved in input-output relationships). The next
section outlines the study's conceptual model and includes the
definitions used for describing the sectors and relationships in the
study.

## Conceptual Model

This study's basic framework is built around a conceptual model (see
Figure 1) that isolates the dairy industry and the local economy into
two separate entities. The dairy industry include annual revenues from
total milk sales and the corresponding expenses for producing milk,
revenue from the sale of calves, bulls, and heifers, average capital
expenditures, and other farm income such as custom-work, government
payments, etc. The "local" economy is represented by the economic
structure of Erath County at the regional level and the state of Texas
at the state level. The dairy industry's interactions and backward
linkages will be identified to estimate the output and employment that
can be associated with the presence of the dairy industry.

##### Figure 1: Conceptual Model

III\. Data:

We should also emphasize that this study, as most other economic impact
studies, makes no attempt to estimate the negative externalities and
their associated costs to the county/region such as pollution, road
conditions, tax-burden, etc. The scope of this study precludes the
inclusion of these factors that could be treated in a future project.

##  Data

Estimating an economic impact of an industry requires data on income,
expenses, source of inputs purchased, capital improvements, and taxes
paid. As noted earlier, the previous study (Neilsen et.al) which
estimated the economic impact of Erath County's dairy industry relied
heavily on the production function estimated by IMPLAN. This study uses
primary data through a survey instrument. The objective of this exercise
is to improve and calibrate IMPLAN's production function to conform
better to local conditions. The income category in the survey includes
questions not only on revenues received by producers from the sale of
milk, but also from additional sources such as the sales of heifers,
cattle, and government payments received. The expense categories
included questions on the actual expenses that producers on inputs and
the percentage of them bought from local sources, other counties within
Texas, and from out-of-state. Besides operating expenses for the year
2000, the survey sought information on capital expenses such as expenses
for building silos, lagoons, farm structures, and for buying farm
vehicles and equipment. As individual producers are unlikely to incur
all these expenses in a given year, producers were asked to provide
these data for the last five years. An annual average of these
expenditures was computed from the data provided (see Table 3).

Surveys were sent to all dairy producers in the county with from the
local extension agent. Out of almost 140 surveys mailed, 40 usable
surveys were returned. These forty producers accounted for 47% of total
production in 2000; owned 33% of the total cows in the county, and
represented almost 30% of all the existing producers in the county. Two
local accounting firms also made available summary reports of their
dairy clients that included estimated enterprise budgets for them. The
IMPLAN datasets include the US Bureau of Economic Analysis economic data
that approximates production functions at the county level. Once the
production function was developed at the county level, the same function
was also utilized to measure the impacts at the state level, with
appropriate adjustments for expenses or inputs purchased at the state
level. The alternative was to use the Texas production function provided
by IMPLAN. Since this study focuses on the county's dairy industry at
the state level, using Erath County production function (with
appropriate adjustments) is a more accurate choice.

At the time the study was initiated, the county's 1998 IMPLAN dataset
was the most current available. This dataset was used for the dairy
industry, adjusted to 2000 figures from the survey data. For the state,
1997 Texas IMPLAN model was used and later updated to the 1999 Texas
model when the more recent version was made available.

The Milk Marketing Administrator (Carrolton, Texas) provides the best
county-level source of monthly and annual production. However, their
price data was less reliable, particularly with a reporting area change
in mid-2000 affecting Erath County (Milk Marketing Administrator). The
National Agricultural Statistical Service (NASS) price data was
reliable, but was available only at roughly five year intervals between
1949 with the latest survey in 1997 (NASS). NASS produces annual
county-level estimates of milk production in their dairy section, and
annual county-level estimates of milk cow numbers in the cattle section
of their on-line database. Their county-level annual figures were not as
accurate as the Milk Marketing Agency's due to a much smaller NASS
survey size. Therefore, NASS figures were used from 1970 to 2002 in the
report. For illustrative purposes, a partial table was replicated from
NASS.

NASS also produces state-level average monthly and annual estimates of
milk prices paid to producers. Erath county's prices are assumed to be
close to the state average because the county is both centrally located
within Texas and is the state's largest producer. Our study uses the
NASS Texas average annual prices. The Milk Marketing Administrator has
better county-level production numbers than does the NASS survey.
Combining the Milk Marketing Administrator's estimate of production of
1,502,226,552 lbs. multiplied by the NASS Texas average price of
\$13.30/cwt. gave a total of \$199,796,131 for milk sales in the year
2000.

##### Table 2: Number of cows in Erath County

  ------------- ------------------ ------------------- -------------------
  Year          All Cattle         Beef Cows           Milk Cows

                Head               Head                Head

  1994          185000             35000               76800

  1995          211000             38000               82700

  1996          217000             22000               90400

  1997          219000             20000               93300

  1998          189000             35000               79000

  1999          192000             27000               86100

  2000          189000             17000               91400

  2001          182000             19000               90600

  2002          194000             16000               82300
  ------------- ------------------ ------------------- -------------------

## Methodology: 

The major portion of the economic impact analysis was performed using
the IMPLAN input/output model. The theoretical basis for the model comes
from work done by Wassily Leontief, for which he won a Nobel Prize.
Leontief completed input/output studies of the U.S. economy for 1919,
1929, and 1939. Since that time, use of the input/output model has
spread.

The model contains these basic components: the flow-table, direct
coefficients, and indirect coefficients, and induced coefficients. Two
fundamental assumptions are associated with the model. First, the direct
coefficients are fixed. Fixed coefficients require the assumption of
static technology. This assumption means the coefficients must be
periodically adjusted to better represent the real world. Second, there
are no errors of aggregation. The output multiplier and the employment
multiplier are important derivations from the model.

IMPLAN and other input/output models attempt to estimate the large
economic impacts of policies that occur through forward and backward
linkages in the economy. Backward linkages are purchased inputs,
supplies, and services. Forward linkages include further value-added
economic activities, such as preparation and processing. By going beyond
measuring only direct impacts, these models give more complete pictures
of the economic effects of policy options.

IMPLAN is basically a general accounting system of the transactions
taking place in an economy between industries, businesses, and
consumers. Purchases and sales are adjusted for in-state versus
out-of-state, or in-region versus out-of-region sources, and are then
summed to arrive at estimates of total impacts arising from an initial
policy change. The IMPLAN model estimates impacts on total output
(sales), personal income, value-added, taxes, and employment.

IMPLAN's data sets are derived from several sources which include
national, state and local data from the Bureau of Economic Analysis's
Regional Economic Information (RIES), Bureau of Labor Statistics, Bureau
of Economic Analysis's Benchmark Input-Output Study, and County Business
Patterns. The primary data source for the Agricultural Sector is the
National Agricultural Statistical Service (NASS), Census of Agriculture
and from the Department of Agriculture in the 50 states. Further details
of data sources and methods could be found in the IMPLAN User's Guide
(IMPLAN).

All impacts were calculated on the 1998 Erath County model constructed
with all SAM sectors included, except Federal Defense Spending (no
apparent relationship was seen between the local dairy industry and the
local defense industry). Since there are no large towns within 60 miles
of Stephenville, the county seat (Fort Worth is 65 miles away), Erath
County provides an ideal economic impact area, containing most basic
services within the area and being generally isolated from outside
markets. However, Erath County is small (population of 30,815) and
contains only 128 of the 528 industrial sectors in the IMPLAN model.
With so many missing sectors, economic multiplier effects are obviously
smaller than larger economic areas, such as the entire state of Texas.
Before the results are presented, it could be prudent to define the
basic terms that will be utilized to explain the findings.

### Basic Terms

**Direct Effects** -- The initial immediate effects caused by a specific
activity; for example, the initial investment in the construction of a
new lagoon or the effects of the purchase of feed or medicines and the
hiring of local labor, etc. The direct effect, or impact, will
subsequently initiate a series of iterative rounds of income creation,
spending, and re-spending that will result in indirect effects and
induced effects.

**Indirect Effects --** The effects that result from the actions of the
processing sectors to produce the *direct effects.* Therefore, the
*indirect effects* are those changes to production, employment, incomes,
etc., which take place as a result of the direct effects and include the
effects on industry sectors that may be directly or indirectly related
to the initially impacted sector.

**Induced Effects** **--** The effects of household spending in the
regional economy are the result of *direct* and *indirect effects* of
some economic activity. The induced effects arise from a general change
in the household sector's earnings and spending patterns economic
changes due to direct and indirect effects. Further I-O development has
allowed a flexible number of sectors including state, local, and federal
spending and corporations to be added to this model. Social accounting
matrices (SAM) reports include all commodity flows, not only purchases
and production of sales commodities, but transfer payments to and from
institutions. Since the biggest additional sectors are normally
household spending, these SAM effects are still routinely called induced
effects.

These three component effects---direct, indirect, and induced (SAM)
effects---constitute the **total** effects resulting from the initial,
direct effect.

**Leakages** -- are those expenditures that "leak" out of the county and
cannot be included in estimating the economic impact at the local level.
For example, if producers purchase feed from the local feed-store, then
the profits and subsequently employment stays within the region. However
when the same producer "imports" feed from outside the region, the
economic effects are felt in the region from which the feed is imported,
and the positive gains cannot be locally captured. Appropriate
adjustments will have to be made to properly estimate the effects at the
local level.

**Multiplier** -- A numeric measurement-expressed as a mathematical
ratio-of the total effects (including the direct, indirect, and induced
effects) to the direct effects of a specific activity, or a change in
some activity. For example, a multiplier of 1.33 indicates that for
every dollar spent (direct expenditure) an additional \$0.33 (indirect)
is generated within the economy.

### Preparing Data for IMPLAN Analysis:

Table 3 provides the totals for each income and expense category. As
noted earlier, the survey sample accounted for 47% of total county milk
production. To estimate total income and expenses for the county, total
income and expenses (for the survey respondents) are multiplied by (1 /
0.47) = 2.1276.

The variation of milk sales per cow by farm was questioned so a quick
regression analysis was run. The forty farms in the sample average
\$3,202 dollars of monthly milk sales per cow in 2000, with a standard
deviation of only \$74. Just knowing the number of cows on the farm
explains 95% of the variation in total milk sales. One small farm sold
only \$1,490 annually per cow; the next lowest producer sold about
\$2,000 per cow. The highest sales per cow were \$4,082 annually.
Besides the management productivity per cow, some variation is due to
increasing or decreasing the herd count through the year and to milk
price fluctuations through the year 2000.

Actual milk production per year for each farm was an important variable
which was not included in the survey. The survey's failure to ask this
question may explain much of the variation in income.

### Calculations of the Regional Purchase Coefficients and Expenditures:

The Regional Purchase Coefficients (RPC) are the percent of income and
expenses purchased/spent by producers in Erath County and in Texas. This
data was collected from the survey respondents. Dairy farm expenditures
and RPCs primarily from the survey data were calculated, with
adjustments, from the original Erath County IMPLAN data (see Table 4).

The owner's draw, taxes, health, other benefits, and labor expenses were
excluded from these operating expense calculations, and are treated
separately later. We combined several of the survey categories to better
match the IMPLAN sectors and to minimize errors, using a pivot table and
guidance from the base IMPLAN dataset.

The combination of the \$210 million dairy sales, \$18 million ranch fed
cattle sector, and \$12 million range fed cattle sector cover the output
of these dairy farms in the 1998 IMPLAN model for Erath County's
economy. The dairy sector only includes milk sales; the other 10% of
sales (particularly dry cows, and heifers) are in the ranch and range
fed cattle sectors in the IMPLAN model. These ranch and range fed cattle
sectors for Erath County is interchangeable since they have identical
production functions and outputs within the Erath County IMPLAN dataset.
Their separation in the IMPLAN model dates back to the 1980s when the
Forest Service was trying to separate cattle on federal land from cattle
on private land. The remainder of the replacement heifers sector was
imported using local wholesale and transportation margins modified from
the other sectors. For the purpose of this study, the dairy industry
includes all three sectors.

Erath County has only 125 of the potential 512 IMPLAN industrial
sectors. The dairy industry buys products from 81 sectors. The smaller
ranch and range fed cattle sectors buy from 88 sectors. The combined
IMPLAN dairy and cattle sectors buy from 96 different industrial sectors
in Erath County.

The adjusted categories used in the IMPLAN analysis are shown in Table
5. These RPCs from the survey were used instead of the RPCs in the
original IMPLAN dataset. The first RPC run uses the survey's RPC,
limited to the amount produced within the county. Each sector was
examined individually to determine whether the IMPLAN RPC, the survey
RPC, or the IMPLAN retail margin should be used. For example, if the
product is not produced in the county, such as John Deere tractors, then
the household purchase margin has been used, if available. If not
available, the industrial or institutional margins are used. All RPCs
are constrained by the amount produced in the county.

One needed adjustment was to divide the feed grain and hay and pasture
sectors into two input vectors, one for feed bought in the county (51%)
and the other for feed imported into the county (49%). This division was
made from the survey's calculated RPCs. For the feed purchased within
the county, the wholesale margin was used for IMPLAN calculations. For
the feed that was imported, the transportation margin was applied.

Another adjustment was to move \$25,000,000 from the prepared feeds-
N.E.C sector to the feed grain sector. The interview data did not
designate a prepared feeds sector, but local sources say that because of
their size the local dairies buy the components and process their own
feed. The primary difference is higher margins for the feed grain
sector, particularly wholesale and transportation margins.

Based on local data, it was decided to use the IMPLAN RPC of 68.73% for
banking and credit unions instead of the survey's 45.11%. The Feed Grain
RPC adjusted down to 25%. The margins for feed grains and hay were
adjusted to move the 11.3% margin for feed stores into the Wholesale
sector. There is a large wholesale feed marketing system in Erath
County, and these larger dairy producers will not be using the feed
store sector.

The "replacement heifer" sector[^1] valued at \$8,000,000 was moved to
the range-fed cattle sector from the ranch-fed sectors. In Erath County
these two sectors are interchangeable since they have identical
production functions and outputs. The separation in the IMPLAN model
dates back to the 1980s when the Forest Service was trying to separate
cattle held on federal land from cattle held on private land. The
remainder of the replacement heifers sector was imported using local
wholesale and transportation margins modified from the other sectors.

The remaining problem was an underestimation of the local wholesale,
rail, and trucking costs for imported goods. To solve this we separate
the margins for these imports as separate expenses. The twenty-three
other margin categories totaled less than 3% and were ignored as a
result. There are currently \$82,000,000 of imports purchased by the
dairies. These margins will be assigned to the \$73,000,000 of imported
feed grains and the \$4,000,000 of hay margins, deducting 34.9% from
these amounts and moving that to the rail, trucking, and wholesale
sectors. A test run showed the need to reduce locally-produced range fed
cattle by \$3M and feed grains and hay by \$1M each below the survey
RPCs to stay within the county's level of production. The final margin
adjustments to these large categories are shown in Table 6.

##### Table 3: Erath County's Dairy Industry Production Function

  ---------------------- ------------- --------------- -------- ------- --------- -------------
  INCOME                 3 yr.         2000 Total      \% of    2000 %  \% of     Totals used
                         Average/ Farm                 Total    of Milk Total     for Analysis
                                                       Income   Sales   County    

  Receipts from Sales of \$2,315,003   \$94,302,812    90%      100%    47.200%   \$
  Milk (gross)                                                                    199,796,131

  Milking\\Dry Cows      847           29,861                           33%       

  Number of Producers    40            40                               25%       

  Cull Cow Sales         \$ 107,431    \$ 4,833,262    5%       5%                \$ 10,240,067

  Sales of Bulls/Heifers \$ 36,832     \$ 1,568,397    1%       2%                \$ 3,322,909
  Dairy calves                                                                    

  Sale of Other          \$ 11,291     \$ 375,000      0%       0%                \$ 794,500
  Livestock                                                                       

  Sales of Crops and Hay \$ 5,601      \$ 106,709      0%       0%                \$ 226,081
  etc.                                                                            

  Other Farm Income      \$ 25,544     \$ 885,485      1%       1%                \$ 1,876,047

  Gov. Payments received \$ 14,625     \$ 740,260      1%       1%                \$ 1,568,364

  Off-farm Income        \$ 5,828      \$ 190,847      0%       0%                \$ 404,341
  Dividends\\Interest                                                             
  Received                                                                        

  Spouses Off-farm       \$ 10,883     \$ 181,675      0%       0%                \$ 384,910
  income                                                                          

  Sale of                \$ 36,503     \$ 1,771,114    2%       2%                \$ 3,752,398
  Machinery/Equipment                                                             
  Capital Assets                                                                  

  Total Income           \$ 2,570,429  \$104,985,463   100%     111%              \$
                                                                                  222,429,097

  Operating Expenses     2000 Avg.     2000 Total                                 
                         Farm                                                     

  Feed                   \$ 1,013,893  \$ 39,541,830   38%      42%               \$ 83,775,919

  Labor Wages Paid       \$ 222,013    \$ 8,128,896    8%       9%                \$ 17,222,414

  Health Benefits        \$ 4,328      \$ 60,587       0%       0%                \$ 128,364

  Other Benefits         \$ 12,653     \$ 215,102      0%       0%                \$ 455,729

  Owner\'s Draw          \$ 33,300     \$ 765,902      1%       1%                \$ 1,622,690

  Supplies               \$ 83,308     \$ 3,332,311    3%       4%                \$ 7,060,053

  Insurance              \$16,902      \$ 659,165      1%       1%                \$1,396,550

  Vet, Medicines         \$ 51,850     \$ 2,022,133    2%       2%                \$ 4,284,224

  Breeding               \$ 88,705     \$ 2,749,855    3%       3%                \$ 5,826,022

  Test & Trimming        \$ 17,598     \$ 615,923      1%       1%                \$ 1,304,935

  Repairs & Maintenance  \$ 65,710     \$ 2,628,405    3%       3%                \$ 5,568,711

  Interest               \$ 159,491    \$ 5,502,702    5%       6%                \$ 11,658,386

  Utilities              \$ 45,931     \$ 1,791,326    2%       2%                \$ 3,795,221

  Milk Hauling           \$ 136,289    \$ 5,178,978    5%       5%                \$ 10,972,523

  Promotion              \$ 37,240     \$ 1,377,886    1%       1%                \$ 2,919,279

  Crop Expenses          \$ 33,553     \$ 939,495      1%       1%                \$ 1,990,477

  Fuel, Oil, Gas         \$ 19,151     \$ 746,876      1%       1%                \$ 1,582,381

  Taxes                  \$ 16,084     \$ 546,839      1%       1%                \$ 1,158,570

  School Taxes           \$ 4,442      \$ 71,075       0%       0%                \$ 150,584

  Mortgage\\Rent         \$ 98,309     \$ 3,145,892    3%       3%                \$ 6,665,094

  Legal & Accounting     \$ 8,294      \$ 306,883      0%       0%                \$ 650,184

  Cost of Raising        \$ 133,486    \$ 4,538,521    4%       5%                \$ 9,615,608
  Heifers                                                                         

  Replacement Heifers    \$ 485,267    \$ 20,465,902   19.49%   21.7%             \$ 43,360,404
  Purchased                                                                       

  Miscellaneous          \$ 117,479    \$ 3,759,328    4%       4%                \$ 7,964,759

  Total Expenses         \$ 2,905,275  \$102,213,390   97%      108%              \$
                                                                                  231,129,079
  ---------------------- ------------- --------------- -------- ------- --------- -------------

+-----------------------+------+------+--------+--------+------------+
| ##### Table 4: Dairy  |      |      |        |        |            |
|  Expenses from Survey |      |      |        |        |            |
+-----------------------+------+------+--------+--------+------------+
| Expense Category      | E    | O    | Total  | Out of | Survey     |
|                       | rath | ther | Texas  | State  | Expenses   |
|                       | Co   | Coun |        |        |            |
|                       | unty | ties |        |        |            |
+-----------------------+------+------+--------+--------+------------+
| Breeding              | 6    | 0.1% | 62.7%  | 37.3%  | \$         |
|                       | 2.6% |      |        |        | 5,826,022  |
+-----------------------+------+------+--------+--------+------------+
| Cost of Raising       | 9    | 8.5% | 100.0% | 0.0%   | \$         |
| Heifers               | 1.5% |      |        |        | 9,615,608  |
+-----------------------+------+------+--------+--------+------------+
| Crop Expenses         | 9    | 2.3% | 100.0% | 0.0%   | \$         |
|                       | 7.7% |      |        |        | 1,990,477  |
+-----------------------+------+------+--------+--------+------------+
| Feed                  | 5    | 2    | 74.1%  | 25.9%  | \$         |
|                       | 1.0% | 3.1% |        |        | 83,775,919 |
+-----------------------+------+------+--------+--------+------------+
| Fuel, Oil, Gas        | 9    | 0.8% | 100.0% | 0.0%   | \$         |
|                       | 9.2% |      |        |        | 1,582,381  |
+-----------------------+------+------+--------+--------+------------+
| Health                | 7    | 1    | 89.4%  | 10.6%  | \$ 128,364 |
|                       | 3.5% | 5.9% |        |        |            |
+-----------------------+------+------+--------+--------+------------+
| Insurance             | 7    | 1.1% | 77.4%  | 22.6%  | \$         |
|                       | 6.3% |      |        |        | 1,396,550  |
+-----------------------+------+------+--------+--------+------------+
| Interest              | 4    | 6.8% | 51.9%  | 48.1%  | \$         |
|                       | 5.1% |      |        |        | 10,772,521 |
+-----------------------+------+------+--------+--------+------------+
| Labor-Wages           | 10   | 0.0% | 100.0% | 0.0%   | \$         |
|                       | 0.0% |      |        |        | 17,222,414 |
+-----------------------+------+------+--------+--------+------------+
| Legal & Accounting    | 6    | 0.3% | 66.1%  | 33.9%  | \$ 650,184 |
|                       | 5.8% |      |        |        |            |
+-----------------------+------+------+--------+--------+------------+
| Milk Hauling          | 9    | 1.5% | 100.0% | 0.0%   | \$         |
|                       | 8.5% |      |        |        | 10,972,523 |
+-----------------------+------+------+--------+--------+------------+
| Misc.                 | 9    | 1.4% | 95.9%  | 4.1%   | \$         |
|                       | 4.5% |      |        |        | 7,964,759  |
+-----------------------+------+------+--------+--------+------------+
| Mortgage\\Rent        | 8    | 0.0% | 83.2%  | 16.8%  | \$         |
|                       | 3.2% |      |        |        | 6,665,094  |
+-----------------------+------+------+--------+--------+------------+
| Other Benefits        | 10   | 0.0% | 100.0% | 0.0%   | \$ 455,729 |
|                       | 0.0% |      |        |        |            |
+-----------------------+------+------+--------+--------+------------+
| Owner\'s Draw         | 9    | 0.0% | 90.1%  | 9.9%   | \$         |
|                       | 0.1% |      |        |        | 1,622,690  |
+-----------------------+------+------+--------+--------+------------+
| Promotion             | 6    | 3.2% | 70.7%  | 29.3%  | \$         |
|                       | 7.4% |      |        |        | 2,919,279  |
+-----------------------+------+------+--------+--------+------------+
| Repairs Maintenance   | 9    | 0.8% | 97.5%  | 2.5%   | \$         |
|                       | 6.7% |      |        |        | 5,568,711  |
+-----------------------+------+------+--------+--------+------------+
| Replacement Heifers   | 5    | 5.8% | 63.7%  | 36.3%  | \$         |
| Purchased             | 7.9% |      |        |        | 22,601,978 |
+-----------------------+------+------+--------+--------+------------+
| School Taxes          | 9    | 0.8% | 100.0% | 0.0%   | \$ 150,584 |
|                       | 9.2% |      |        |        |            |
+-----------------------+------+------+--------+--------+------------+
| Supplies              | 9    | 0.6% | 96.8%  | 3.2%   | \$         |
|                       | 6.2% |      |        |        | 7,060,053  |
+-----------------------+------+------+--------+--------+------------+
| Taxes                 | 9    | 0.1% | 100.0% | 0.0%   | \$         |
|                       | 9.9% |      |        |        | 1,158,570  |
+-----------------------+------+------+--------+--------+------------+
| Testing & Trimming    | 9    | 0.5% | 100.0% | 0.0%   | \$         |
|                       | 9.5% |      |        |        | 1,304,935  |
+-----------------------+------+------+--------+--------+------------+
| Utilities             | 9    | 0.0% | 99.9%  | 0.1%   | \$         |
|                       | 9.9% |      |        |        | 3,795,221  |
+-----------------------+------+------+--------+--------+------------+
| Vet, Medicines        | 9    | 0.2% | 100.0% | 0.0%   | \$         |
|                       | 9.8% |      |        |        | 4,284,224  |
+-----------------------+------+------+--------+--------+------------+
| Totals                |      |      |        | \$     |            |
|                       |      |      |        | 209,4  |            |
|                       |      |      |        | 84,788 |            |
+-----------------------+------+------+--------+--------+------------+

##### 

##### 

##### Table 6: Margin Adjustments

  --------- -------------- -------------- -------------- --------- ---------- ----------- ----------- ----------- ------------ --------------
  Sector    Total          Local          Imported       Percent                          Margin                               Actual
                                                         Margin                           Amount                               

                                          Amount         Rail      Trucking   Wholesale   Rail        Trucking    Whole-sale   Imports

  Feed      \$78,485,555   \$6,485,555    \$72,000,000   2.50%     6.00%      26.20%      1,800,000   4,320,000   18,864,000   \$47,016,000
  Grains                                                                                                                       

  Hay       \$9,626,508    \$8,794,052    \$832,456      2.70%     5.70%      26.50%      22,476      47,450      220,601      \$541,929

  Import    \$43,360,404   \$15,118,484   \$20,241,920   0.00%     6.00%      26.20%      \$-         1,214,515   5,303,383    \$13,724,022
  Heifers                                                                                                                      

  Range fed                \$8,000,000                                                                                         
  cattle                                                                                                                       

  Totals    \$131472467    \$38,398,091   \$93,074,376                                    1,822,476   5,581,965   24,387,984   \$61,281,951
  --------- -------------- -------------- -------------- --------- ---------- ----------- ----------- ----------- ------------ --------------

### Wages 

Wages were run as a separate calculation[^2]. Total wages were estimated
at \$17,222,413 and local labor at 100% based on the survey. A deduction
of 10% accounted for taxes and savings, therefore, \$15,500,169 was the
direct impact used. This income figure was used with the IMPLAN
institution impact group, Household 20-30K to estimate their
expenditures. This income group was adopted since the average income for
most farm workers was likely to fall in this range. As primary data on
consumption patterns for this group was not surveyed, the IMPLAN model
household consumption RPCs were used for sector allocation and their
corresponding RPC's.

### Owner's Draw

Owner's draw was also figured as a separate calculation. Owners' draw
represents the amount, retained by the proprietor or owner for family
expenses. The total owners' draw was placed at \$4,201,127, based on the
interview data in the final section of the survey. These numbers were
estimated by comparing respondent information regarding owner's draw
expenses, retained earnings, and household expenses. By comparing the
information, the maximum of the three figures was selected to estimate
the equity or profits that producers earned in the year. The logic
behind this approach was that producers may have reacted differently to
the three survey questions. A deduction of 25% was made for taxes and
savings to arrive at actual consumption. As in the previous case,
owners' consumption patterns were not researched in the survey. In the
absence of these details, the IMPLAN Households 60-70K (and the
corresponding RPC's) was adapted to estimate the expenditures.

### Capital Expenses

Besides incurring operating expenses for producing milk in the county,
producers from time to time also incur expenses for capital
improvements, such as new equipment and vehicle purchases, building new
farm structures, lagoons and retention ponds (for complying with
environmental regulations), erecting new storage silos and so on. In the
survey, producers were asked to estimate these expenditures for the last
five years. Taking yearly averages and extrapolating the figures from
the sample to the county dairy population provided estimates of capital
expenses (See Table 7).

##### Table 7: Estimated Capital Expenses

  ------------------------------ ---------------- ------------------------
  ITEM                           Expenditures     IMPLAN Sector

  Structures and Buildings       \$10, 121, 436   \# 49

  Equipment                      \$ 6, 989, 677   \# 309

  Lagoons & Retention ponds      \$ 429, 677      \# 51

  Farm vehicles                  \$1,243,752      \# 451

  Storage Silos                  \$ 286, 924      #49

  Other                          \$14, 066,347    (Not Used in Model)
  ------------------------------ ---------------- ------------------------

The "other" category was not analyzed since it was computed on a very
small response in the sample, which precluded us from generalizing this
estimate to the total population.

## Texas Model

The Texas model was constructed from the 1999 MIG Texas data set using
all sectors except for Federal Defense. This dataset uses 497 industrial
sectors, compared to the 125 sectors active in Erath County. In 2000,
Texas had a total population of 20.85 million, total personal income of
\$580.7 billion, and with the Gross State Product (output) of \$710.1
billion (State Comptrollers Office). For this year, Erath County has
only 0.21% of Texas\'s total output (sales), but 25.0% of the state's
total dairy production. The dairy impact vectors were imported into the
Texas model from the Erath County model. Due to Texas' larger economy,
the multiplier effects can be expected to be higher.

The only needed adjustment was in the employment run of the capital
expenditures account. The county's local construction industry generates
more jobs per million dollars than the state average, perhaps because
construction wages in Erath County are lower than the Texas average.
Since the number of jobs used in the direct construction in Erath County
is known, the Erath County figure of 190 jobs was measured as having a
direct impact for both the Erath County and Texas results, with the
indirect jobs being calculated within the respective model.

## Results and Discussion

As stated above, the economic impact is measured at three levels namely:
the direct effect, the indirect effect, and the induced effect. These
were estimated at two levels, county and state. These impacts are not
mutually exclusive; indeed the state-level impact measures the impact of
Erath County's dairy industry on the state of Texas and thus includes
the impact on Erath County as well. One can estimate the
"rest-of-the-state" impact by subtracting the county impact from the
state total.

### Economic Impact at the County Level:

The economic impact is calculated for four types of expenses, namely
**Operating Expenses**, **Wages**, **Owner's Draw**, and **Capital
Expenditures**. Direct operating expenses for the dairy industry, as
described in the section above, were based on the amount that was
estimated from the sample (extrapolated to the population). These
expenditures were consequently adjusted to the actual amount spent
within the county (state) -- the Regional Purchasing Coefficients - by
either adjusting the total by the percentage indicated by respondents or
by using the RPC's supplied by IMPLAN. These estimates were further
cross-checked by examining the economic structure of the county provided
by IMPLAN's input-output model.

In all, it was estimated that the dairy industry's *operating expenses*
for the year 2000 equaled (after adjusting for local RPC's) to
\$200,897,159 (See Appendix Table A) spread over 97 of the 128 sectors
in Erath County's economy. When these expenditures were imported in
IMPLAN, the model reduced these expenditures to \$190,876,693, adjusting
for the RPC's. These represent the *direct* economic effects of the
operating expenses of the county's dairy industry. These expenditures by
individual sectors were then processed by IMPLAN, and after several
iterations, the model computed the indirect effects amounting to
\$31,251,920. Subsequently the model estimated the induced effects to
equal an additional \$27,411,505. Thus, the total effect from partial
operating expenses in aggregate equals **\$249.54 million** in
**output** (sales).

**Wages** were treated separately, and as reported earlier were
estimated from the survey data to equal \$17,222,413. A deduction of 10%
accounted for taxes and savings, so \$15,500,169 was the direct impact
figure used. The total effects inclusive of direct, indirect and induced
effects equaled \$**18.84 million.**

**Owners' Draw** was also figured separately. As stated earlier, owners'
draw represents the amount retained by the proprietor or owner for
his/her family expenses. The total owners' draw was placed at
\$4,201,127 and an adjustment of 25% was made to reflect taxes and
savings. The total effects inclusive of direct, indirect, and induced
effects equaled to \$**3.81 million.**

Adding the effects associated with operating expenses, wages, and
owners' draw gives a total impact of **\$272.2 million** in output or
sales (See Appendix Table A). We repeated the procedure by aggregating
the operating expenses, wages, and owners' draw and processed the data
into IMPLAN. The total effect was slightly higher \-- \$272.8 million
(See Table 8). The marginal difference of less than 0.22% is due to
rounding within the model. To this last figure, the direct impact of
wages of \$17,222,413 and owner's draw of \$4,201,127 are added to
obtain a total economic impact from operating expenses of **\$294.2
million**.

Besides non-labor expenses (\$200,897,100), wages (\$17,222,413) and
owners' draw (\$4,201,127), we also added the actual taxes (\$915,622)
paid by dairy farmers in the county for year 2000. This number was
derived by obtaining information on the value of properties listed as
dairies from the Erath County Appraisal District. Ms. Jennifer Carey,
Tax Assessor for the county, assisted us in estimating the actual taxes
paid. The total expenses added to \$223,236,262. Dividing the total
impact of \$294,202,950 by \$223,236,262 provides a multiplier of
**1.32.** This is a conservative and smaller multiplier than various
multipliers obtained earlier: (a) 1.44 obtained in Neilson's study
(Neilsen et.al) of Erath County's dairy industry in 1995, (b) 1.5
reported in the 1993 Jones study of the dairy industry in the
Cross-Timbers region (Jones et.al), and (c) 1.58 for Okeechobee County
in 1991 in Florida (Mulkey & Clouser). Our results were expected, since
Erath County is a smaller area, represents only one county within the
Cross-Timbers Region and is smaller in size and population than
Okeechobee County, Florida. The main difference between this study and
the Neilsen study was the collection method and usage of the local
survey data compared with Neilsen's greater reliance on the national
IMPLAN baseline data.

The dairy producer's gross income from the sale of milk for the year
2000, as mentioned earlier was estimated at \$199,796,131. This amount
represents about 90% of the dairy industry's total income there. The
remaining 10% is derived from the sale of cows, heifers, government
payments, and off-farm income. The combined total of all income for the
Erath County dairy industry equals \$222,429,097. Adding this last
figure to the additional impact of \$294,202,250 obtained from applying
from the multiplier effects provides a figure of \$516,632,047 for the
total impact of the dairy industry (from operating expenses alone).

As mentioned in the methodology section, producers occasionally incur
expenses for capital improvements such as building new farm structures,
lagoons and retention ponds (for complying with environmental
regulations), erecting new storage silos, new equipment and vehicle
purchases and so on. The average yearly total capital expenditures were
estimated (direct impact) at \$19,071,044. Using IMPLAN, the estimated
indirect and induced impact flowing from these direct expenditures added
another \$7,553,483 to give a total impact of \$26,624,526 from
**capital expenditures**.

Adding capital expenditures to the previous figure of \$516,632,047
(from operating expenses) gives a grand total of **\$543.3 million** for
the economic impact of the dairy industry to Erath County. This amount
represents **36%** of the county's total output.

##### Table 8: Output Creation in Erath County

  ------------ --------------- -------------- -------------- ---------------
  Event        Direct          Indirect       Induced        Total

  Operating    \$209,527,707   \$32,846,943   \$30,404,760   \$272,779,410
  Expenses                                                   

  Capital      \$19,071,040    \$3,514,195    \$4,039,288    \$26,624,526
  Expenses                                                   

  Total        \$228,598,747   \$36,361,138   \$34,444,048   \$299,403,936
  ------------ --------------- -------------- -------------- ---------------

#### Employment Impact

The economic structure created by the IMPLAN input-output model
estimated that in 1998 there were 1,386 workers in the county's dairy
sector and an additional 325 in the ranch fed cattle sector, for a total
of 1,711 workers in the dairy sector. USDA's National Agricultural
Statistical Service (NASS) estimated that there were 79,000 milking cows
in 1998. This translates into roughly 2.16 jobs per 100 cows. According
to NASS, the number of milking cows in the year 2000 was estimated at
91,400. Using the ratio of 2.16 jobs/100 cows for a total of 91,400 cows
yields an estimate of 1,980 jobs located on the county's dairy farms.

The *direct* impact on employment from the operating expenses of almost
\$200 million equals 2,465 jobs, the *indirect* impact creates an
additional 550 jobs while the *induced* impact result in 600 more jobs
created. Adding these three figures results in the creation of 3,615
jobs linked to operating expenses from the dairy industry in Erath
County. To this figure we add another 317 jobs created from the capital
expenses sector for a total of 3,932 jobs.

Further, adding the 3,932 jobs from the direct, indirect, and induced
effects to the 1,980 jobs on the dairy farms provides an estimated
**5,912** jobs that can be attributed to the presence of the dairy
industry in the county. The county's total employment equals 19,354.
Thus, the dairy industry accounts for **31%** of Erath County's total
employment.

##### Table 9: Job-Creation in Erath County

  -------------------------- ---------- ------------ ------------ ---------
  Event                      Direct     Indirect     Induced      Total

  Operating Expenses         2465       550          600          3615

  Capital Expenses           190        48.3         78.6         317

  Total                      2655       598.3        678.6        3932
  -------------------------- ---------- ------------ ------------ ---------

#### Value-Added

The IMPLAN model also estimates the total value added in terms of
profits, rent, wages and local taxes. The total value-added to the
county from all these sources is \$**123.1 million**. This amount
represents **18%** of the \$706.6 million in personal income for Erath
County.

The impact on wages for the county (direct and indirect wages) paid by
the dairy industry amounted to \$60 million also representing **18%** of
all the wages paid (the total employee compensation in the county equals
\$338 million according to IMPLAN).

The direct taxes (property and school) paid by the county's dairy
producers were estimated at \$915,622. Of this amount, 75% were paid as
school taxes, 18% were paid to the county, and the remaining 7% were
paid as roads and bridges taxes. A detailed breakdown by school district
was estimated by obtaining information from the Erath County Appraisal
District on the value of all dairy properties. Based on this information
the county's Tax Assessor calculated the actual taxes paid by the dairy
producers in the year 2000. According to the Tax Assessor's office,
total property taxes collected from all sources for the year 2000
equaled \$22,800,678. Dairy producers paid 4% of all the property.

In addition to direct taxes, the model estimated that indirect business
taxes (mainly sales taxes) from expenditures incurred by the dairy
industry in the county at \$9,443,409. Adding the direct and indirect
taxes yields a total of **\$10.4 million** that can be attributed to the
dairy industry. Also note that this IMPLAN model is built on a national
scale to model all 3,028 US counties simultaneously. IMPLAN estimates
marginal taxes at the national, state, and county levels, but then makes
adjustments so all the counties add up to the national level. As such,
these tax estimates may not exactly reflect the current Texas and Erath
County tax codes.

+----+-----------------------------+----------+-----------+----------+
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| s  |                             |          |           |          |
| in |                             |          |           |          |
|  E |                             |          |           |          |
| ra |                             |          |           |          |
| th |                             |          |           |          |
|  C |                             |          |           |          |
| ou |                             |          |           |          |
| nt |                             |          |           |          |
| y  |                             |          |           |          |
| Im |                             |          |           |          |
| pa |                             |          |           |          |
| ct |                             |          |           |          |
| ed |                             |          |           |          |
|  b |                             |          |           |          |
| y  |                             |          |           |          |
| th |                             |          |           |          |
| e  |                             |          |           |          |
| Da |                             |          |           |          |
| ir |                             |          |           |          |
| y  |                             |          |           |          |
| In |                             |          |           |          |
| du |                             |          |           |          |
| st |                             |          |           |          |
| ry |                             |          |           |          |
+----+-----------------------------+----------+-----------+----------+
| Se | Industry                    | Direct   | Indirec   | Total    |
| ct |                             |          | t/Induced |          |
| or |                             |          |           |          |
+----+-----------------------------+----------+-----------+----------+
| 4  | Wholesale Trade             | 24671364 | 3052214   | 2        |
| 47 |                             |          |           | 7,723578 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Motor Freight Transport and | 16       | 4,269,995 | 20       |
| 35 | Warehouse                   | ,472,708 |           | ,742,704 |
+----+-----------------------------+----------+-----------+----------+
| 13 | Hay and Pasture             | 15       | 1,602,923 | 16       |
|    |                             | ,040,222 |           | ,643,145 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Real Estate                 | 6        | 8,027,057 | 14       |
| 62 |                             | ,826,460 |           | ,853,516 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Banking and Credit Agencies | 9        | 3,739,812 | 13       |
| 56 |                             | ,273,845 |           | ,013,657 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Medical and Health Services | 4        | 3,113,408 | 7        |
| 93 |                             | ,370,437 |           | ,483,844 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Electric Services           | 3        | 2,195,577 | 6        |
| 43 |                             | ,911,748 |           | ,107,325 |
+----+-----------------------------+----------+-----------+----------+
| 56 | Maintenance and Repair      | 4        | 1,658,756 | 5        |
|    | Other Facilities            | ,083,607 |           | ,742,363 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Communications              | 1        | 2,245,403 | 4        |
| 41 |                             | ,927,809 |           | ,173,212 |
+----+-----------------------------+----------+-----------+----------+
| 1  | Dairy Farm Products         | 3        | 603,102   | 3        |
|    |                             | ,270,165 |           | ,873,266 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Eating & Drinking           | 637,503  | 1,715,137 | 2        |
| 54 |                             |          |           | ,352,640 |
+----+-----------------------------+----------+-----------+----------+
| 1  | Drugs                       | 1        | 867,687   | 2        |
| 95 |                             | ,247,421 |           | ,115,108 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Insurance Carriers          | 1        | 319,630   | 1        |
| 59 |                             | ,157,987 |           | ,477,617 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Automotive Dealers &        | 469,987  | 998,953   | 1        |
| 51 | Service Stations            |          |           | ,468,940 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Miscellaneous Retail        | 413,643  | 901,637   | 1        |
| 55 |                             |          |           | ,315,280 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Automobile Repair and       | 135,396  | 1,051,993 | 1        |
| 79 | Services                    |          |           | ,187,389 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Other Business Services     | 74,798   | 1,094,605 | 1        |
| 70 |                             |          |           | ,169,403 |
+----+-----------------------------+----------+-----------+----------+
| 4  | Equipment Rental and        | 776,925  | 329,308   | 1        |
| 73 | Leasing                     |          |           | ,106,232 |
+----+-----------------------------+----------+-----------+----------+

From the model results we also extracted information on output and
employment for industries that were the most impacted by the presence of
the dairy industry in the county. These industries will be on the top of
the list that could either benefit or lose by the expansion or
contraction of the dairy industry in the county. A list of these
industries with their corresponding output and employment is given in
Tables 10 and 11. Note that the dairy farm sector includes the dairy
farm products and ranch and range fed cattle.

Significant output (sales) impacts occurred in numerous sectors,
including wholesale trade, motor freight, transportation and warehouse,
hay and pasture, real estate, banking and credit agencies.

In terms of employment those industries impacted most by the dairy
industry include the hay and pasture industry, which tops the list in
the number of jobs linked to the dairy industry. Other industries of
significance are wholesale trade, motor freight transportation and
warehouse (229), banking and credit agencies (191), Ag services (171),
and medical and health services (138).

+--------+----------------------------------------+--------+------+---+
| #      |                                        |        |      |   |
| #### T |                                        |        |      |   |
| able 1 |                                        |        |      |   |
| 1: Emp |                                        |        |      |   |
| loymen |                                        |        |      |   |
| t in E |                                        |        |      |   |
| rath C |                                        |        |      |   |
| ounty  |                                        |        |      |   |
| Impact |                                        |        |      |   |
| ed by  |                                        |        |      |   |
| the Da |                                        |        |      |   |
| iry In |                                        |        |      |   |
| dustry |                                        |        |      |   |
+--------+----------------------------------------+--------+------+---+
| IMPLAN | Industry                               | Direct | I    | T |
| Sector |                                        |        | ndir | o |
|        |                                        |        | ect+ | t |
|        |                                        |        | Ind  | a |
|        |                                        |        | uced | l |
+--------+----------------------------------------+--------+------+---+
| 13     | Hay and Pasture                        | 746    | 79   | 8 |
|        |                                        |        |      | 2 |
|        |                                        |        |      | 5 |
+--------+----------------------------------------+--------+------+---+
| 447    | Wholesale Trade                        | 391    | 48   | 4 |
|        |                                        |        |      | 3 |
|        |                                        |        |      | 9 |
+--------+----------------------------------------+--------+------+---+
| 435    | Motor Freight Transport and Warehouse  | 182    | 47   | 2 |
|        |                                        |        |      | 2 |
|        |                                        |        |      | 9 |
+--------+----------------------------------------+--------+------+---+
| 456    | Banking and Credit Agencies            | 138    | 53   | 1 |
|        |                                        |        |      | 9 |
|        |                                        |        |      | 1 |
+--------+----------------------------------------+--------+------+---+
| 26     | Agricultural- Forestry- Fishery        | 127    | 44   | 1 |
|        | Services                               |        |      | 7 |
|        |                                        |        |      | 1 |
+--------+----------------------------------------+--------+------+---+
| 493    | Medical and Health Services            | 89     | 50   | 1 |
|        |                                        |        |      | 3 |
|        |                                        |        |      | 8 |
+--------+----------------------------------------+--------+------+---+
| 454    | Eating & Drinking                      | 21     | 56   | 7 |
|        |                                        |        |      | 7 |
+--------+----------------------------------------+--------+------+---+
| 462    | Real Estate                            | 38     | 27   | 6 |
|        |                                        |        |      | 4 |
+--------+----------------------------------------+--------+------+---+
| 455    | Miscellaneous Retail                   | 14     | 30   | 4 |
|        |                                        |        |      | 4 |
+--------+----------------------------------------+--------+------+---+
| 450    | Food Stores                            | 11     | 22   | 3 |
|        |                                        |        |      | 3 |
+--------+----------------------------------------+--------+------+---+
| 449    | General Merchandise Stores             | 10     | 22   | 3 |
|        |                                        |        |      | 2 |
+--------+----------------------------------------+--------+------+---+
| 451    | Automotive Dealers & Service Stations  | 9      | 20   | 2 |
|        |                                        |        |      | 9 |
+--------+----------------------------------------+--------+------+---+
| 1      | Dairy Farm Products                    | 22     | 4    | 2 |
|        |                                        |        |      | 6 |
+--------+----------------------------------------+--------+------+---+
| 479    | Automobile Repair and Services         | 2      | 17   | 1 |
|        |                                        |        |      | 9 |
+--------+----------------------------------------+--------+------+---+
| 507    | Accounting- Auditing and Bookkeeping   | 8      | 11   | 1 |
|        |                                        |        |      | 9 |
+--------+----------------------------------------+--------+------+---+
| 470    | Other Business Services                | 1      | 16   | 1 |
|        |                                        |        |      | 8 |
+--------+----------------------------------------+--------+------+---+
| 525    | Domestic Services                      | 5      | 13   | 1 |
|        |                                        |        |      | 8 |
+--------+----------------------------------------+--------+------+---+
| 482    | Miscellaneous Repair Shops             | 10     | 8    | 1 |
|        |                                        |        |      | 8 |
+--------+----------------------------------------+--------+------+---+
| 441    | Communications                         | 8      | 9    | 1 |
|        |                                        |        |      | 7 |
+--------+----------------------------------------+--------+------+---+
| 459    | Insurance Carriers                     | 13     | 4    | 1 |
|        |                                        |        |      | 7 |
+--------+----------------------------------------+--------+------+---+
| 473    | Equipment Rental and Leasing           | 11     | 5    | 1 |
|        |                                        |        |      | 6 |
+--------+----------------------------------------+--------+------+---+

## Economic Impact at the State level

The state economic impact is calculated as for the county, with four
types of expenses: operating, wages, owner's draw, and capital. Direct
operating expenses for the dairy industry, as described in the previous
sections, was based on the amount that was estimated from the sample
extrapolated to the county level. These expenditures were consequently
adjusted for the actual amount spent within the state-- the Regional
Purchasing Coefficients (RPC) by either adjusting the total by the
percentage respondents indicated or by using IMPLAN RPC's. The Regional
Purchasing Coefficients at the state level (see Tables 8 and 9) were
higher and the amount of imports was lower, as expected. For example, at
the county level the RPC for feed was 51%, indicating that producers
imported 49% from outside the county. At the state level, the
corresponding RPC is 74%, which implies that only 26% was imported.
Since Texas has a relatively large economy, total imports from outside
the state will be low, and subsequently the state's multiplier effects
are expected to be larger than for Erath County.

The multiplier effects were larger at the state level than at the county
level. The direct effects at the state level for operating expenses
equaled \$204.4 million, as compared to \$190.9 million at the county
level due to the higher RPC's at the state level. The indirect and
induced effects are also correspondingly higher, amounting to \$68.9
million and \$178.2 million, respectively. The total effects from the
operating expenses alone are \$451.5 million. Wages and owners' draw
were separately calculated following the approach used in the county
calculations, with adjustments made as discussed in the previous
section.

The state's total impact from wages amounted to \$21.8 million, and for
owners' draw to \$5.8 million. The total effect from operating expenses
at the state level equaled \$479.1 million (See Table B). We repeated
the procedure by aggregating the operating expenses, wages, and owners'
draw, and then processed the data into IMPLAN. The total effect was
slightly higher \-- \$485,932,785 (See Table 12). The marginal
difference of 1.4% is due to the rounding within the model. To this last
figure we add the direct impact of wages of (\$17,222,413) and owner's
draw of (\$4,201,127) to obtain a total economic impact from operating
expenses at **\$507,356,248**. Dividing this impact by total expenses
(\$223,236,232) yields a multiplier of **2.28**. As expected, this
multiplier is higher than what was at the county level (1.32). It is
also slightly higher than that for the state's wine industry (1.92)
\[Michaud et.al\], the state's poultry industry (1.35) \[Carey et.al\],
but lower than that for California's dairy industry (2.65) \[CARES\].

As indicated in the previous section, the combined total income of the
dairy industry in Erath County equaled \$222,429,097. Adding this number
to the total impact of \$507,356,248 from operating expenses results in
an impact of \$729,785,345 at the state level.

The direct impact of capital expenses was \$19,071,040, and when these
were processed in the State IMPLAN's model the indirect/induced impacts
generated an additional \$22,941,035, to provide a total impact of
\$42,012,075 for capital expenses at the state level (See Table 12).

When we add the impact of \$729,785,345 from operating expenses to the
\$42,012,075 associated with capital expenses, the total impact of Erath
County's dairy industry on the state of Texas equals **\$771,797,420**.
Please recall that the total impact at the county level was equaled
\$543,256,573. Subtracting the impact at the county level from the
state's total impact gives a difference of \$228,540,847. This implies
that the counties in Texas other than Erath are directly or indirectly
affected by the dairy industry to the magnitude of **\$228.5 million**.

##### Table 12: Output Creation in the State of Texas

  ----------- --------------- -------------- --------------- ---------------
  Event       Direct          Indirect       Induced         Total

  Operating   \$223,042,778   \$72,759,523   \$190,130,402   \$485,932,705
  Expenses                                                   

  Capital     \$19,071,040    \$8,005,895    \$14,935,137    \$42,012,075
  Expenses                                                   

  Total       \$ 242,113,818  \$ 80,765,418  \$ 205,065,539  \$ 527,944,780
  ----------- --------------- -------------- --------------- ---------------

### Employment Impact at the State Level

Besides output, we also estimated the total number of jobs created at
the state level, which can be attributed to the presence of the dairy
industry in Erath County. We would like to restate that the RPC's at the
state level are higher than at the county level. These added purchases
translated into an additional output of \$228 million at the state
level. Thus, we should expect higher job-creation at the state level.

The operating expenses of approximately \$200 million provides 5,211
jobs directly in the dairies. Once the indirect and induced effects are
included, the total jobs figure increases to 8,170. As before, wages and
owners' draw were analyzed separately and once the direct, indirect and,
induced effects are accounted for the total jobs due to these
expenditures translate to 195 and 55, jobs respectively. Thus, the total
jobs from operating expenses add up to 8,420 (See Table Appendix C). We
repeated the procedure by aggregating the operating expenses, wages, and
owners' draw and processed the data into IMPLAN. The total effect was
slightly higher -- 8,501. The difference is due to rounding within the
model

An interesting adjustment needed to be made for calculating the
employment effects from capital expenses. The local impact for
construction was 190 direct jobs, while the state impact calculated only
156 direct jobs on the same \$19M of construction activities. The local
construction industry uses more jobs per million dollars than the state
average, perhaps because construction wages in Erath County are lower
than the Texas average. Since we know the number of jobs used in direct
construction within Erath County (from the county model), the Erath
County figure of 190 jobs was used as the direct impact for both the
Erath County and Texas results. The indirect and induced jobs calculated
with the state model added an additional 255 jobs to give a total effect
of 445 jobs attributed to capital expenditures.

Adding the 445 jobs in the capital expenses sector to the 8,501 from
operating expenses provides an estimate of 8,946 jobs (See Table 13). To
this last figure we add the direct jobs in the dairy industry, estimated
at 1,980 to give a grand total of 10,926 jobs in the state that are
associated with the presence of the dairy industry in Erath County.
Table 14 summarizes all the results for the county and the state.

+--------------------------+---------+-----------+-----------+--------+
| ##                       |         |           |           |        |
| ### Table 13: Job-Creati |         |           |           |        |
| on in the State of Texas |         |           |           |        |
+--------------------------+---------+-----------+-----------+--------+
| Event                    | Direct  | Indirect  | Induced   | Total  |
+--------------------------+---------+-----------+-----------+--------+
| Operating Expenses       | 5361    | 866       | 2274      | 8501   |
+--------------------------+---------+-----------+-----------+--------+
| Capital Expenses         | 190     | 77.2      | 178       | 445    |
+--------------------------+---------+-----------+-----------+--------+
| Total                    | 5551    | 943.2     | 2452      | 8946   |
+--------------------------+---------+-----------+-----------+--------+

##### Table 14: Year 2000 Summary Dairy Impacts

  ----------------------------------------- -- ------------------ -- ------------------
                                               **Erath County**      **Texas**

  Milk Income                                  \$199,796,131         \$199,796,131

  Dairy Producer\'s Gross Income               \$222,429,097         \$222,429,097

  Expenses                                     \$200,897,100         \$200,897,100

  Property+ School Taxes                       \$915,622             \$915,622

  Wages (Pre-Tax)                              \$17,222,413          \$17,222,413

  Owners Draw (Pre-Tax)                        \$4,201,127           \$4,201,127

  Total Expenses                               \$223,236,262         \$223,236,262

  Erath Output Impacts                         \$294,202,950         \$507,356,248

  Output Multiplier                            1.32                  2.28

  Total Impact from Operating Expenses         \$516,632,047         \$729,785,345

  **Total Impact including Capital             \$543,256,573         \$771,797,420
  Expenses**                                                         

  JOBS                                                               

  Dairy Industry Jobs                          1,980                 1,980

  Additional Jobs Created from Operating       3,615                 8,501
  Expenses                                                           

  **Total Jobs**                               5,595                 10,481

  Employment Multiplier                        1.83                  4.29

  Total Jobs including Capital Expenses        5,912                 10,926

  **Value Added (Profits, Rent, Wages,                               
  Local Taxes)**                                                     

  Direct Value Added                           \$29,004,256          \$29,004,256

  Additional Value Added                       \$94,109,426          \$271,577,667

  Total Value Added                            \$123,113,682         \$300,581,923

  **Wages**                                                          

  Direct Wages Paid by Dairy                   \$17,222,413          \$17,222,413

  Indirect Wages                               \$42,719,252          \$116,609,876

  Total Wages Paid                             \$59,941,665          \$133,832,289

  **Property Income**                                                

  Rent paid by Dairies                         \$6,665,094           \$6,665,094

  Indirect Property Income                     \$28,506,353          \$72,059,819

  Total Property Income                        \$35,171,447          \$78,724,913

  **Profits**                                                        

  Dairy Owners Draw (Pre-Tax)                  \$4,201,127           \$4,201,127

  Proprietors Income                           \$13,440,443          \$56,662,106

  Total Profits                                \$17,641,570          \$60,863,233

  **Taxes**                                                          

  Dairy Property+ School Taxes                 \$ 915,622            \$915,622

  Indirect Business Taxes                      \$9,443,409           \$26,245,864

  **Total Local Taxes**                        **\$10,359,031**      **\$27,161,486**
  ----------------------------------------- -- ------------------ -- ------------------

##  Sensitivity Analysis Modeling

Besides estimating the total impact, we also conducted a series of tests
to determine the marginal or micro impact of changes in production and
prices for the dairy industry along with the consequent impacts these
changes will have on output and employment in the county. The questions
we posed follow:

For a change of 1,000 cows what will the impact be on output, value
added, and employment?

We posed the question: what will be the impact on the county in terms of
output and employment when a large dairy (1,000 cows) either decides to
locate or leave the county. This question is taking on an increasing
importance as local newspaper reports suggest that indeed some of the
larger dairies have moved out of the county or are being denied permit
renewals to operate from the Texas Natural Resource Conservation
Commission (TNRCC).

Since the IMPLAN model assumes fixed coefficients, we modeled the change
by adjusting total production (the totals run). In 2000, NASS estimated
91,400 dairy cows in Erath County. A change in 1,000 cows provides a net
change of 1.094% of total dairy production. Using previous IMPLAN
estimates of output and employment, a 1.094% change translates into a
change of \$5,651,955 in output, 61 jobs, and \$1,351,169 in value
added. The change in wages will be \$655,762 (refer to Table 22 for
details). We also estimated total employment in the county by differing
herd sizes as can be seen in Table 16.

##### Table 15: Economic Impact of the loss of a 1,000 Cow Operation

Loss of 1.0940% of current dairy production

  -------------------------------------- -- ----------------- -- -------------
                                            **Erath County**     **Texas**

  NASS Milk Price                           \$13.30              \$13.30

  Milk Income                               \$2,185,770          \$2,185,770

  Dairy Producer's Gross Income             \$2,433,374          \$2,433,374

  **Expenses**                              \$2,197,814          \$2,197,814

  Property and School Taxes                 \$10,017             \$10,017

  Wages(Pre-Tax)                            \$188,413            \$188,413

  Owners Draw(Pre-Tax)                      \$45,960             \$45,960

  Total Expenses                            \$2,442,205          \$2,442,205

                                            **Erath County**     **Texas**

  Output Impacts                            \$3,218,580          \$5,550,477

  Output Multiplier                         1.447%               2.495%

  Total Impact                              \$5,651,955          \$7,983,852

                                                                 

  JOBS IMPACTS                                                   

  Dairy Industry Jobs                       22                   22

  Additional Jobs Affected                  40                   93

  Total Jobs                                61                   115

  Value Added (Profits, Rent, Wages,                             
  Local Taxes)                                                   

  Direct Value Added                        \$317,307            \$317,307

  Additional Value Added                    \$1,029,557          \$2,971,060

  Total Value Added                         \$1,346,864          \$3,288,366

                                                                 

  Wages                                                          

  Direct Wages Paid by Dairy                \$188,413            \$188,413

  Indirect Wages                            \$467,349            \$1,275,712

  Total Wages Paid                          \$655,762            \$1,464,125

                                                                 

  Property Income                                                

  Rent paid by Dairies                      \$72,916             \$72,916

  Indirect Property Income                  \$311,860            \$788,334

  Total Property Income                     \$384,776            \$861,251

                                                                 

  Profits                                                        

  Dairy Owners Draw (Pre-Tax)               \$45,960             \$45,960

  Proprietors Income                        \$147,038            \$619,883

  Total Profits                             \$192,999            \$665,844

                                                                 

  Taxes                                                          

  Dairy Property and School Taxes           \$10,017             \$10,017

  Indirect Business Taxes                   \$103,311            \$287,130

  Total Local Taxes                         \$113,328            \$297,147
  -------------------------------------- -- ----------------- -- -------------

<table>
<colgroup>
<col style="width: 14%" />
<col style="width: 10%" />
<col style="width: 10%" />
<col style="width: 6%" />
<col style="width: 9%" />
<col style="width: 2%" />
<col style="width: 11%" />
<col style="width: 13%" />
<col style="width: 9%" />
<col style="width: 12%" />
</colgroup>
<tbody>
<tr class="odd">
<td colspan="10"><h5
id="table-16-impacts-of-erath-county-employment-per-cow">Table 16:
Impacts of Erath County Employment per cow</h5></td>
</tr>
<tr class="even">
<td colspan="6">Year 2000 Baseline</td>
<td></td>
<td colspan="3">Erath County</td>
</tr>
<tr class="odd">
<td colspan="3">Erath Co. Employment</td>
<td colspan="3"></td>
<td></td>
<td>19,345</td>
<td>Jobs</td>
<td></td>
</tr>
<tr class="even">
<td colspan="6">Erath Co. Employment in the Dairies</td>
<td></td>
<td>1,980</td>
<td>Jobs</td>
<td>10%</td>
</tr>
<tr class="odd">
<td colspan="7">Total Erath Co. Employment with current Dairies</td>
<td>5,595</td>
<td>Jobs</td>
<td>29%</td>
</tr>
<tr class="even">
<td colspan="5">Total Cows in Erath Co. Dairies in 2000</td>
<td colspan="2"></td>
<td>91,400</td>
<td>Cows</td>
<td></td>
</tr>
<tr class="odd">
<td colspan="4">Direct Jobs per 1000 Cows</td>
<td></td>
<td colspan="2"></td>
<td>21.7</td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td colspan="4">Total Jobs per 1000 Cows</td>
<td></td>
<td colspan="2"></td>
<td>61.2</td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td></td>
<td></td>
<td colspan="2"></td>
<td></td>
<td colspan="2"></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td>Cows</td>
<td></td>
<td colspan="2"></td>
<td>0</td>
<td colspan="2">50000</td>
<td>91,400</td>
<td>150000</td>
<td></td>
</tr>
<tr class="odd">
<td colspan="4">Jobs Directly in Dairies</td>
<td>0</td>
<td colspan="2">1,083</td>
<td>1,980</td>
<td>3,249</td>
<td></td>
</tr>
<tr class="even">
<td colspan="4">Total Dairy Supported Jobs</td>
<td>0</td>
<td colspan="2">3,061</td>
<td>5,595</td>
<td>9,182</td>
<td></td>
</tr>
<tr class="odd">
<td colspan="4">Erath Co. Employment</td>
<td>13,750</td>
<td colspan="2">16,811</td>
<td>19,345</td>
<td>22,932</td>
<td></td>
</tr>
<tr class="even">
<td colspan="5">Percent of jobs supported by dairies</td>
<td colspan="2">18%</td>
<td>29%</td>
<td>40%</td>
<td></td>
</tr>
</tbody>
</table>

### For a \$1 increase/decrease in milk price, what will the impact be on output, value added, and employment?

As dairy producers are price-takers, their fortunes increase or decrease
with changes in the price of milk. The price of milk is also a contested
issue in national farm policy debates. We conducted an exercise to
measure the impact of a one-dollar increase or decrease in the price of
milk on dairy producers and the consequent implications for output and
employment for the rest of the county. Our results follow.

Since the IMPLAN model assumes fixed coefficients, we modeled this by
assuming all the impact will be entirely reflected in the owners'
profits (owner's draw). We are assuming no direct impacts on wages or
other expenses. Using the production figures for the county in the year
2000, 1,502,226,552 lbs of milk, a one dollar change in the price of
milk, will translate into a change in \$15,022,265 in the income
received by dairy producers. We assigned this change to owners' profits
for a given year to directly affect the owners' income because all other
expenses are either expended or committed. To estimate the impact of
this change in owners' profits, we subtracted 25% of \$15,022,265 to
adjust for taxes and savings, leaving an \$11,266,700 direct loss in
spending. Once the indirect and induced impacts are estimated using the
IMPLAN model, the total output (sales) change equals \$13,614,000.
Subtracting \$5,630,000 in domestic and foreign trade leaves the final
impact of sales of goods and services produced in Erath County to
**\$7,984,000**. The corresponding employment change is 128.7 jobs and
the Value added change amounts to \$4,892,300. The change in wages is
\$2,176,200 (see Table 17 for details).

##### Table 17: Impact of a change in price of Milk of \$1.00

  ------------------ ------- --------------- --------------- -------------- --------------- --------------
                                             **Erath                        **Texas**       
                                             County**                                       

                                             **Total         **\$1 change   **Total         **\$1 change
                                             Impact**        in Price of    Impact**        in Price**
                                                             Milk of                        
                                                             \$1.00**                       

  Milk Income                                \$ 199,796,131  \$15,022,266   \$199,796,131   \$15,022,266

  Total Gross Income                         \$222,429,097   \$15,022,266   \$222,429,097   \$15,022,266

  **Expenses**                               \$ 200,897,100                 \$200,897,100   

  Property+ School                           \$915,622                      \$915,622       
  Taxes                                                                                     

  Wages (Pre-Tax)                            \$17,222,413                   \$17,222,413    

  Owners Draw                                \$4,201,127     \$ 15,022,266  \$4,201,127     \$15,022,266
  (Pre-Tax)                                                                                 

  Total Expenses                             \$223,236,262   \$15,022,266   \$223,236,262   \$15,022,266

  Erath Output                               \$294,202,950   \$7,984,000    \$507,356,248   \$20,616,494
  Impacts                                                                                   

  Output Multiplier          1.32                            0.53           2.28            1.37

  Total Impact               \$516,632,047                                  \$729,785,345   

  **JOBS**                                                                                  

  Dairy Industry             1,980                           86             1,980           90
  Jobs                                                                                      

  Additional Jobs    3,615                                   42             8,501           107
  Affected                                                                                  

  Total Jobs                 5,595                           129            10,481          197

  Jobs Multiplier            1.83                            0.49           4.29            1.19

  **Value Added                                                                             
  (Profits, Rent,                                                                           
  Wages, Local                                                                              
  Taxes)**                                                                                  

  Direct Value Added                         \$29,004,256    \$3,375,899    \$29,004,256    \$4,601,309

  Additional Value                           \$ 94,109,426   \$1,516,397    \$271,577,667   \$5,670,338
  Added                                                                                     

  Total Value Added                          \$ 123,113,682  \$ 19,914,562  \$300,581,923   \$25,293,913

  **Wages**                                                                                 

  Direct Dairy Wages                         \$17,222,413    \$1,389,924    \$17,222,413    \$2,115,800

  Indirect Wages                             \$42,719,252    \$ 786,213     \$116,609,876   \$3,113,110

  Total Wages Paid                           \$59,941,665    \$2,176,137    \$133,832,289   \$5,228,910

  **Property                                                                                
  Income**                                                                                  

  Rent paid by                               \$6,665,094     \$1,236,609    \$6,665,094     \$1,587,969
  Dairies                                                                                   

  Indirect Property                          \$ 28,506,353   \$ 431,216     \$72,059,819    \$1,491,300
  Income                                                                                    

  Total Property                             \$ 35,171,447   \$1,667,825    \$78,724,913    \$3,079,269
  Income                                                                                    

  **Profits**                                                                               

  Owners Draw                                \$ 4,201,127    \$ 15,022,266  \$4,201,127     \$15,022,266
  (Pre-Tax)                                                                                 

  Proprietors Income                         \$13,440,443    \$ 525,362     \$56,662,106    \$ 942,198

  Total Profits                              \$17,641,570    \$ 15,547,628  \$60,863,233    \$15,964,464

  **Taxes**                                                                                 

  Property+ School                           \$ 915,622      \$ 407,835     \$915,622       \$ 557,091
  Taxes                                                                                     

  Indirect Business                          \$9,443,409     \$ 115,137     \$26,245,864    \$ 464,177
  Taxes                                                                                     

  Total Local Taxes                          \$10,359,031    \$ 522,972     \$27,161,486    \$1,021,268
  ------------------ ------- --------------- --------------- -------------- --------------- --------------

#  Summary and Conclusions

Erath County has the largest production milk in Texas. It accounts for
27% of all the production within the state. Revenues from milk
production within the county represent 79% of total agricultural income
in 2001. Milk sales for 2000 were estimated to be close to \$200 million
and the total income earned by dairy producers from all sources was
estimated at \$222 million. This study attempted to estimate the
economic impact of the dairy industry on the county and the state by
using a standard input-output model, IMPLAN.

A survey instrument was distributed to all the producers in the county
and after three mailings, forty out of 135 producers responded. They
represent almost 30% of all the existing producers, own 33% of the total
cows in the county, and produced 47% of total milk in the year 2000.
This survey data produced income and expense estimates and included
information to adjust for leakages at the county and state levels. A
"leakage" identifies the portion of expenditures that leaves an impact
area and has no further effect within that area. Since the state level
covers a larger economic area than the county level, a greater portion
of expenditures is captured at this level, resulting in less leakage at
the state level. The adjusted direct expenditures were then processed
through the input-output model -- IMPLAN to calculate the re-spending or
multiplier effects.

The overall multiplier for all expenditures was equal to 1.32. This is a
conservative and smaller multiplier compared to those obtained in
similar studies for this region and in other parts of the country
(Nielsen et.al, Jones et.al, Mulkey & Clouser). Applying this multiplier
to a total direct impact of \$223 million yields a total impact of
\$294.2 million. Adding the last figure to the combined total income of
\$222.4 million results in the total impact (from operating expenses
alone) equals \$516.6 million. Besides operating expenses, the study
also estimated the yearly "average" (averaged over five years) capital
expenditures incurred by dairy producers. The direct capital
expenditures were estimated at \$19.1 million and the indirect and
induced effects added another \$7.5 million for a total of \$26.6
million. Thus, the overall impact of the dairy industry in the county
amounts to **\$543.3 million**. This amount represents 36% of the total
output of the county. The dairy industry directly and indirectly creates
**5,912 jobs** and is responsible for 31% of the total employment. The
total value-added (income) in the dairy industry amounts to **\$123
million** which represents 18% of the personal income of the county.
This proportion parallels the contribution of the
Agriculture/Agribusiness sector to the national output. The dairy
producers directly paid over **\$900,000** in county taxes in 2001, 75%
of which were in the form of school taxes. In addition to the direct
taxes, the model also estimated that **\$9.4 million** in taxes were
generated stemming from all the direct and induced effects connected
with the dairy industry.

At the state level, the dairy industry contributed a total of \$**771.8
million** in output and provided (directly/indirectly) **10,926**
**jobs**. Once we subtract the impacts in Erath County, we note that the
dairy industry contributes to the rest of the state **\$228.5** million
in output and creates **5,014 jobs**.

The scope of this study limited the researchers to fail to recognize the
other dimensions linked to the dairy industry and merit further
research. A large dairy industry with Concentrated Animal Feed
Operations (CAFO's) is expected to create negative externalities such as
water and air pollution, overstress on roads and bridges (with the
continuous movement of inputs and milk), changes in land/property
values, long-term economic/social stability, etc. Lately, these negative
externalities have taken increased media and political attention. What
we hope to have accomplished in this study is to offer the community,
public-policy officials, and the dairy industry an economic perspective
of the dairy industry and its contributions to the economic well being
of the county.

# Appendixes

### Appendix A, Output and Job Creation Tables

##### Output Creation in Erath County

  ------------------ --------------- -------------- -------------- ---------------
  Event              Direct          Indirect       Induced        Total

  Operating Expenses \$190,876,693   \$31,251,920   \$27,411,505   \$249,540,118

  Wages              \$15,500,169    \$1,173,455    \$2,167,213    \$18,840,837

  Owners' Draw       \$3,150,845     \$235,006      \$421,411      \$3,807,261

  Total              \$209,527,707   \$32,660,381   \$29,578,718   \$272,188,217
  ------------------ --------------- -------------- -------------- ---------------

##### 

##### Output (Sales) Creation in Texas

  ------------------ --------------- -------------- --------------- ---------------
  Event              Direct          Indirect       Induced         Total

  Operating Expenses \$204,391,762   \$68,903,547   \$178,233,314   \$451,528,621

  Wages              \$15,500,169    \$3,217,604    \$3,059,945     \$21,777,719

  Owners' Draw       \$3,150,843     \$638,371      \$1,976,390     \$5,765,605

  Total              \$223,042,774   \$72,759,522   \$183,269,649   \$479,071,945
  ------------------ --------------- -------------- --------------- ---------------

##### 

##### Job-Creation in Texas

  -------------------------- ---------- ------------ ------------ ---------
  Event                      Direct     Indirect     Induced      Total

  Operating Expenses         5211       828          2131         8170

  Wages                      126        32           37           195

  Owners Draw                25         6            24           55

  Total                      5362       866          2192         8420
  -------------------------- ---------- ------------ ------------ ---------

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[^1]: In the survey instrument, replacement heifers were initially
    included as part of the capital expenses. However, the high
    frequency that producers responded incurring expenses for this item
    (almost on a yearly basis) suggested that the expenses for replacing
    heifers be moved from the capital to the operating sector.

[^2]: Wages and Owners' draw were estimated independently. The impact
    from these expenditures was linked with consumption patterns. All
    other operating expenses had production backward linkages.