June 2000

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Douglas E. Bowers

Executive Editor

Fred Gale

Issue Editor

Brenda Powell

Managing Editor

Anne E. Pearl

Art Director

Cover photo:

ERS/USDA
Rural Conditions and Trends, Vol. 10, No. 2 • 1



Rural Conditions and Trends

	



2 Overview

Nonfarm Growth and Structural Change Alter Farming’s Role in the

Rural Economy 

7 National Economy

World Growth and Weaker Dollar Expected To Boost Exports

10 Agriculture and the Rural Economy

Economic Growth in Farming Areas Lags the Rest of Rural America

Where Is Agriculture Important?

Farm Employment Losses Outstrip Job Gains in Farm-Related Industries 

in Some Nonmetro Areas

Agriculture’s Role Shrinks as the Service Economy Expands

Small and Large Farms Both Growing in Number

Bureau of Labor Statistics Data Provide More Complete Count 

of Young Farmers

Can Computer Use on the Farm Build Skills for Off-farm Jobs?

Contracting Changes How Farms Do Business

Urbanization Affects a Large Share of Farmland

64 The 1997 Economic Census

Economic Census Provides Detailed Picture of U.S. Industry

Semiconductor Industry Growing Rapidly

Completely Rural Montana Counties Lost Fewer Retail Dollars in 1997

76 Appendix A 

Data Sources 

78 Appendix B

Definitions

80 Appendix C 

Latest Trends in Nonfarm Jobs and Earnings

84 Appendix D 

Two Methods of Measuring Farm-Linked Employment

88 Appendix E

Economic Activity Triggered by Agricultural Trade
The rural economy continued to grow during the

late 1990’s, despite low

commodity prices that

caused economic problems in the farm sector.

The resiliency of the rural

economy is a reminder

that agriculture is not the

primary source of economic growth in rural

America. Growth in other

rural industries and structural changes in the farm

sector have reduced

farming’s importance and

altered traditional perceptions of farms. This issue

of Rural Conditions and

Trends examines the

changing role and character of farming and

other agriculturally related industries in the

United States.

Overview

2 • Rural Conditions and Trends, Vol. 10, No. 2

Low commodity prices and the Asian financial crisis buffeted rural America during thelate 1990’s, but the strength of the U.S. economy as a whole sustained the rural economy. Falling prices for many farm commodities have caused considerable hardship in

recent years, but the hardship has largely been confined to the farm sector and closely

related industries. USDA’s index of prices received by farmers for all crops fell to less than

90 (1990-92=100) in late 1999 (indicating that crop prices were more than 10 percent

below their level for the years 1990-92) after having reached 140 in 1996 (fig. 1). In most

rural communities, problems in the farm sector have not spilled over to cause a general

rural downturn. In fact, the rural unemployment rate fell at the same time crop prices were

falling, dropping to about 4.25 percent in 1999. Knowledgeable commentators quoted in

the news media and in financial publications have observed that some farmers, induced

by the combination of low farm prices and nonfarm job growth, have sold off their farm

assets and taken nonfarm jobs.

This issue of Rural Conditions and Trends examines the changing role of agriculture in

the rural economy. While many people view “rural” and “agriculture” as being virtually synonymous, the ability of the rural economy to shake off severe problems in the agricultural

sector is a reminder that agriculture is no longer the primary economic engine of rural

America. The articles in this issue draw upon a number of different research programs

and data sources from the Economic Research Service and other government agencies

to look at agriculture’s economic role from different perspectives.

Nonfarm Growth and Structural Change Alter

Farming’s Role in the Rural Economy 

1995 96 97 98 99

90

100

110

120

130

140

150

4.0

4.5

5.0

5.5

6.0

Index (1992-94=100) Unemployment (percent)

Crop

price index

Nonmetro

unemployment

rate

Figure 1

Prices received by farmers for all crops and nonmetro unemployment rate,1995-99

A downturn in crop prices buffeted the farm sector, but nonmetro unemployment declined, 

illustrating continued overall health of the rural economy

Source: ERS analysis of U.S. Department of Agriculture and Current Population Survey data.
Rural Conditions and Trends, Vol. 10, No. 2 • 3

Overview

While recent fluctuations in farm prices have had important short-term effects on U.S.

agriculture, this issue looks at how the role of agriculture in the rural economy has gradually evolved over the past several decades. Our definition of “agriculture” includes not only

farms, but also the complex system of businesses that manufacture, transport, and market

food and fiber products. This issue highlights two changes. First, the nonagricultural economy in rural America has grown steadily, outpacing growth in agriculture, so that agriculture’s relative importance as a source of jobs and income has been reduced. Second,

farms and agribusinesses are becoming closely integrated with the rest of the economy

as they respond to external pressures. Rising wages in other occupations draw workers

out of farming. Urbanization increases competition for use of farmland and constrains

farmers in how they operate their businesses. Health concerns and changing consumer

tastes give rise to demands for specific attributes in food products. As a result, agricultural

businesses no longer conform to traditional perceptions.

Agriculture’s Share of the Economy Shrinks

It is well known that over the past two centuries the United States has evolved from a

rural society with almost all of the population engaged in farming to a predominantly

urban society. The urban share of U.S. population rose from less than 10 percent in 1820

to about 75 percent in 1990, while the farm share of population fell from about 75 to 2

percent over the same period (fig. 2). While growth in population and income created new

demand for food and fiber as the Nation grew, growth in agriculture was limited by the fact

that demand for food grows more slowly than demand for other goods and services as

incomes rise. Other sectors expanded much more rapidly than agriculture. Furthermore,

farm productivity (output per unit of input) rose faster than the demand for food and fiber,

releasing labor and capital to be put to work in other industries. These two effects have

meant that the farm population did not have to grow as fast as the population it was supplying with food. As growth in farm productivity accelerated in the 20th century, the farm

population actually declined in absolute numbers after the 1930’s. ERS research has

Urban

Farm

Rural,

nonfarm

 Source: Census of Population data obtained from Woods and Poole Economics.

Percent

Figure 2

U.S. urban, farm, and rural nonfarm population shares, 1820-1990

The rural nonfarm share of U.S. population has been surprisingly stable

1820 1840 1860 1880 1900 1920 1940 1960 1980

0

20

40

60

80

100
Overview

4 • Rural Conditions and Trends, Vol. 10, No. 2

found that farm productivity rose an average of 1.9 percent from 1948 to 1994, one of the

fastest rates of growth of any sector (see M. Ahearn and others, Agricultural Productivity

in the United States, AIB-740, USDA/ERS, January 1998). The productivity of all farm

inputs rose, but increase in labor productivity was particularly rapid. The farm sector produced more than twice as much output in 1994 (in inflation-adjusted terms) as it did in

1948, but with only 29 percent as much labor.

High farm productivity benefits consumers by ensuring an abundant supply of food at low

prices. Other sectors (and ultimately consumers) benefit from farming’s efficient use of

resources, which frees up labor and capital for other industries (initially for manufacturing

in the 1940’s to 1960’s and more recently for service industries). Agricultural exports also

make an important contribution to the balance of trade. However, despite agriculture’s

important role, its share of the economy and the number of people that depend on it for

income and jobs is shrinking, both nationally and in rural areas. The Bureau of Labor

Statistics (BLS) projects a 1-percent decline in agricultural employment between 1998

and 2008 (see Allison Thomson, “Industry Output and Employment Projections to 2008,”

Monthly Labor Review, November 1999, pp. 33-50). BLS projects a 13-percent decline in

employment of farmers, the largest projected decline of any occupation. Employment of

farm workers is projected to decline 6.6 percent, and jobs in food and kindred products

manufacturing are projected to grow by only 2 percent. By comparison, nonfarm employment is projected to grow 14 percent between 1998 and 2008. Agricultural output is

expected to grow, but at a slower rate than that of most other industries.

The decline in farm population share shown in figure 2 reflects the movement of farm

labor into other sectors. What is less well known is that the rural nonfarm share remained

remarkably stable at around 22 percent. While farming is perhaps the most visible rural

activity, it is clearly not the only economic activity in rural America. There is enough activity in rural America to support over one-fifth of the Nation’s population, but farming supports only about 2-3 percent. Rural areas have created enough new economic opportunities to maintain a constant rural nonfarm share of population, but rural nonfarm jobs were

not created fast enough to absorb most of the labor released from the farm sector.

Consequently, the overall rural share of population fell. In recent decades, many small

communities built to serve the 19th century’s farm population have become nonviable due

to population loss and geographic concentration of fewer, larger firms supplying wider and

wider market areas. Much rural development activity is concerned with how to create jobs

in those communities.

Fewer Communities Rely on Farming

In most rural communities, nonfarm growth has reduced their economic dependence on

farming. However, farming is still a primary source of income and jobs in some areas,

mostly in sparsely populated areas of the Nation’s heartland. “Economic Growth in

Farming Areas Lags the Rest of Rural America,” in this issue, takes a look at how the

counties classified by ERS in 1989 as “farming dependent” have fared during the 1990’s.

The Nation’s economic expansion during the 1990’s appears to have reduced the number

of farming-dependent counties by adding jobs in manufacturing and services. (Definitional

changes in the way the data are reported since the 1989 classification make meaningful

comparisons over time problematic.) Counties that remained in the farming-dependent

category shared in the Nation’s economic growth during the 1990’s, but to a lesser extent

than other rural counties.

Of course, agriculture’s economic influence extends far beyond the farm gate. ERS produces two measures of employment in the more broadly defined agriculture sector: Food

and Fiber System and Farm and Farm-Related Employment. This issue includes articles

that report State-level changes in these agricultural job totals over the past two decades.

Both data series tell a similar story. Jobs in farming have declined steadily, while jobs in

food retail and wholesale sectors have grown. Retail and wholesale activities tend to

locate close to consumers, so much of the growth in agriculturally related employment

has occurred in more urbanized areas. Sparsely populated States, including those heavily
Rural Conditions and Trends, Vol. 10, No. 2 • 5

Overview

represented in the farming-dependent category, have gained relatively few retail and

wholesale jobs to offset their loss of farm jobs.

Faced with the continual loss of farm jobs, many rural areas have pursued value-added

development strategies that encourage agriculturally related businesses (food processing

and marketing) to choose rural locations. This strategy may be successful for some communities, but food processing does not appear promising as an engine for rural job

growth. Many types of food processors do not use raw farm commodities and choose

urban locations to gain access to suppliers of other inputs and distribution networks.

While rural areas gained jobs in food and other types of manufacturing during the 1990’s,

service industries have generated much of the recent job growth in both urban and rural

areas. The BLS employment projections cited earlier in this article predict an increase in

service jobs of 2.8 percent per year between 1998 and 2008, but job growth is not

expected to occur in most food manufacturing sectors.

External Pressures Reshape the Farm Sector

The agricultural sector is not a compartmentalized sector, distinct from the rest of the

economy. Like other businesses, farms are under pressure to raise productivity, adopt the

latest technologies, raise quality standards, respond to changing consumer tastes, and

exploit economies of scale. As they do so, farms are becoming more integrated into the

general economy. They are looking more like manufacturing businesses and less like traditional perceptions of “family farms.” The declining number of people who work primarily

in farming is one of the most noticeable effects of these pressures. “Small and Large

Farms Both Growing in Number” shows that the apparent stability in number of farms

between 1992 and 1997 hides differing underlying trends. Farms operated by people who

consider farming their principal occupation continued to fall between 1992 and 1997,

while the number of farms operated by people primarily employed elsewhere rose. Much

of the adjustment in farm numbers occurs through a demographic process, as fewer new

young farmers enter to replace retiring farmers. BLS data measuring the number of people employed in farming by age group provide a more accurate count of young farmers,

who are often missed by the census, but this data series also shows a decline in young

farmers.

Computers have revolutionized the way most businesses operate in the 1990’s. But analysis in this issue suggests that relatively few farms have taken full advantage of information technology. USDA survey data from 1999 show that more than 40 percent of farms

have computers, but less than one-fourth have incorporated computers into their business

operations. Most seem to have adopted computers piecemeal for bookkeeping or other

applications without using information systems to integrate production, marketing, and

financial data. Full use of computer technology can improve efficiency of farm operations

and give farm household members the skills they need to compete for well-paid jobs outside the farm sector.

Another notable trend in agriculture is the increased use of marketing and production

contracts. Contracting is not a new phenomenon, but it has become more prevalent in

some sectors, most notably the hog sector. Many processors have turned to contracting

in order to increase efficiency and ensure steady supply of commodities with attributes

needed for specific food products demanded by consumers. Contracting changes the way

farms operate, reducing farm operators’ independence and forging closer ties to agribusinesses. Contracting has been associated with geographic shifts in production of hogs and

other commodities, and large livestock operations associated with this trend have created

environmental concerns.

Nonfarm sectors have been drawing labor out of agriculture for decades while the agricultural land base has remained relatively stable. In recent years, however, conflicts over

urban encroachment on farmland have arisen in more rural communities. ERS research

reported in this issue estimates that urbanization pressures from residential, commercial,

and industrial development drive up farmland values by 25 percent, on average. For the

17 percent of farmland classified by ERS as “urban-influenced,” urbanization effects
Overview

6 • Rural Conditions and Trends, Vol. 10, No. 2

account for about two-thirds of per acre land value. Urbanization affects geographic patterns of farm production, encourages growth in the number of small farms, and leads to

conflicts over waste disposal, chemical use, odors, water quality, and other issues.

Farmland protection is an important concern for policymakers in Federal, State, and local

governments.

Economic Census Data Provide a Snapshot of U.S. Industry

This issue also reports on how new 1997 Economic Census data can be used to analyze

trends in rural industry. The Census Bureau began publishing the data in 1999 and will

continue publishing reports through 2000 and 2001. One article describes the data and

the new North American Industrial Classification System (NAICS) that replaces the

Standard Industrial Classification (SIC). Two additional articles provide examples of how

Economic Census data can be used to analyze manufacturing and retail industries.

This issue reports the most recent data on nonmetro earnings and employment, farmand farm-related employment, food and fiber system employment, and jobs related to

agricultural trade. Between 1996 and 1997, the most recent years available, nonmetro

employment grew by 2.0 percent, slightly slower than metro growth of 2.3 percent. All

nonfarm, nonmetro sectors and regions added jobs in 1997. The agricultural services,

forestry, fishing, and other category had the fastest growth in jobs, followed by the

finance, insurance, and real estate, and transportation and public utilities sectors. Both

metro and nonmetro job growth was fastest in the Rocky Mountain, Southwest, and Far

West regions. Nonmetro earnings per job also grew in all sectors except transportation

and public utilities. Earnings growth was fastest in manufacturing and wholesale trade, the

only sectors where earnings per job grew more than 2 percent in 1997. Earnings per job

grew in all regions, but at a slower rate than metro earnings. Overall, nonmetro real earnings per job grew 1.3 percent, the first increase following several years of small declines

from 1993 to 1996. [Fred Gale, 202-694-5349, fgale@ers.usda.gov]
The world economy was

in a recession in 1998

because of the global

financial crisis, but the

U.S. economy continued

to grow due to low interest rates, low oil prices,

and solid productivity

growth. However, the

U.S. trade deficit

increased sharply in

1998 and 1999, negatively affecting the goodsproducing sector, particularly, agriculture and

manufacturing. U.S. agricultural exports dropped

partly due to a strong

dollar and weak world

growth as well as record

large world supplies.

Although nonmetro

employment growth

dipped in 1997-98, the

nonmetro United States

did not experience lasting

damage from the global

financial crisis. Based on

most indicators, the world

economy is clearly on the

road to recovery with

improvement in U.S. nonmetro employment and

farm exports expected in

2000.

Rural Conditions and Trends, Vol. 10, No. 2 • 7

National Economy

The world financial crisis began in the summer of 1997 with a sharp devaluation of theThai currency. The crisis spread to other countries of East and South Asia, Russia,

and Brazil. A huge outflow of investment funds from these and other developing countries

resulted in a world recession in 1998. Investment funds flowed into the United States as a

safe haven. As a result, the value of the dollar rose and long-term U.S. interest rates fell

sharply (fig. 1). Further, weak world growth and failure of Organization of Petroleum

Exporting Counties (OPEC) discipline resulted in low oil prices at the end of 1998—the

lowest in real terms since 1947.

The quick turnaround in Asian and world growth was crucially dependent on a strong U.S.

economy absorbing increasing trade deficits. Japan, a major trading partner of the affected Asian countries, and Europe were experiencing sluggish growth. If the United States

had not been able to absorb the imports that were needed to boost the Asian economies,

no other country could have.

Overall, the U.S. economy was the locomotive that pulled the world out of recession. The

already fully employed U.S. economy continued to expand in 1998 and 1999 at about a 4-

percent growth rate for gross domestic product (GDP), with inflation at about 2 percent.

The strong dollar kept imported goods prices low while low oil prices provided a boost to

the supply side of the economy and further constrained inflation. Real compensation rose

with no rise in inflation due to low input price inflation, to oil price declines, and to solid

U.S. productivity growth from expanded and more effective business computer usage

along with a high rate of capital growth. Increasing compensation, low interest rates, and

rising household wealth spurred rapid consumer spending growth. Low interest rates and

World Growth and Weaker Dollar Expected To

Boost Exports

1995 96 97 98 99

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

40

60

80

100

Exchange rate

 (Index, 1973=100)

Figure 1

Treasury bond yields and value of the U.S. dollar, 1995-99

Long-term interest rates reversed their decline in 1999 as growth in the value of the 

dollar stalled

Exchange value

of U.S. dollar

10-year treasury bond yield

 Note: Exchange rate is a trade-weighted index of the value of the dollar against major currencies,

not adjusted for inflation. The index equaled 100 in March 1973.

 Source: Federal Reserve Board.

Bond yield

(percent)
National Economy

8 • Rural Conditions and Trends, Vol. 10, No. 2

strong equity prices allowed continued growth in business investment spending. As a

result, growth continued unabated despite a sharply rising trade deficit.

Still, the major goods-producing sectors—agriculture, manufacturing, and mining—were

hurt by the strong dollar and weak world growth. Exports stagnated as U.S. goods were

increasingly expensive on world markets, and our foreign customers often lacked the

income to afford our exported products.

U.S. agricultural exports were especially hard-hit as the world already had large surpluses

of many bulk commodities. In fiscal year 1998, farm exports dropped to $53.7 billion,

down from $57.4 billion in fiscal 1997. Farm exports for fiscal 1999, which ended in

September, are estimated to fall further to $49 billion. The declines are concentrated in

bulk-goods exports, such as feed grains and oilseeds, while high-valued product exports

appear to be largely unaffected.

Prices received by farmers reflected the weakness of bulk goods markets. The index of

prices of all crops went from 127 in 1996 (index value 1990-92=100) to 116 in 1997, and

fell further to 107 in 1998. But prices for food grains, which are largely exported, showed

even more weakness, as the index fell from 157 in 1996 to 128 in 1997, and then

declined sharply to 107 in 1998. In particular, wheat prices went from $4.30 per bushel in

1996 to $3.38 in 1997, and then dropped to $2.70 in 1998. Feed grains prices were also

hard hit, dropping 46 percent over 2 years.

High-value farm product prices were relatively unaffected partly because of smaller export

market shares of total production and continued high export demand. High-value farm

products include both certain agricultural commodities, such as fruits and nuts, and

processed agricultural products, such as cigarettes and snack foods. For example, prices

received by farmers for fruits and nuts dropped slightly between 1996-98. Commercial

vegetables, grown to be sold as fresh produce or to be processed, saw prices rise almost

10 percent between 1996-98. Prices for processed fruits and vegetables stayed essentially level over the crisis period.

Nonmetro Labor Market Bounces Back After Crisis

The crisis brought a decline in goods export growth in 1997 followed by a sharp drop in

early 1998 (fig. 2). Nonmetro employment growth declined along with goods export

growth. As goods exports rebounded in late 1998 and the global financial crisis ended,

the shock to the nonmetro labor market subsided. Metro labor markets were largely unaffected. Since the metro labor force is about 80 percent of the U.S. labor force, nationallevel employment continued to grow and the unemployment rate declined to 4.1 percent

in October 1999—a 30-year low.

Food processing is one industry that mitigated the negative impact of the crisis on nonmetro areas. Employment in food processing is disproportionately rural, as 37 percent of

the 1.8 million food processing workers live in nonmetro areas. The export category

foods, feeds, and beverages, which has a high proportion of processed products, peaked

in real dollar value in 1995 at $56.4 billion (1996 dollars) and dropped slightly to $55.5 billion in 1996. During the 1997-99 global financial crisis, exports of foods, feeds, and beverages stayed relatively high, with only modest declines, consistent with low impact that the

crisis had on high-value agricultural exports.

At the start of the crisis, some analysts compared what was happening with the severe

debt crisis of the 1980’s. That debt crisis created lingering effects on the U.S. financial situation: high interest rates, a high-valued dollar, and continuing softness of the U.S. banking system. In particular, the very high-valued dollar made U.S. goods more expensive

abroad. That debt crisis hit nonmetro areas disproportionately hard. Nonmetro unemployment did not recover to 1979 levels until 1989. In addition, farm real estate prices peaked

in 1982 at $823 per acre, a price not again reached until 1995 when the average acre

sold for $844. Although the 1997-99 global financial crisis did indeed result in a higher

valued dollar, its rise was brief, small, and not associated with higher interest rates, which 
Rural Conditions and Trends, Vol. 10, No. 2 • 9

National Economy

could have pushed the value of the dollar even higher. Consequently, the net impact on

the rural economy was brief and shallow.

Prospects for Goods Sector Recovery in 2000

The U.S. economy is expected to slow in 2000 due to moderating consumer and business

investment spending. The slower spending growth will be partly offset by a falling trade

deficit, reflecting improvements of manufacturing export prospects.

Manufactured goods exports are expected to rise in 2000 due to improved world growth

and a weaker dollar. Low inflation and interest rates, albeit somewhat higher than in 1998

and early 1999, and continued productivity growth will keep manufacturing profitable.

[Data as of 12/16/1999. David Torgerson, 202-694-5334, dtorg@ers.usda.gov; Karen S.

Hamrick, 202-694-5426, khamrick@ers.usda.gov] 

1995 96 97 98 99

-1

0

1

2

3

4

-10

0

10

20

30

40

Employment growth 

(percent)

Export growth

(percent)

Figure 2

Annualized growth rates of nonmetro employment and goods exports, 1995-99

Growth slowed during the 1997-99 global financial crisis

Note: Export growth adjusted for inflation, constant 1996 dollars.

Source: ERS analysis of U.S. Department of Commerce and Bureau of Labor Statistics data.

Goods exports

Nonmetro

employment
Fewer counties depend

on farming for a large

share of their income

than was once the case.

Growth in employment

and population has

lagged other nonmetro

areas, as many farming

counties struggle to

adapt to a changing rural

economic landscape.

Retaining population,

enhancing off-farm job

opportunities, and providing public services will be

pivotal determinants of

the future of farming

counties.

Agriculture and the Rural Economy

10 • Rural Conditions and Trends, Vol. 10, No. 2

Farming areas have participated in the 1990’s overall employment and populationgrowth but not to the extent of other nonmetro areas. Population in many farming

areas is still declining. Shrinking local economies spell continued uncertainty for sparsely

settled farming communities unless nonfarm jobs are added.

The proportion of total labor and proprietor income (LPI) that comes from farming in nonmetro economies declined substantially through the mid-1980’s but has remained relatively stable in the 1990’s (fig. 1). Since the early 1980’s, ERS has used this measure as an

indicator of the relative importance of farming to local economies. Increased productivity

and structural change in the farming sector has contributed to continued decline in farm

employment since 1935, and the decline is expected to continue for the foreseeable

future. Growth in the number of nonfarm businesses, first manufacturing and then services, has greatly expanded the rural employment base. Thus, farming is no longer a

dominant source of jobs or income in most rural communities as it was 50 years ago.

Farming contributes 10 percent or more of county-earned income for about one-fourth of

nonmetro counties, clustered largely in our Nation’s heartland (fig. 2). These are the communities likely to be affected the most by changes in farm financial conditions. Not only

does farming have a relatively large economic presence, but the farm commodities produced are those most susceptible to price fluctuations in international markets. Federal

agricultural commodity programs have historically played an important role in the farm

economy of these counties. Many farming areas have not participated in the industrial

diversification of America’s rural economy. Therefore, they have a unique economic personality. At the same time, they represent a remnant of rural America’s past.

Economic Growth in Farming Areas Lags the

Rest of Rural America

19 75 80 85 90 95

0

2

4

6

8

10

12

14

16

18

Nonmetro

Metro

Percent

Note: Chart shows the proportion of total labor and proprietor income (LPI) that comes from farming.

Source: ERS analysis of data from the Bureau of Economic Analysis.

1970

Figure 1

Farming share of local personal income, metro and nonmetro counties, 1969-97

The share of income from farming has been relatively steady during the 1990's
Rural Conditions and Trends, Vol. 10, No. 2 • 11

Agriculture and the Rural Economy

We look at two groups of counties with relatively high dependence on farming. ERS classifies nonmetro counties that obtain at least 20 percent of LPI from farming as “farmingdependent.” In the mid-1990’s, there were 316 counties in the farming-dependent category, down from 556 in 1989. Another 312 nonmetro counties have a farm income share of

10 to 19.9 percent, and are classified as “farming important” (see box, “Farm Income

Share Used To Classify Counties”).

Farming-Dependent Counties Experience the Slowest Growth

Average county per capita income in farming-dependent counties is higher than in other

nonmetro areas (table 1). Earned income contributes about 62 percent of total personal

income, while the remainder comes from unearned sources such as dividends, interest,

and rent and transfer payments. Farming in these counties contributes about 30 percent

of earned income, a percentage that has remained relatively constant throughout the

1990’s. It continues to be true that average farm earnings are higher in farming-dependent counties. Average earnings per farm job were $34,300 in farming-dependent counties, compared with $14,550 for the rest of nonmetro counties in 1997. The average farm

(measured by total value of agricultural products sold) is larger in farming-dependent

counties (table 2). Farms in these counties produced 18.2 percent of all agricultural products sold in 1997. With relatively few nonfarm jobs available in farming-dependent coun-



 Farming dependent (20% or more)

 Farming important (10% to 19.9%)

 Metro

 Note: Farming-dependent counties derived at least 20 percent of labor and proprietor income

(LPI) from farming. Farming-important counties derived 10 to 19 percent of LPI from farming.

 Source: Prepared by ERS using data from the Bureau of Economic Analysis.

Figure 2

Nonmetro counties with at least 10 percent of income from farming

Most counties that rely on farming are in the Nation's heartland
Agriculture and the Rural Economy

12 • Rural Conditions and Trends, Vol. 10, No. 2

Table 1

Characteristics of counties by farming dependence

The more dependent a county was on farming, the less it participated in employment and population growth in the 1990’s

Farming- Farming- Other

Item dependent important nonmetro

Number

Number of counties 316 312 1,662

Thousands

Total employment, 1997 1,347 2,328 24,359

Employment by industry:1 Percent

Goods producing— 37.2 35.9 29.5

Farming 18.3 12.0 5.3

Manufacturing 10.6 15.7 16.2

Other 8.4 8.2 7.9

Services— 61.1 62.3 68.7

Business services2 12.3 11.8 11.7

Retail trade 14.0 15.5 17.6

Government 16.1 15.2 15.9

Other 18.7 19.8 23.5

Employment change, 1980-90 -1.6 6.8 14.1

Employment change, 1990-97 11.3 13.6 14.1

Employment change by industry:

Goods producing— 4.4 6.4 3.7

Farming -6.4 -6.8 -6.9

Manufacturing 12.4 14.5 4.4

Other 24.7 14.6 10.5

Services— 13.9 16.8 17.7

Business services2 9.2 12.6 14.4

Retail trade 20.1 20.4 21.2

Government 7.2 8.9 6.9

Other 19.0 23.7 25.2

Dollars

Average per capita income, 1997 19,413 18,489 19,131

Thousands

Population, 1998 2,692 4,631 47,218 

Population change: Percent

1990-98 2.6 6.1 7.4

1980-90 -6.5 -1.5 3.8

Net migration:

1990-98 .9 3.4 4.4

1980-90 -10.6 -6.5 -1.9

Proportion of counties with population loss:

1990-98 57.6 39.4 21.0

1980-90 85.8 71.2 44.9

1Percentages do not sum to 100, due to suppression.

2Includes transportation, public utilities, wholesale trade, finance, insurance, and real estate.

Source: ERS analysis of data from the Bureau of Economic Analysis and the Bureau of the Census.
Rural Conditions and Trends, Vol. 10, No. 2 • 13

Agriculture and the Rural Economy

ties, farm operators are more likely to expand the size of their farms in order to maintain

household income. As a result, the number of farms in these counties declined by 12.5

percent between 1987 and 1997, while the average farm’s sales have increased by 78

percent, according to the Census of Agriculture.

As a group, farming-dependent counties experienced 11.3 percent job growth during

1990-97. This is in sharp contrast to the employment declines in these counties during

the 1980’s, although farming-dependent counties added jobs at a slower rate than other

nonmetro areas (table 1). And job growth during the 1990’s has not been in farming: farming-dependent counties lost farm jobs at a rate of 6.4 percent in 1990-97. Growth has

occurred, however, in agricultural services, manufacturing, and services.

As a whole, goods-producing industries (farming, agricultural services, manufacturing,

mining, and construction) provide a higher proportion of jobs in farming-dependent counties than in the other county types—although farming-dependent counties have relatively

few manufacturing jobs. It follows that service sector jobs are a smaller share of employment in farming-dependent counties. The relative scarcity of service jobs in these counties is in large part responsible for their weak employment growth, since growth in service

sector jobs drove overall employment growth in the 1990’s.

While over 60 percent of jobs are in service industries, service jobs contribute only half of

earned income, suggesting that wages in this sector are relatively low. In fact, earnings

per service job in farming-dependent counties were only 87 percent of the rest of nonmetro counties. Farming-dependent counties have a smaller proportion of service jobs in

retail trade and other services (which include health, educational, recreational, and social

services). This likely reflects the small and shrinking population base in many farmingdependent counties.

About 2.7 million people (5 percent of the nonmetro population) lived in farming-dependent counties in 1998. Population growth between 1990 and 1998 averaged 2.6 percent.

About one-third of this growth was due to net migration; the remainder was due to natural

increase (births exceeding deaths). This is a sharp turnaround from the 6.5-percent population decline of the 1980’s, a period of heavy population outmigration. Counties that have

grown are located in the eastern part of the Corn Belt, the South, and the Rocky

Mountains where nonfarm job opportunities are growing or where people are migrating in

order to enjoy scenic landscapes. Some farming-dependent counties located along the

Platte River in Nebraska and around Garden City, Kansas, have grown as a result of new

jobs in meatpacking. Value-added manufacturing such as meatpacking has helped some

Table 2

Characteristics of farms by county farming dependence, 1987-97

The more dependent a county was on farming, the larger the decline in the number of farms and

the increase in sales per farm

Farming- Farming- Other

Item Unit dependent important nonmetro

Farms, 1997 Thousands 166.3 186.2 940.2

Share of all farms Percent 8.7 9.7 49.2

Farms, 1987 Thousands 190.0 208.2 1,007.7

Change in farms, 1987-97 Thousands -12.5 -10.6 -6.7

Market value of agricultural 

products sold, 1997 Billion dollars 35.9 27.9 66.4

Average sales per farm, 1997 1,000 dollars 233.9 161.2 69.2

Average sales per farm, 1987 1,000 dollars 131.6 94.8 46.0

Average land area in farms, 1997 Percent 78.4 66.5 34.4

Source: ERS analysis of data from the Census of Agriculture.
Agriculture and the Rural Economy

14 • Rural Conditions and Trends, Vol. 10, No. 2

farming areas expand their employment base and attract immigrants. Nevertheless, more

than half of farming-dependent counties lost population during the 1990’s. Those losing

population were in the Plains, an area that has been losing population for decades.

It appears that many farming-dependent counties will have difficulty maintaining a large

enough population base to support community services. Economic growth during the

1990’s has favored more urban places, even within nonmetro America. Many farmingdependent counties are remote from urban growth nodes, and have low population densities. There is, however, some evidence that telecommunications has helped to overcome

the distance problem, particularly for farming-dependent counties in the Rocky Mountains,

which offer scenic beauty often sought by migrants to rural areas.

Farming-Important Counties Fare Better 

Jobs grew faster in farming-important counties than in farming-dependent counties during

1990-97. Employment grew 13.6 percent, double the growth rate during the 1980’s. Most

farming-important counties are adjacent to farming-dependent counties, and some were

formerly classified as farming-dependent counties in 1989. Manufacturing has a larger

presence in these counties, as does the service sector. This suggests that farming-important counties have been able to expand their nonfarm employment base in order to retain

or attract population. For these counties, strong job growth in manufacturing and services

(especially health, educational, and recreational services) offset lost jobs in farming.

Farms in farming-important counties produced about 14 percent of the Nation’s agricultural products in 1997. The number of farms in these counties declined by 10.6 percent over

the 1987-97 period, slower than the decline in farming-dependent counties. The availability of off-farm jobs often helps farm households maintain income while continuing farming.

Relative to farming-dependent counties, farming-important counties have experienced

robust population growth during the 1990’s. Net inmigration has contributed over half this

growth. Places like the Ozark-Ouachita Mountains in Arkansas and the Rocky Mountain

Front offer natural amenities sought by rural inmigrants. Still, about 40 percent of the

farming-important counties, many in the High Plains, continued to lose population during

the decade.

Number of Farming-Dependent Counties Declined Since 1989

ERS last identified farming-dependent counties in 1989, using farm earnings over the

1987-89 period. Of the previous 556 farming-dependent counties, 275 are included in our

updated analysis. Thus, 281 counties previously defined as farming-dependent are not so

classified in this article. Of these 281 counties, 134 are now classified as farming-important. Rapid growth in manufacturing jobs is the one feature that differentiates these counties from our farming-dependent counties. Another 104 counties moved out of our two

farming groups altogether. Job growth in these counties was unusually high in other services (health, educational, recreational, and social services) and other goods-producing

(construction and mining) sectors. Finally, 43 former farming-dependent counties had

negative farm earnings (farm losses) during 1994, 1996, and 1997. Given that over a fifth

of their total employment is in farming, these sparsely settled counties would likely be

classified as farming-dependent had the farm losses not occurred.

Forty-one new counties joined our farming-dependent category. These counties resemble

our farming-important group in terms of employment structure and population size. A

number of counties have a ratio of farm LPI to total LPI that is close to 20 percent. Thus,

a small change in either farm earnings or nonfarm earnings could shift a county into farming-dependent status. [Kathleen Kassel, 202-694-5428, kkassel@ers.usda.gov; Thomas

Carlin, 202-694-5406, tcarlin@ers.usda.gov]
Rural Conditions and Trends, Vol. 10, No. 2 • 15

Agriculture and the Rural Economy

Farm Income Share Used To Classify Counties

The Bureau of Economic Analysis, U.S. Department of Commerce, compiled the data used to

classify counties. Farm labor and proprietor income includes the net income of farm operators

(proprietors) and wages paid persons employed on farms. Total labor and proprietor income

(LPI) includes the earnings of all proprietorship business (farm and nonfarm) in the county plus

wages paid all persons working in the county. LPI also includes some nonwage but work-related income items such as employer contributions to life and health insurance.

Farming-Dependent Counties are the 316 counties where farming constituted 20 percent or

more of a county’s LPI in 1994, 1996, and 1997. Farming-Important Counties are the 312 counties where farming constituted 10-19 percent of LPI for those years. A 3-year average was used

to “smooth over” year-to-year variability in farm income. The years chosen had the highest net

income in the 1990’s. Because of unusual conditions that reduced farm income in 1995, data

from that year were excluded. A cool, wet spring delayed planting of many crops, and hot summer weather and an early frost also reduced crop production. Corn production, for example,

declined by 25 percent from the 1994 record crop. Carryover stocks were rather large coming

into the year. Thus, when output declined, inventories were drawn down, further lowering net

farm income. Also, livestock prices fell throughout the year.

Replicating the earlier ERS classification using more recent revised Bureau of Economic

Analysis (BEA) data yields 406 farming-dependent counties in 1987-89, not 556. Revisions in

the data account for over half of the 281-county decrease in the number of farming-dependent

counties. BEA continually revises county income estimates (both farm and nonfarm) as new

information becomes available or as new estimating procedures are introduced. Even after

adjusting for data revisions, the decline in the number of farming-dependent counties is substantial, particularly given that we chose the years with the highest farm income during the

1990’s for analysis.

Our measure is a gauge of the importance of farming to the local economy. It is not a measure

of the top agricultural counties in the Nation, as might be measured by the market value of

agricultural products sold from farms (see fig. 3). There are, however, overlaps between the two

concepts. For example, Iowa has 60 counties—clustered in the northern region of the State—

among the top quintile of nonmetro counties ranked by the market value of agricultural products sold in 1997. Of these, 50 are also classified as farming-dependent or farming-important

counties. On the other hand, most of the nonmetro counties in eastern South Dakota are farming-dependent or farming-important, but few of them are in the top quintile of nonmetro counties ranked by farm sales.
Agriculture and the Rural Economy

16 • Rural Conditions and Trends, Vol. 10, No. 2

 Top quintile

 Metro

Note: Chart shows the top 20 percent of nonmetro counties ranked by market value of agricultural production.

Source: Prepared by ERS using data from the Census of Agriculture.

Figure 3

Leading nonmetro counties in market value of agricultural products sold, 1997

Many but not all farming-dependent and farming-important counties (see fig. 2) are top ranked in sales
More than one in six U.S.

jobs stem from agriculture. Even in nonfarm

States, a substantial portion of jobs are in the

food and fiber system.

There are several ways

of measuring the dependence of a State’s economy on agriculture. We

present several alternatives and compare these

estimates of dependence

in 1997 with similar estimates of 1981 conditions.

Rural Conditions and Trends, Vol. 10, No. 2 • 17

Agriculture and the Rural Economy

Rural development planners, rural legislators, agricultural college deans, and representatives from agricultural commodity groups all at some time or another have

expressed interest in measuring the importance of agriculture in a particular State. They

often want to compare agriculture’s importance in different States. To address this concern, we derived estimates of agriculture’s importance for all States using common estimation procedures and data.

To measure the importance of agriculture, we estimated the supporting economic activity

required to produce farm products and move them to products ready for consumers. We

included the activity that produces farm inputs (fertilizer, manufactured feeds, etc.), farm

production, and assembling, processing, and distributing raw farm products for final consumption by domestic and foreign consumers—activities that make up the U.S. food and

fiber system (FFS). Several factors help make agriculture important to a State’s economy—a viable farm economy, a concentration of sector-supporting industries, and a relative scarcity of nonagricultural economic activity.

Size Versus Share of Economy

California illustrates the classification dilemma. It is the leading producer of many commodities, has many successful commercial farms, and has a strong base of farm-supporting industries. As a result, California has the largest number of workers who owe their

jobs to agriculture—2.7 million. The size of its FFS workforce makes it the leading State in

the national food and fiber system. But California is not an agriculturally dependent State.

With a total labor force of 16 million, agriculture accounts for a smaller share of the

State’s economy (16.9 percent of civilian workforce) than its national share (17.8 percent

of civilian workforce).

In contrast, consider the Dakotas. Their FFS employment is between 89,000 and 97,000,

half of it farmers and farm workers, and FFS jobs account for more than 25 percent of all

jobs in each State. FFS jobs are very important in the Dakotas, although the combined

total FFS employment in these States accounts for less than 1 percent of U.S. employment in the food and fiber system.

How do you tell how important agriculture is to your State? In an earlier article, we

addressed this question using 1981 data (see Gerald Schluter and William Edmondson,

“How to Tell How Important Agriculture Is to Your State,” Rural Development Perspectives,

Vol. 2, No. 3, June 1986). We concluded that the importance measure depends upon what

you are looking for. This article uses 1997 data to revisit our earlier analysis. We include

estimates of each State’s FFS employment in 1997 and 1981 (table 1), the FFS’s share of

total State workforce (fig.1) and of the relative importance of selected groups of workers

in the region’s FFS workforce.

Table 1 shows FFS jobs for 1981 and 1997 by State, while figure 1 shows FFS employment proportions of total civilian employment for each State. Between 1981 and 1997,

total FFS employment rose by 3 million workers, from 21.3 to 24.3 million. Not all States

shared in this growth. Nine States lost workers involved in producing, assembling, and

processing raw farm products and in industries that distribute those products to domestic

and foreign consumers. The loss of FFS employment followed no particular pattern.

States with large FFS workforces lost jobs (New York, Pennsylvania), as did States where

the share of FFS employment was high (North Dakota and South Dakota). States in similar groupings gained employment. Nebraska, for instance, had the highest percentage of

FFS workers in its State workforce in 1997 and also saw its FFS employment increase

nearly 28 percent from 1981 to 1997. California, the State with the largest FFS employWhere Is Agriculture Important?
Agriculture and the Rural Economy

18 • Rural Conditions and Trends, Vol. 10, No. 2

Table 1

Food and fiber system employment by State, 1981 and 1997

California was the leading State in food and fiber system employment for both 1981 and 1997

1981-97,

1997 1997 1981 1981 Percent

State Employment Ranking Employment Ranking change1

1,000 workers 1,000 workers 1981-97

Alabama 425.8 20 380.2 19 12.0

Alaska 53.2 50 34.7 51 53.4

Arizona 359.4 26 218.7 32 64.3

Arkansas 270.8 31 213.9 33 26.6

California 2,701.3 1 2,160.2 1 25.1

Colorado 396.5 23 299.6 26 32.4

Connecticut 259.4 32 251.0 30 3.3

Delaware 76.5 47 56.4 48 35.6

District of Columbia 63.4 48 68.8 47 -7.9

Florida 1,286.2 4 858.8 7 49.8

Georgia 774.6 10 623.8 11 24.2

Hawaii 114.4 40 103.4 40 10.7

Idaho 133.6 38 107.2 38 24.6

Illinois 1,112.3 5 1,044.2 5 6.5

Indiana 560.5 14 465.6 18 20.4

Iowa 380.9 25 361.0 23 5.5

Kansas 304.1 29 276.7 28 9.9

Kentucky 400.5 22 330.4 25 21.2

Louisiana 351.2 27 378.1 20 -7.1

Maine 111.7 41 110.3 37 1.2

Maryland 410.4 21 368.5 22 11.4

Massachusetts 526.8 16 523.8 13 .6

Michigan 794.9 9 640.2 9 24.2

Minnesota 510.3 19 478.4 17 6.7

Mississippi 235.2 34 221.9 31 6.0

Missouri 518.1 18 521.9 15 -.7

Montana 89.7 44 82.4 43 8.9

Nebraska 255.6 33 199.7 34 28.0

Nevada 136.1 37 69.5 46 95.9

New Hampshire 103.3 42 81.4 44 26.9

New Jersey 647.4 11 630.7 10 2.6

New Mexico 136.8 36 106.9 39 28.0

New York 1,351.7 3 1,472.0 2 -8.2

North Carolina 907.7 8 789.5 8 15.0

North Dakota 89.5 45 90.3 42 -.9

Ohio 999.9 7 872.6 6 14.6

Oklahoma 278.0 30 298.8 27 -6.9

Oregon 304.5 28 252.7 29 20.5

Pennsylvania 1,044.3 6 1,068.2 4 -2.2

Rhode Island 76.6 46 76.0 45 .7

South Carolina 382.6 24 353.3 24 8.3

South Dakota 97.4 43 98.2 41 -.8

Tennessee 543.2 15 487.0 16 11.5

Texas 1,639.5 2 1,405.9 3 16.6

Utah 173.2 35 120.9 36 43.3

Vermont 57.1 49 43.7 50 30.7

Virginia 617.2 12 546.9 12 12.9

Washington 524.6 17 374.1 21 40.2

West Virginia 127.2 39 134.5 35 -5.4

Wisconsin 562.5 13 522.4 14 7.7

Wyoming 49.1 51 44.7 49 9.9

United States 24,326.8 NA 21,320.0 NA 14.1

NA = Not applicable.

1Percentage change in food and fiber system employment from 1981 to 1997.

Source: ERS analysis of U.S. Department of Commerce data.
Rural Conditions and Trends, Vol. 10, No. 2 • 19

Agriculture and the Rural Economy

ment, saw its FFS employment grow 25 percent from 1981 to 1997. In general, FFS

employment accounts for a larger share of total employment in rural States with relatively

weak combined manufacturing, forestry, and mining sectors.

The FFS is important to all States. Nationally, the FFS accounts for 17.8 percent of total

employment. Among the States, the share ranges from 14.7 percent in Maryland to 28.2

percent in Nebraska, but in nearly two-thirds of the States the FFS employment share of

total employment is between 15 and 20 percent. Contributing to this grouping is a growing

trend to more of the FFS jobs being at the consumer end of the FFS delivery chain.

These jobs tend to be in transportation, wholesale and retail trade, and food service. As

we see in table 2, employment in these sectors is more evenly distributed regionally.

Composition of FFS Employment Varies by Region

While table 1 emphasizes the level of employment, table 2 illustrates how the sectoral mix

of FFS employment varies regionally. As in 1981, farming and food processing jobs are

more important in the Midwest. Textile manufacturing jobs accounted for more than 7 percent of FFS jobs in the South. FFS manufacturing jobs other than food processing and

textile manufacturing were relatively more important in the Northeast and North Central

regions.

17.9

18.4

16.9

16.5

19.2

16.9

15.4

16.8

16.6

17.4

22.2

19.6

21.1

16.7

17.6

17.6

19.7

24.1 28.2

25.7

25.0

19.4

18.2

20.9

18.6

17.4

22.3

20.1

18.0

19.6 19.8

18.1

18.1

23.6

19.8

17.5

17.5

15.8

16.0

19.1 15.3

15.0

16.2

16.9

FFS share 

 14 - 16 percent

 17 - 19 percent

 20 percent or higher

Figure 1

Food and fiber system share of employment by State, 1997

States in the Great Plains have the highest share of jobs in the food and fiber system

Source: ERS analysis of U.S. Department of Commerce data.

17.5

16.0

15.2

15.4

20.0

14.7
Agriculture and the Rural Economy

20 • Rural Conditions and Trends, Vol. 10, No. 2

Alternate Views of Agricultural Dependency 

Which States are agriculturally dependent? In our previous article, we chose four possible

criteria and listed the 10 top States for 1981 under those criteria (see box, “Ranking

States by Dependence on Agriculture). If one defines importance as the total FFS workers within a State, then the most important States are those listed in the upper left of the

box. If one defines importance as the share of the State’s employment accounted for by

the FFS workers, then the most important States are those listed in the upper right of the

box. If one’s interest is in farm workers rather than FFS workers, the lower part of the box

gives similar comparisons. We show the 1981 list alongside the 1997 list under the same

criteria. In 1981, North Carolina and Iowa both appeared on three of the four lists; North

Carolina on the number of FFS jobs, number of farm workers, and the FFS proportion of

total and Iowa on number of farm workers, the FFS proportion of total, and farm workers’

share of State FFS employment. In 1997, North Carolina and Iowa repeated on those lists

and Nebraska joined Iowa on its lists.

Why do we care about which States are farm dependent? American agriculture is in a

price slump. It is no coincidence that there is a strong overlap between the States on our

four lists of farming-dependent States under different criteria and the list of States whose

public officials have expressed concern about the economic health of American agriculture. [Gerald Schluter, 202-694-5395, schluter@ers.usda.gov; William Edmondson, 202-

694-5374, wedmonds@ers.usda.gov]



	
	




	
	


	





			

North United

Northeast Central South Midwest West States

Percent

Farming 2.23 6.44 7.24 19.49 7.97 7.49

Food processing 4.45 5.99 5.32 8.34 5.49 5.59

Textiles 5.00 .78 7.32 1.34 2.94 4.37

Other manufacturing 6.05 7.60 5.25 4.79 3.53 5.37

Wholesale and retail 38.51 35.12 32.75 29.54 32.17 33.73

Transportation 2.55 2.63 2.37 2.55 2.36 2.46

Food service 25.38 28.85 26.00 23.09 27.83 26.50

Other 15.83 12.58 13.76 10.86 17.71 14.51

Total 100.00 100.00 100.00 100.00 100.00 100.00

Source: ERS analysis of U.S. Department of Commerce data.
Rural Conditions and Trends, Vol. 10, No. 2 • 21

Agriculture and the Rural Economy




	

States with the most food and fiber system workers: States with the highest proportion of 

food and fiber system workers:

1997 1981 1997 1981

1. California California 1. Nebraska South Dakota

2. Texas New York 2. North Dakota North Dakota

3. New York Texas 3. South Dakota North Carolina

4. Florida Pennsylvania 4. Iowa Iowa

5. Illinois Illinois 5. North Carolina South Carolina

6. Pennsylvania Ohio 6. Arizona Idaho

7. Ohio Florida 7. Kansas Nebraska

8. North Carolina North Carolina 8. Idaho Georgia

9. Michigan Michigan 9. Tennessee Alabama

10. Georgia New Jersey 10. Delaware Tennessee

States with the most farm workers: States with the highest proportion of 

farm workers to the State’s total food 

and fiber system jobs:

		
 	 		
 	

1. California California 1. North Dakota South Dakota

2. North Carolina Texas 2. South Dakota North Dakota

3. Texas North Carolina 3. Nebraska Iowa

4. Iowa Minnesota 4. Iowa Idaho

5. Nebraska Michigan 5. Kansas Montana

6. Illinois Wisconsin 6. Idaho Kansas

7. Kansas Iowa 7. Montana Nebraska

8. Minnesota Illinois 8. Kentucky Minnesota

9. Kentucky Missouri 9. Arkansas Wisconsin

10. Wisconsin Kansas 10. Wyoming Oklahoma

Source: ERS analysis of U.S. Department of Commerce.
Farm jobs have declined

during the past 20 years,

and jobs closely related

to farming have shown

little growth. At the same

time, the number of agriculturally related jobs

away from the farm has

increased, but not as fast

as farm employment

losses in some States.

Agriculture and the Rural Economy

22 • Rural Conditions and Trends, Vol. 10, No. 2

Employment on farms—including farm proprietors and wage and salary farmworkers—in nonmetro counties diminished by almost 667,000 jobs (26.9 percent) during 1975-

96 (table 1). Farm consolidation and technological changes that substitute capital for labor

in farming explain much of the decline. These factors, coupled with periods of unfavorable

agricultural economic conditions, caused all regions to lose nonmetro farm jobs. The

Southeast and Delta regions lost the most farm employment (about 40 percent), while the

Pacific, Southern Plains, and Mountain regions had relatively modest declines (from 3 to

12 percent).

As the number of farm proprietors and wage and salary farmworkers declined, employment changes were mixed in industries closely related to farming (table 2). The agricultural services, forestry, and fisheries sector in nonmetro counties gained more than 100,000

jobs (mostly in veterinary and crop services), but these gains were offset by an almost

equal number of jobs lost by nonmetro industries that process and market agricultural

goods after they leave the farm. Processing and marketing employment was negatively

affected by mergers and acquisitions in the industry and the replacement or retooling of

labor-intensive plants to rely on more automated machinery. Employment also declined in

agricultural input industries, such as farm machinery manufacturers and suppliers, which

lost 28,000 jobs in nonmetro counties.

Rural jobs increased the most in industries weakly linked to farming (table 2). The largest

segment of these peripherally related industries—wholesale and retail trade of agricultural

products, such as grocery stores and restaurants—increased by more than 1.3 million

jobs (94.7 percent). Job growth in wholesale and retail trade industries is principally linked

to growth in population and income. Increased personal income has changed consumer

behavior, with more prepared foods being purchased at retail outlets or eaten outside the

home. Compared with wholesale and retail trade, indirect agribusiness, like chemical and

fertilizer mining and food products machinery manufacturing, gained only about 36,000

jobs in nonmetro areas (34.5 percent).

Farm Employment Losses Outstrip Job 

Gains in Farm-Related Industries in Some

Nonmetro Areas 

Table 1

Change in nonmetro farm employment, 1975-961

Farm employment fell in nonmetro areas of all regions

Region 1975 1996 Change, 1975-96

————Number of jobs———— Number Percent

of jobs

U.S. nonmetro 2,475,218 1,808,435 -666,783 -26.9

Appalachia 371,992 256,875 -115,117 -30.9

Corn Belt 530,017 360,091 -169,926 -32.1

Delta States 197,261 121,786 -75,475 -38.3

Lake States 260,728 187,634 -73,094 -28.0

Mountain 146,914 128,374 -18,540 -12.6

Northeast 109,318 80,751 -28,567 -26.1

Northern Plains 272,140 203,236 -68,904 -25.3

Pacific 106,648 102,787 -3,861 -3.6

Southeast 203,240 115,372 -87,868 -43.2

Southern Plains 265,233 242,046 -23,187 -8.7

Note: Detail may not add to total because of data unclassified by metro/nonmetro county.

1Nonmetro farm employment includes farm proprietors and wage and salary farmworkers.

Source: Calculated by ERS using Department of Commerce data.
Rural Conditions and Trends, Vol. 10, No. 2 • 23

Agriculture and the Rural Economy

Farming and Its Closely Related Jobs Are Not Easily Replaced 

Trends in farm and farm-related employment indicate that, nationally, nonmetro areas

gained less than two jobs in industries peripheral to agriculture for each job lost in farming and its closely related industries (table 3). More striking is the low ratio of peripheral

farm-related job gains to farm job losses in some States where farm production comprised a high percentage of total nonmetro employment. North Dakota, South Dakota,

and Iowa, where farm production jobs comprised 20 to 26 percent of total nonmetro

employment, had a job gain/loss ratio of less than one. In these States, the agricultural

sector, including industries only weakly linked to farming, could not create new jobs at a

pace equal to the large decline in farm jobs. Other States with low ratios, such as

Missouri (1.1) and Tennessee (1.0), suffered from large losses of jobs in farming and

closely related processing and marketing industries.

Although agricultural wholesale and retail trade industries may generate jobs in most nonmetro areas, employment growth in these industries depends on population increases

and subsequent expansion of consumer markets. Agricultural wholesale and retail industries most likely cannot provide significant job growth in sparsely settled areas that experience little or no population expansion. Population losses in nonmetro areas of North

Dakota (-13.1 percent), South Dakota (-2.3 percent), and Iowa (-7 percent) help explain

the low agricultural sector job growth in these States during 1975-96. Conversely, nonmetro population increases in California (62.9 percent) and Idaho (32.1 percent), coupled

with small losses of farm jobs, yield a peripheral job gain to farm job loss ratio in these

States of 38.3 and 57.5, respectively. Texas, where nonmetro population increased 22

percent, had a job gain/loss ratio of 6.8, almost equal to the job gain/loss ratio of 6.9 for

these industries in metro areas of the Nation.

Peripheral Farm-Related Industries Offer Job Growth...

Job growth in many nonmetro areas, which in the past relied primarily on farming for jobs,

may now rest with industries only remotely related to agriculture. Agricultural wholesale

and retail trade industries, which provide the final linkage between farmer and consumer,

have been the principal source of new farm-related jobs in nonmetro areas during the

past 20 years. In some nonmetro areas, population growth rates cannot increase the size

of consumer markets needed to support wholesale and retail job gains to offset the number of jobs lost in farming and its closely related industries.

...as Farm Jobs Continue To Dwindle 

Farm production has suffered large employment losses from long-term trends in farm

consolidation and increases in productivity that reduced labor requirements needed to

Table 2

Change in employment in nonmetro farm and farm-related industries, 1975-96

	
		
		
	


	
	

Industry 1975 1996 Change, 1975-96

————Number of jobs———— Number Percent

of jobs

Farming 2,475,218 1,808,435 -666,783 -26.9

Forestry, fisheries, and

agricultural services 88,521 189,409 100,888 114.0 

Agricultural inputs 239,601 211,518 -28,083 -11.7

Processing and marketing 1,202,916 1,102,737 -100,179 -8.3

Wholesale and retail trade 1,384,196 2,694,762 1,310,566 94.7

Indirect agribusiness 104,068 140,045 35,977 34.5 

Source: Calculated by ERS using U.S. Department of Commerce data.
Agriculture and the Rural Economy

24 • Rural Conditions and Trends, Vol. 10, No. 2

produce agricultural goods. These trends are likely to continue, placing farm production in

a position unlikely to generate nonmetro jobs. Jobs in closely related agricultural input

industries will decrease along with the decline in farm production employment. These

trends are largely responsible for the declining nonmetro share of farm and farm-related

jobs (fig. 1). Processing of agricultural products to add value to the region’s commodities

may be a source of new jobs that build upon the agricultural base in nonmetro counties,

but as evidenced during 1975-96, such processing industries lost more than 100,000

jobs. Still, some rural locations may add jobs through the development of value-added

agricultural operations. However, sustained employment growth in processing industries

may depend on the ability to penetrate new markets through expanded distribution of

existing goods or development of new products. [Alex Majchrowicz, 202-694-5355,

alexm@ers.usda.gov]

Table 3

Jobs gained in industries peripheral to agriculture compared with jobs lost in farming and its closely related industries, 1975-96

Most of the top 15 States in which farm production jobs comprised a large percentage of total nonmetro employment gained few jobs in peripherally related farm industries to replace farm jobs lost

Farm production share Ratio of peripheral

of total nonmetro job gain 

State/area employment, 1975 to farm job loss1

Percent Ratio

U.S. nonmetro 14.2 1.9

Top 15 States:

North Dakota 26.4 .5

South Dakota 25.0 .7

Nebraska 21.9 2.4

Iowa 20.6 .6

Texas 20.4 6.8

Minnesota 20.4 1.3

Missouri 20.3 1.1

Arkansas 18.2 1.2

Wisconsin 17.8 2.1

Kansas 17.1 2.2

Kentucky 16.8 2.5

Oklahoma 16.5 3.7

Tennessee 15.9 1.0

California 15.6 38.3

Idaho 15.0 57.5

1Ratio of peripheral farm-related job gain to loss of jobs in farming and closely related sectors.

Source: Calculated by ERS using U.S. Department of Commerce data.
Rural Conditions and Trends, Vol. 10, No. 2 • 25

Agriculture and the Rural Economy

Metro

Nonmetro

 Note: Complete data are not available for 1976-80.

 Source: Calculated by ERS using U.S. Department of Commerce data.

Jobs

1975 77 79 81 83 85 87 89 91 93 95

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

Figure 1

Farm and farm-related employment, 1975-96

Nonmetro areas account for a declining share of all farm and farm-related jobs

Farm and Farm-Related Employment

Farm and farm-related employment includes jobs not only in farm production but also in processing, marketing, and input supply industries (see appendix, “Two Methods of Measuring

Farm-Linked Employment”). Farm and farm-related industries are identified as those having

generally 50 percent or more of their national workforce employed in providing goods and services necessary to satisfy the final demand for agricultural products. An exception to this criterion is indirect agribusinesses, in which percentages range between 32 and 50 percent. In this

article, we classify farm-related industries into those closely related to farming (agricultural services, forestry, and fishing; agricultural inputs; and processing and marketing of agricultural

goods) and industries peripherally related to farming (wholesale and retail trade of agricultural

products and indirect agribusiness). Nonfarm employment estimates in this article are based on

the 1996 County Business Patterns file released by the Bureau of the Census and subsequently enhanced to impute values for confidential data not published by the Bureau. Data on farm

proprietors and wage and salary jobs in farm production, as well as nonfarm proprietors, government employment, and railroad workers, are not included in the County Business Patterns.

Employment for these excluded groups was obtained from the Bureau of Economic Analysis,

U.S. Department of Commerce. Employment data on nonfarm proprietors, available only for

major industrial divisions (one-digit Standard Industrial Classification (SIC) level), were distributed among farm-related industries (two-, three-, and four-digit SIC levels) based on the proprietor’s share of total employment in the division in which the farm-related industry is classified.

The percentage of proprietor employment in every industrial division was determined for each

county. These percentages were applied to wage and salary employment in farm-related industries in the county.
Agriculture and the Rural Economy

26 • Rural Conditions and Trends, Vol. 10, No. 2
Rural communities have

sought to offset shrinking

employment in the farm

sector by adding value to

farm products.

Agricultural value-added

strategies can provide

only limited rural job

growth. The growing

importance of the service

sector as an engine of

job growth appears to be

bringing many rural

areas into the economy’s

mainstream, but some

areas could be left

behind.

Agriculture and the Rural Economy

26 • Rural Conditions and Trends, Vol. 10, No. 2

Focusing on the role of farms as a source of raw materials for food and fiber products,officials in many agricultural States and communities have pursued “value-added”

development strategies. Value added by businesses beyond the farm gate that produce,

process, store, transport, and market food dwarfs the value created on the farm. Rural

communities have often failed to retain or attract many businesses in these “value-added”

sectors. Only a few cents of each dollar spent on food and fiber by consumers represents

the value of farm-produced raw materials. Value-added strategies aim to keep a larger

share of the consumer’s dollar in rural areas. Value-added strategy proponents seek to

lure food processing plants to rural areas, start new processing operations, develop new

consumer or industrial uses for agricultural products, or bypass conventional wholesaleretail systems to sell food products directly to consumers.

Many Factors Determine the Best Location for Food Processing

It is tempting to take for granted that industries using agricultural inputs would naturally

locate in rural areas, close to their farm sources of raw materials. However, access to

agricultural inputs is only one of many factors that determine the best site for a food

processor. Firms choose sites that minimize the transport costs for all their inputs, as well

as their output. If inputs are more costly to transport, the best site is closer to the inputs.

Industries that add value to raw farm products must obtain packaging materials and other

industrial inputs, as well as livestock or grain from surrounding farms. Raw farm commodities are the dominant cost component for firms such as meatpackers and grain and oil

mills that do basic processing (table 1). Because it is costly to transport live animals and

bulk commodities, these operations frequently locate near the source of their raw materials—in rural areas. Many other food processing industries, such as bread, snack food,

pasta, and beverage makers, use little or no raw farm commodities. They purchase flour,

sugar, oils, processed sugars, and sweeteners from other processors. For these types of

processors, there is little advantage to locating in rural areas. Packaging is a large cost

component for many food processors, often accounting for 25 percent of materials cost.

For these firms, access to suppliers of containers, labels, and other materials is often a

more important consideration, as is access to customers and product distribution networks. These factors often lead firms to choose an urban location. Labor is also an important cost component, and many analysts credit the search for lower cost nonunion labor

for the recent migration of meatpacking jobs from the urban Midwest and Northeast to the

rural South and Great Plains.

The variation in nonmetro employment shares across industries illustrates the differences

in location choices for different types of food processors. Over half of meat products manufacturing employment is in nonmetro counties (fig. 1). Between 30 and 40 percent of

grain mill, fats and oils, and fruit and vegetable processing jobs are in nonmetro counties.

Agricultural raw materials are important inputs for each of these industries. By comparison, beverage and bakery product plants have only 12 percent of their employment in

nonmetro counties.

Food Manufacturing Jobs Grew in Some Nonmetro Counties During the 1990’s

During the 1990’s, food manufacturing employment grew by over 70,000 jobs, and nonmetro areas attracted most of the new jobs. Our analysis of County Business Patterns

data indicates that nonmetro counties gained 60,800 food processing jobs between 1991

and 1996, partially offsetting the loss of nonmetro farm jobs over that period (table 2).

Metro areas gained only 11,750 food processing jobs during 1991-96. Thus, the nonmetro

share of food processing jobs rose from an estimated 29.2 percent in 1991 to 31.8 perAgriculture’s Role Shrinks as the Service

Economy Expands 
Rural Conditions and Trends, Vol. 10, No. 2 • 27

Agriculture and the Rural Economy

Table 1

Materials cost shares for selected food processing industries, 1992

For many food products, packaging accounts for a greater share of costs than farm commodities

Type of materials and inputs used

Farm Intermediate

Industry commodities products Packaging Other

Percent

Meat packing 86 3 2 8

Beet sugar 83 0 1 13

Flour and other grain mills 79 5 3 10

Soybean oil mills 68 12 0 8

Fluid milk 62 8 9 15

Poultry slaughter and processing 50 18 4 15

Cheese 30 32 4 15

Wines, brandy 25 18 26 26

Potato chips and similar snacks 24 25 20 30

Prepared feeds 10 48 1 27

Creamery butter 9 73 1 15

Cereal breakfast foods 9 42 27 22

Ice cream and frozen desserts 8 32 15 44

Dog and cat food 0 36 25 31

Bread, cake, and related 0 73 10 18

Cookies and crackers 0 52 26 22

Bottled and canned soft drinks 0 42 41 18

Macaroni and spaghetti 0 52 22 26

Note: Farm commodities include grain, livestock, and other commodities produced by farms. Intermediate products include

processed food products purchased from other food manufacturers.

Source: ERS analysis of 1992 Census of Manufactures.

Meat products

Grain mills

Fats and oils

Fruits and vegetables

Dairy

Sugar and confectionery

Bakery products

Beverages

0 20 40 60

Percent

Employment

Establishments

Figure 1

Nonmetro shares of employment and establishments for food processing industries,

1996

Food processing industries vary considerably in their nonmetro share of operations

Source: ERS analysis of 1996 County Business Patterns, enhanced by Claritas, Inc., to impute suppresed data.
Agriculture and the Rural Economy

28 • Rural Conditions and Trends, Vol. 10, No. 2

cent in 1996. Nearly all of the nonmetro food manufacturing job growth was in meat and

grain mill products manufacturing, the two food manufacturing sectors with the strongest

nonmetro ties (fig. 2). Meat products manufacturing employment grew by about 45,000

nonmetro jobs, and grain mill products added about 17,000 nonmetro jobs. Dairy, beverTable 2

Growth in food manufacturing employment by county type, 1991-96

Most of the gain in food manufacturing jobs occurred in 357 nonmetro counties

Type of county Counties Employment gain

Number

Nonmetro counties 2,310 60,800

Gained at least 50 food manufacturing jobs 357 104,000

Lost at least 50 food manufacturing jobs 232 -44,300

Stable food manufacturing employment1 1,720 1,100

Metro counties 835 11,750

Note: Table was constructed using estimated county employment in 1991 and 1996 for food and kindred products 

manufacturing.

1Counties that gained or lost fewer than 50 food manufacturing jobs between 1991 and 1996.

Source: ERS analysis of U.S. Department of Commerce, County Business Patterns data, enhanced by Claritas, Inc., 

to impute suppressed data.

Meat products

Grain mill products

Dairy products

Beverages

Sugar and confectionery

Bakery products

Miscellaneous food and kindred

Fats and oils

Preserved fruits and vegetables

-20,000 0 20,000 40,000 60,000

Employment change

Source: ERS analysis of 1996 County Business Patterns, enhanced by Claritas, Inc., to impute suppresed data.

Figure 2

Nonmetro food manufacturing employment growth by sector, 1991-96

Most job gains were in meat and grain mill products manufacturing
Rural Conditions and Trends, Vol. 10, No. 2 • 29

ages, and sugar and confectionery products manufacturing each added several thousand

jobs between 1991 and 1997, while preserved fruits and vegetables lost about 8,000 jobs.

Nonmetro employment changed little in fats and oils, bakery products, and miscellaneous

food products industries.

Employment gains were limited to relatively few nonmetro counties. Only 357 of 2,310

nonmetro counties gained 50 or more food processing jobs during 1991-96. Across the

357 nonmetro job-gaining counties, the average gain in food processing jobs was about

291 jobs per county. The job-gaining counties were scattered geographically across 47

States, but were predominantly in Midwestern and Southern States (fig. 3). However,

most nonmetro counties did not gain food processing jobs. Food processing employment

fell by at least 50 jobs in 232 nonmetro counties and was stable in the remaining 1,720

nonmetro counties during 1991-96.

Food manufacturing and other value-added activities can provide only modest growth in

jobs for rural America. Food manufacturing provides only 1.7 percent of all nonmetro jobs.

Even if all of the roughly 1 million food manufacturing jobs in metro areas were suddenly

moved to nonmetro counties, total nonmetro employment would rise by only 4 percent.

Food retail and marketing are the largest and fastest agriculturally related sectors (see

“Farm Employment Losses Outstrip Job Gains in Farm-Related Industries in Some

Nonmetro Areas” in this issue), but businesses in these sectors usually choose urban

locations to gain access to consumers.

Figure 3

Nonmetro counties that gained at least 50 jobs in food manufacturing, 1991-96

Gains in food manufacturing jobs were geographically scattered across the country

Source: ERS analysis of U.S. Department of Commerce, County Business Patterns data.

Agriculture and the Rural Economy
Agriculture and the Rural Economy

30 • Rural Conditions and Trends, Vol. 10, No. 2

Agricultural and Manufacturing Employment Expected To Decline

Nationally, farming and most food manufacturing industries are not expected to create

many jobs. The Bureau of Labor Statistics (BLS) projects a decrease in agricultural

employment of 0.1 percent per year between 1998 and 2008 (table 3). BLS projects

falling employment in most types of food manufacturing, textiles, and apparel industries.

The one bright spot is meat products manufacturing employment, which is projected to

grow 1.4 percent annually. In goods-producing industries, like agriculture and manufacturing, competitive pressures are inducing businesses to cut per unit costs by raising worker

productivity (output per worker). This means employment will be stagnant or declining in

all but the most rapidly growing industries. Thus, even though output is expected to grow

at a healthy rate, employment is expected to grow slowly or decline. For example, BLS

projects annual growth in manufacturing output of 3.4 percent, but it projects no change in

manufacturing employment between 1998 and 2008. Projected output growth exceeds

projected job growth for nearly all goods-producing industries shown in table 3.

During the coming decade, jobs are projected to grow fastest in service-producing industries, including transportation, communications, public utilities; wholesale and retail trade;

finance, insurance, and real estate; and personal, business, and health services. ServiceTable 3

Projected employment and output growth by industry, 1998-2008

Service industry employment is projected to grow the fastest

Employment Output

Industry growth growth

Percent

Goods-producing industries: 0.1 3.0

Agriculture -.1 1.4

Mining -2.1 1.2

Construction .9 1.3

Manufacturing .0 3.4

Food and kindred products manufacturing .2 1.2

Meat products 1.4 1.7

Dairy products -1.2 .6

Preserved fruits and vegetables -.6 .9

Grain mill products, fats and oils .1 1.5

Bakery products -.5 -.1

Sugar and confectionery products -.4 .6

Beverages -1.0 1.5

Miscellaneous foods and kindred 1.0 .9

Tobacco products -3.1 1.0

Textile mill products -1.7 1.2

Apparel -2.6 .3

Service-producing industries: 1.8 3.2

Transportation, communications, and utilities 1.3 3.4

Wholesale trade .7 3.7

Retail trade 1.3 2.7

Eating and drinking places 1.6 1.6

Finance, insurance, and real estate 1.2 3.0

Services 2.8 3.9

Government .9 1.3

Note: Table shows projected annual growth rates. Output growth is in constant 1992 dollars.

Source: Allison Thomson, “Industry Output and Employment Projects to 2008,” Monthly Labor Review,

November 1999, pp. 33-50.
Rural Conditions and Trends, Vol. 10, No. 2 • 31

Agriculture and the Rural Economy

producing sector jobs are projected to grow 1.8 percent per year, and BLS expects these

industries to account for nearly all of U.S. job growth between 1998 and 2008.

Can Rural Communities Participate in the Service Economy? 

Many rural areas are participating in the service economy, especially those enjoying the

spillover effects of prosperity in urban areas and amenity-rich areas that attract retirees,

telecommuters, vacationers, and others. Between 1991 and 1996, the services sector

was the largest source of new jobs in nonmetro counties, creating about one-third of new

nonmetro jobs (fig. 4). Retail trade accounted for another 20 percent of job growth. In

metro counties, the services sector created half of all new jobs between 1991 and 1996.

By comparison, nonmetro counties were more reliant on manufacturing and government

(State and local) for new jobs. These two sectors accounted for a combined 17 percent of

nonmetro job growth, compared with less than 3 percent for metro counties. The increasing service-orientation of the U.S. economy is troubling for rural areas that rely on farming, food processing, and other manufacturing for economic development. Retail; finance,

insurance and real estate; construction; transportation; wholesale trade; and agricultural

services (mostly landscaping and lawn service jobs) shares of job growth were similar in

metro and nonmetro counties.

For many rural communities, the prospects for participating in the service economy seem

less promising because service and trade industries have a greater tendency than other

activities to “agglomerate” in urban places. They tend to concentrate in cities where they

have access to large populations of consumers, transportation nodes, related industries

and business service firms. The retail and services sectors account for 49 percent of

metro jobs compared with only 41 percent for nonmetro counties. Geographic concentration of retail and service activity is especially true in a wide swath of the Great Plains and

other sparsely populated areas where farming is still the chief rural economic activity (see

“Economic Growth in Farming Areas Lags the Rest of Rural America” in this issue). In

these regions, many smaller communities are no longer viable as retail and service centers. With larger farms, nearly universal access to automobiles, and pressure on retailers

and service providers to exploit economies of scale, scattered cities and large towns in

farming-dependent regions are becoming islands of commerce surrounded by a sea of

sparsely populated farming areas. Remoteness seems to be the largest hindrance to

development in these regions. Counties that reduced their farming dependency during the

1990’s tended to be on the fringes of the farming-dependent region.

Another problem associated with growth of service industries is that service jobs tend to

have low skill requirements and low pay, especially those in food and personal services

that small communities are most likely to retain. In contrast, rural jobs lost in manufacturing, mining, and farming tend to pay well. More highly paid service jobs in information,

business and health services are among the most likely activities to locate in urban areas.

Many highly educated professionals who fill these jobs prefer not to live in areas that lack

natural amenities and/or good primary and secondary education.

Consumer Orientation Leads to Development

The increasing consumer orientation of the service economy holds lessons for planners

and policymakers. Contracting and supply chain arrangements have increased their

prevalence in recent years partly because consumers are demanding food products with

specific attributes. In many cases, consumers are demanding less tangible attributes. For

example, the method by which a product was produced (organically or without genetic

modification) is becoming an important attribute. Many consumers seem to be willing to

pay a premium for these attributes. Businesses and communities have taken advantage of

this to create brands associated with their particular region, production practice, or some

other attribute that can command a premium price. Many farms have broadened the

scope of their business to offer entertainment and recreation in the form of agricultural

tourism, theme-oriented farm visits, paid fishing and hunting access, and other services.

Advances in information technology also make it possible for businesses in remote places
Agriculture and the Rural Economy

32 • Rural Conditions and Trends, Vol. 10, No. 2

to get in touch with consumers and sell directly to them. In today’s service-oriented economy, it is this type of consumer-savvy search for new market niches that is likely to lead

to development. [Fred Gale, 202-694-5349, fgale@ers.usda.gov; Maureen Kilkenny, 515-

294-6259, kilkenny@iastate.edu] 

Agricultural services, forestry, fishing, other

Construction

Manufacturing

Tr ansportation

Wholesale trade

Retail trade

Finance, insurance, real estate

Services

Government

Agricultural services, forestry, fishing, other

Construction

Manufacturing

Transportation

Wholesale trade

Retail trade

Finance, insurance, real estate

Services

Government

Nonmetro

Metro

Figure 4

Employment growth by sector, nonmetro and metro counties, 1991-96

Most job growth was in service and retail trade industries during the 1990’s

Source: ERS analyis of Bureau of Economic Analysis data.
Census of Agriculture

data from 1997 seem to

indicate that farm numbers stabilized in the

1990’s. A closer look

shows that the number of

full-time farms continued

declining, while part-time

farms surged. Many

counties continued to

lose farms at a steady

pace, while others gained

farms.

Rural Conditions and Trends, Vol. 10, No. 2 • 33

Agriculture and the Rural Economy

At first glance, the latest agricultural census data indicate that the number of U.S.farms stabilized in recent years, perhaps indicating an end to the trend toward fewer,

larger farms. The total of 1,911,859 U.S. farms reported by the most recent Census of

Agriculture in 1997 represented a decline of less than 1 percent from the 1992 total. This

was the slowest rate of decline since the late 1970’s. Whereas the previous three censuses reported steady decline in farm numbers averaging about 30,000 per year, the decline

in farm numbers between 1992 and 1997 was only 2,700 per year. USDA farm counts

based on annual sample surveys also indicate that farm numbers stabilized from 1993 to

1998. On the surface, the data indicate that perhaps the trend toward fewer, larger farms

that has done much to change the character of rural America may have finally run its

course.

A closer look at the data shows some important trends that are hidden in the aggregate

numbers. When the data are disaggregated by age group, type of farm, and geography,

we find that various segments of the farm sector are following divergent trends. While

commercial-sized farms continue to consolidate into fewer, larger farms, small noncommercial farms in various regions of the country are also growing in number. This means

that many rural communities (largely in the Midwest and Great Plains) are still facing loss

of population, declining retail trade and services, and a shrinking tax base that often

accompany the loss of farms. At the same time, other rural communities are enjoying an

influx of new farms.

Surge in Farms Operated by People Principally Employed Outside Farming

The census of agriculture asks respondents to report whether or not farming is their principal occupation. Those principally employed outside farming are largely “part-time” farmers and those pursuing dual farm-nonfarm careers. Figure 1 shows that the number of

farms whose operators say farming is their principal occupation continued a trend of

steady decline between 1992 and 1997. This group includes farmers who are strongly

committed to a full-time farming career, as well as retirees. These farms declined in number by more than 90,000 between 1992 and 1997, comparable with the decline recorded

for the two previous 5-year census intervals for this group. In contrast, the number of

farms operated by people who are primarily employed outside farming has been more

steady in recent decades and rose by 78,000 between 1992 and 1997.

Changes in farm numbers by size of farm show a surge of very small farms (usually operated by people primarily employed outside farming). Farm numbers grew among very

small farms (less than $10,000 in annual sales) and among larger farms that have sales

of $250,000 or more (table 1). Few farms earn significant profits with less than $10,000 in

sales, so these data show again that much of the growth in farm numbers came from

part-time “recreational” or “retirement” farms. (The definition of a farm is any place that

sold, or normally would sell, at least $1,000 of agricultural products. See box, “Farm

Definition Affects Farm Numbers.”) Farm operators whose primary occupation is farming

generally try to expand the size of their farms (although this group also includes retirees

who operate small farms and generally do not expand their size). Since fixed costs are

such an important part of total costs and per unit profit margins are slim, large operations

are needed for most operators to earn significant income. The number of farms with sales

between $10,000 and $250,000 per year fell by 100,000 between 1992 and 1997. Many

farms that were in this sales class in 1992 probably moved to larger sales classes as they

expanded their operations. (USDA’s National Commission on Small Farms classified

farms with less than $250,000 as “small farms.”) However, many of them apparently left

Small and Large Farms Both Growing in

Number
The Bureau of Labor

Statistics (BLS) estimates the number of

people employed in farming. These data provide a

less dire picture of the

rising age of farmers

than does the census of

agriculture, which does

not provide personal data

on junior partners and

unpaid family members.

Nevertheless, the BLS

data show a steady

decline in the number of

young farmers during the

1990’s.

Rural Conditions and Trends, Vol. 10, No. 2 • 39

Agriculture and the Rural Economy

There is concern over the age of farmers—specifically concern that the average age isrising and the number of young people entering the occupation is falling. The issue is

not a new one. Since the 1950’s, USDA has received letters from farmers who were

alarmed by the decline in the number of farms, a visible rise in average age of farmers,

and the apparent shortage of young new farmers. Young people were going off to “public

work,” they said, using a common expression of the time.

The most common source of information on the number and age of farmers has long

been the census of agriculture, taken every 5 years. The data by age go back to 1890.

They are very useful, but are limited in that they consistently understate the number of

younger farmers, and thus overstate the average age of all farmers.

This problem stems from the fact that the census form obtains only personal characteristics (such as age) for one person from each farm or ranch. In the case of partnerships,

such information is obtained only for the “senior partner or person in charge.” Thus, in a

typical parent/offspring partnership, age would be recorded only for the older adult. With 9

percent of all farms being partnerships and another 4 percent being small family corporations, the potential for undercount of young farmers is clear.

BLS Survey Counts Junior Partners 

An alternative data source is that collected for the Bureau of Labor Statistics (BLS) by the

Census Bureau, as part of its monthly national survey of employment. This survey is

based on a sample of 47,000 households. Each employed person’s occupation is

obtained and, thus, junior partner farmers are included as well as senior partners. The

BLS data differ from the census of agriculture in one other respect: persons with more

than one job are tabulated by the occupation at which they spent the most time in the survey week. Therefore, persons for whom farming is secondary work are excluded from

those tabulations. (People with second jobs are identified, but data on those jobs by occupation and age of worker are not available.) This can be viewed as a limitation of the

data, but it does mean that the results represent people who have their main work

reliance on farming. In contrast, the overall census of agriculture numbers include many

thousands of people with minimal attachment to farming, given the very liberal farm definition used in the census. (A place is regarded as a farm if $1,000 or more of products

were sold from it in the past year, or if it is deemed capable of selling such an amount.) 

Surge of Young Farmers During 1970’s Reversed During 1980’s 

The BLS series shown in table 1 begins in 1970. At that time, nearly 50 percent more

farmers were aged 65 years and over than under 35 (fig. 1). The age trend, however, was

steadily downward throughout the 1970’s, as substantial numbers of young people

entered the business and many older ones retired. This was a time when the large supply

of “baby boom” children was coming of age, when there was a strong back-to-the-countryside movement, and when there were some years of excellent farm profits and rising

farmland values. The number of farmers under age 35 rose from 248,000 in 1970 to

374,000 in 1982, by which time the relative prevalence of young and old farmers had

been reversed, with the young ones two-thirds more numerous than the older ones.

The farm financial crisis in the early and mid-1980’s was the worst since the 1930’s. The

most dramatic trend evident in the data after 1984 is the decline in the number of very

young farmers, those under 25. From 1976 through 1984, their numbers were very stable,

never below 96,000 or above 102,000. (The census of agriculture number for the same

age group was 67,000 in 1978 and 62,000 in 1982.) Thereafter, the BLS figure for farmers under 25 fell steadily to just 41,000 in 1993, a drop of three-fifths. Part of this decline

Bureau of Labor Statistics Data Provide More

Complete Count of Young Farmers
Agriculture and the Rural Economy

40 • Rural Conditions and Trends, Vol. 10, No. 2

Table 1

Number of farm operators and managers by age group, 1970-98

Annual Bureau of Labor Statistics estimates show demographic trends in employment of farm operators and managers

Age group

Year Total <20 20-24 25-34 35-44 45-54 55-59 60-64 65-older Median age

Thousands Years

1970 1,753 14 43 191 281 414 219 229 364 53.4

1971 1,666 14 50 190 266 389 220 205 332 53.0

1972 1,688 16 57 191 275 386 218 225 321 52.9

1973 1,664 17 60 184 266 392 218 222 301 52.8

1974 1,643 21 69 196 262 391 215 194 295 52.0

1975 1,593 22 71 223 259 380 201 176 261 50.8

1976 1,514 18 79 218 242 361 189 155 251 50.5

1977 1,459 15 83 217 238 317 198 145 247 50.6

1978 1,480 18 83 231 247 305 183 162 251 50.3

1979 1,446 18 83 246 238 307 169 169 216 49.5

1980 1,485 20 78 245 260 313 176 174 218 49.5

1981 1,485 21 81 252 266 298 181 163 223 49.1

1982 1,452 18 82 274 256 280 163 158 221 48.4

1983 1,450 17 79 277 274 276 159 155 213 47.8

1984 1,442 19 81 274 272 281 158 154 202 47.7

1985 1,359 15 62 256 262 272 154 151 186 48.1

1986 1,337 12 55 255 250 258 151 140 216 48.7

1987 1,317 11 53 242 252 252 142 153 213 49.0

1988 1,286 14 47 234 259 244 150 122 215 48.6

1989 1,269 16 41 236 269 231 132 136 206 48.1

1990 1,211 14 40 229 262 221 117 125 203 47.7

1991 1,228 11 42 210 285 233 130 140 178 47.8

1992 1,215 10 43 187 272 235 124 136 207 49.0

1993 1,156 9 32 184 270 225 119 114 203 48.7

1994* 1,453 44 43 199 320 302 265** ** 279 49.0

1995* 1,446 46 35 191 341 288 140 124 281 48.8

1996* 1,314 10 28 178 309 275 128 118 267 49.8

1997* 1,317 15 31 173 304 273 139 126 255 50.0

1998* 1,187 11 25 147 270 277 126 115 216 50.1

Note: Data are annual averages of monthly statistics, based on number of persons whose sole or principal occupation (measured by time worked)

was farm operator or farm manager.

*Data for 1994 and later years are not comparable with prior years due to use of 1990 census of population controls and changed procedures that

yielded many more operators, especially female spouses and teenagers.

**In 1994, data were reported only for 55-59 and 60-64 age groups combined.

Source: ERS analysis of Bureau of Labor Statistics data.
Rural Conditions and Trends, Vol. 10, No. 2 • 41

Agriculture and the Rural Economy

probably stemmed from the reduced potential supply of young farmers as the smaller

birth groups that followed the baby boom came of age. But it seems likely that it also

reflects a reduced willingness to enter farming by young people who grew up during the

stressful times of the farm crisis.

In 1994, the BLS changed its interviewing procedures in a manner that elicited a larger

count of unpaid family workers. This change produced a higher number of female and

teenaged farm operators. But from that time to 1998, the number of operators under 25

fell by more than half again from its revised level of 88,000 in 1994 to 36,000 in 1998.

Farmers 25-34 peaked in the early 1980’s, but have since fallen in number as the

“boomers” have either entered middle age, withdrawn from farming, or shifted primarily to

off-farm work. As a group, farmers under 35 comprised 26 percent of all farmers from

1982-84. But as a result of disproportionate declines in both the under 25 and 25-34

groups, those under 35 were just 15 percent of total farmers by 1998. Clearly, farmers

must sense a comparative shortage of young colleagues, given this degree and rapidity

of change.

On the other hand, farmers under 35 comprised just 14 percent of total farmers in 1970

under the earlier procedures, a slightly smaller representation than today. And the 15 percent found in the BLS survey of persons whose sole or principal job is farming is fully

double the 7 percent under age 35 measured by the census of agriculture for farmers it

counts as having farming as their principal occupation. This latter group in the census is

heavily weighted with persons age 65 and over, many of whom are retired and do not

regard themselves as in the labor force any longer.

Census of Agriculture Undercounts Young Farmers

In absolute numbers, BLS found 219,000 farm operators and managers under age 35 in

1997 whose sole or principal work was farm operation, whereas the census reports

149,000, including those who just work part-time (fig. 2). Thus, the BLS data more fully

1970 80 90

0

100

200

300

400

Age 65 and older Age 25-34

Under age 25

 Note: Chart shows number of people who were primarily employed as farmers or farm managers estimated from sample 

surveys. Estimates increased in 1994 due to a change in interview procedure that counted more female and teen-aged farm

operators.

 Source: ERS analysis of Bureau of Labor Statistics data.

Thousands

Figure 1

Farmers in selected age groups, 1970-98

The number of farmers in both young and older age groups has fallen since 1994
Agriculture and the Rural Economy

42 • Rural Conditions and Trends, Vol. 10, No. 2

convey both the proportion and absolute number of farmers who are young. Two points

seem equally important to stress. The supply picture for young farmers is not as dire as

the census data would imply if uncritically interpreted without knowledge of census procedures concerning data for partners and family corporations. That being said, the BLS data

show a rapid drop in young farmers in the last decade, at a pace well above that attributable to the passing of the baby boomers into middle age.

The median age of farmers in the BLS series in 1998 was 50.3 years (the age separating

the farmers into two equal groups). This is not a record high value, being below that of

most of the 1970’s. The median has, however, risen in each year since 1995 and is certain to be pulled considerably higher as the bulk of the large baby boom cohort (now in its

40’s and late 30’s) moves into the over-50 age group. [Calvin Beale, 202-694-5416,

cbeale@ers.usda.gov]

Under 25

25-34

35-44

45-54

55-64

65 and older

Under 25

25-34

35-44

45-54

55-64

65 and older

0 200 400 600

Age of farmer

BLS Census

1982

1997

Thousands

 Note: BLS denotes estimated number of farmers and farm managers based on principal occupation.

The census counts only the senior partner or person in charge for each farm operation.

 Source: ERS analysis of Bureau of Labor Statistics and census of agriculture data.

Figure 2

Comparison of BLS and census of agriculture counts of 

farmers by age group, 1982 and 1997

The census counts fewer young operators and more older operators
The increasing use of

computers on the farm

raises the question of

whether these new skills

will be valued in off-farm

employment. Data suggest that computers are

used predominantly for a

single group of tasks that

may not develop the

“systems skills” that are

becoming increasingly

important in off-farm

employment.

Rural Conditions and Trends, Vol. 10, No. 2 • 43

Agriculture and the Rural Economy

Off-farm employment by farm operators and their spouses has been a key to financialsurvival for farm families. The mechanization of farms earlier in the 20th century gave

farmers mechanical and problem-solving skills that were prized by many rural employers,

largely in manufacturing and related industries that needed workers who were good at

operating and repairing machinery. Many skills learned on the farm were transferable to

nonfarm jobs. Those skills made the transition to nonfarm careers easier for farm youth

and helped farmers in finding off-farm jobs.

As the United States moves from an industrial to an “information economy,” demand for

workers with mechanical skills is stagnant or declining. Many employers now seek computer skills and the ability to find and process information. Will farmers be as employable

off the farm as they were in the past? Will farming communities participate in the information economy, or will they be left behind? 

Onfarm Computer Use Increasing

To a large extent, farms have also been participating in the information revolution. A

recent USDA survey shows that nearly half of farms reported using computers in 1999

(fig. 1). Comparison with 1997 data suggests that onfarm computer use is growing rapidly.

In the 2 years between 1997 and 1999, farms with access to a computer increased from

38 to 47 percent.

Internet access more than doubled in the same 2-year period, rising from 13 percent of

all farms in 1997 to 29 percent in 1999. Unfortunately, these data do not include informaCan Computer Use on the Farm Build Skills

for Off-Farm Jobs?

Use for farm business

Have Internet access

Own or lease computer

Computer access

0 10 20 30 40 50

Percent of farms

1997

1999

Figure 1

Farm computer use, 1997 and 1999

Computer use on the farm grew considerably between 1997 and 1999; Internet access doubled

 Source: Farm Computer Usage and Ownership, National Agricultural Statistics Service, Agricultural Statistics

Board, USDA, July 1999.
Agriculture and the Rural Economy

44 • Rural Conditions and Trends, Vol. 10, No. 2

tion on the percentage of farms using this technology to get up-to-the-minute market

information, to get technical information related to farming problems, or to interact electronically with suppliers or customers. However, the growth in access of itself is an important development as the usefulness of the Internet to the farm business is likely to be discovered over time. Strong sales of books such as The Farmer’s Guide to the Internet

(http://www.rural.org/favorites.html) along with the emergence of search engines devoted

to agriculture (for example, The AgriSurfer available at http://www.AgriSurfer.com) suggest

that many farmers are actively investigating these possibilities.

The percentage of farms using computers in the farm business in 1999 was only 24 percent and also grew at a more modest rate over the 2 years. This finding suggests that

roughly half the farm households with computer access are using computers as a consumer good or for nonfarm business. The data suggest that only half of farms with access

to computers use them for farm business applications.

Larger farms are more likely to have computer access and—if they have access to a

computer—more likely to use computers for farm business (fig. 2). The benefits of integrating computers are more likely to exceed the costs of purchasing and learning to use

them on large farms. The wide diffusion of computer technology—oftentimes used first in

nonfarm activities—bodes well for the eventual use of computer technology across the

farm size spectrum.

A more detailed account of the specific computer applications used in the farm business

is available in the 1995 Agricultural Resource Management Study. While the data are relatively old, they can tell us which applications are most common in the farm business and

provide more detailed characteristics of farmers and farm households associated with

computer use.

Computerized bookkeeping/financial analysis was by far the most common application

across all farm types. For farm sizes up to $500,000 in sales, bookkeeping/financial

analysis applications were roughly twice as prevalent as ‘Computer software for production decisions,’ the second most common application. Computer-aided chemical applicaHave Internet access

Use for farm business

Computer access

Percent of farms

$100,000 or more

$1,000 - $9,999

$10,000 - $99,999

Figure 2

Farm computer use by farm sales class, 1999

Computer use is more likely on larger farms

0 20 40 60 80

 Source: Farm Computer Usage and Ownership, National Agricultural Statistics Service, Agricultural Statistics

Board, USDA, July 1999.

Own or lease computer
Rural Conditions and Trends, Vol. 10, No. 2 • 45

Agriculture and the Rural Economy

tions/field operations were infrequent for farms as a whole (2.5 percent) but used by 15-

20 percent of farms in the two largest size classes. In contrast, using global positioning

systems to aid field operations was infrequent across all size classes. Unfortunately, the

data provide no information on the use of electronic market information either through the

Internet or subscription services.

The data confirm that large farms, and those run by younger farm managers with a college degree, are most likely to use computers in the farm business. Both farm size and

educational attainment of the farm operator produce striking differences in the rate of

adoption. Farmers with a college degree are roughly 10 times more likely to use the various applications compared with farmers with less than a high school diploma. These factors are equaled or exceeded in comparing the smallest farm size class (less than

$50,000 in sales) with the largest farm size class (more than $1,000,000). The increasing

age of the farm operator has a more modest effect on reducing the likelihood of using the

various applications.

Computers Underused

As of 1995, for each sales class, age group, and educational level, relatively few farms

used computers for production operations (table 1). This suggests that the majority of

farms using computers are not integrating this use across production and accounting

required of a farm management information system.

A less comprehensive but more recent 1998 survey of U.S. corn growers by Novartis,

Inc., provides more timely information on the adoption of ‘precision agriculture’ technologies such as Global Positioning System (GPS) mapping and yield monitors (table 2).

However, these statistics are not a representative sample of all farms, and may overstate

computer use compared with the 1999 USDA data. In the one comparable data item,

computer use in the farm business is reported as 24.1 percent in the 1999 NASS/USDA

data but 46.2 percent in the Novartis data. Despite this inconsistency, the Novartis data

suggest that applications providing detailed information on the characteristics and variability of small plots within a field have been adopted by many farms in the two largest

size categories. The data also provide information on the percentage of farms with

Internet access that are using this technology in the farm business. Over all size classes,

21.1 percent of farms are using the Internet to retrieve agricultural information.

While these more recent data suggest a greater prevalence of computer use in production decisions than did the 1995 data, the Novartis data also give the general impression

that computers are not being fully exploited to integrate information from diverse aspects

of the farm operation. Roughly 46 percent of all farms use a computer in the farming

operation, but less than half of those farms use the informational capabilities of the

Internet for production or marketing. An even smaller percentage of farms use precision

agriculture technologies.

Skill Requirements of Information-Intensive Farming

The increasing use of computers in farm businesses is encouraging. It suggests that farm

managers are using some of the same information technologies that are also being used

in the wider economy. However, the question remains whether farmers using computers

on the farm will develop skills that are valued in the off-farm economy. Is it enough for

farmers to be ‘computer literate’ or does the information economy require a broader suite

of skills?

Some experts emphasize that worker skill development is no longer confined to classrooms. Both managers and frontline workers must continuously develop new skills by

learning on the job. A traditional allure of farming has been the combination of mental and

physical activity that values this ability to learn by doing. In the past, this mode of learning

was farm-specific. However, if the capability to learn from farming operations is substantially augmented by the application of information technology, then skills developed using

this new tool may also be valued in off-farm employment. That is, the concrete experience
Agriculture and the Rural Economy

46 • Rural Conditions and Trends, Vol. 10, No. 2

Table 1

Computer applications of farmers by size of operation and operator characteristics, 1995

Bookkeeping/financial analysis is the most commonly used application

Computerized Computer software Computer-aided Global Positioning

bookkeeping/ for production chemical application/ System to aid

Item financial analysis decisions field operations field operations

Percent of responding farms

Farms using technology 14.6 6.5 2.4 0.8

Sales class:

Less than $50,000 8.7 2.7 1.0 .3*

$50,000 or more 31.3 17.4 6.3 2.1

$50,000 - $99,999 20.1 11.5 3.7* 1.6**

$100,000 - $249,999 31.6 16.3 5.3 1.4*

$250,000 - $499,999 43.5 22.7 10.5 3.7

$500,000 - $999,999 54.2 35.3 14.6 6.2

$1,000,000 or more 71.2 51.6 20.3 4.2*

Operator age:

Less than 35 years 21.3 11.4 5.3 1.8*

35 to 44 23.3 12.2 2.9 .9*

45 to 54 17.4 7.0 2.5 .5*

55 to 64 11.6 4.7 1.9 .9*

65 years or older 5.4 1.5 1.3* .5**

Operator education:

Less than high school 2.5 1.5* .8* .1**

High school 9.6 4.1 1.5 .5*

Some college 20.2 9.1 3.8 1.4*

College 33.3 14.8 4.5 1.4*

Note: About 3.5 percent of farm operators refused to answer these questions. Excludes cooperative farms.

* The relative standard error (RSE) of the estimate exceeds 25 percent, but is no more than 50 percent. The RSE provides a means of evaluating the

survey results. A smaller RSE indicates greater reliability of the data. Estimates with RSE’s of 25 percent or less are not marked.

** The relative standard error of the estimate exceeds 50 percent, but is no more than 75 percent.

Source: USDA, Economic Research Service, 1995 Agricultural Resource Management Study, Farm Operator Resources version only.

Table 2

Technologies used by U.S. corn growers by size of operation, 1998

	
	
		
	
		


Acres per farm

Computer technology Total 50-249 250-499 500-999 1,000 or more

Percent

Personal computer (PC) 55.6 46.2 60.4 72.7 78.4

PC for farming operation 46.2 37.6 49.2 61.5 67.2

Internet for agriculture information 21.1 15.2 24.3 29.8 39.7

Global Positioning System (GPS) 12.2 7.2 12.3 21.6 33.9

Yield monitor on combine 16.0 8.1 18.8 27.6 47.5

Monitor tied to GPS 4.5 1.3 3.8 8.6 26.2

Source: Novartis Seeds, Inc., 1998 Farm Technology Adoption Study, available at

http://novartis2.planet.net/press_releases/releases/pr_rel_923949083.html.
Rural Conditions and Trends, Vol. 10, No. 2 • 47

Agriculture and the Rural Economy

of learning from farming operations may outweigh the seemingly large differences with

specialized goods- or services-producing operations.

The value of information-intensive farming emerges from the integration of information

from production, accounting, or marketing facets of the farm enterprise to make better

management decisions for the operation as a whole. Computer use in this view is not an

add-on to increase the efficiency of individual farming tasks. Rather, the technology provides the central hub of a “farm management information system.” A marketing example

demonstrates the potential synergies. Farmers examining daily market information will

make better decisions regarding the advisability of a forward or cash contract if they have

a valid benchmark in the cost of production of the commodity. This, in turn, will require the

integration of accounting information with production decisions to comprehensively track

the cost of past and anticipated future inputs required to produce the commodity.

Sustainable agriculture provides other examples. A number of computer decision tools

are being created to assist farmers in making optimal crop rotation or pasture management plans. These tools require information from all aspects of the farm operation and

then help farmers to assess the production, economic, and environmental effects of various strategies. Here again, the technology requires the integration of diverse information.

In addition, the results generated by these tools are usually complex, requiring the weighing of various impacts in the decisionmaking process.

A common requirement of information-intensive farming practices is the ability to exploit

information from diverse sources to arrive at workable solutions to a variable set of problems. Unfortunately, these skill requirements are not as specific as, say, the ability to read

at a ninth grade level or the ability to perform specific procedures in a spreadsheet program. O*NetTM 98, a skills inventory developed by the U.S. Department of Labor, identifies the cognitive skills needed for more than 1,000 occupations. The list of complex problem solving and systems skills in table 3 identify the types of abilities that may be

required in information-intensive farming. There have been no formal job content analyses

of information-intensive farming. The skill requirements of farmers in the current version of

O*NetTM are rudimentary in comparison. However, the importance of these skills is

emerging in discussions of precision agriculture and in the use of farm management information systems more generally.

Cognitive Skills in Organizing and Interpreting Information Are Needed

While the effect of computer technology on the skill requirements of off-farm work is a

topic of considerable debate, there is one issue that is not contentious. Job security and

wages will be greater in work that uses the cognitive skills outlined above compared with

work where the technology serves mainly to automate tasks.

Examples from the insurance industry make this distinction more concrete. Automation of

insurance claims processing initially reduced skill requirements for clerks. Computers performed calculations and there was little need for clerks to make decisions or use their

own judgment. Consequently, automation initially reduced the skill needed to process

insurance claims and led to less job satisfaction.

However, the decline in job satisfaction along with the realization that worker skills were

being underused caused many firms to re-evaluate the potential benefits of computer

technology. The focus shifted from sole interest in increasing productivity (for example,

processing more claims in less time) to increasing productivity of a more valuable collection of products. For example, one company described in a book by Richard Murnane and

Frank Levy (Teaching the New Basic Skills, The Free Press, 1996, pp. 27-28) redesigned

its computer system so that every customer service representative could access information about all policies held by an individual customer. The new system gave representatives responsibility to perform multiple tasks that had previously been carried out by more

numerous specialized representatives. The system also gave customer representatives

latitude to solve complex customer service problems.
Agriculture and the Rural Economy

48 • Rural Conditions and Trends, Vol. 10, No. 2

There are also instructive examples from manufacturing. In a pulp mill that adopted computer technology, job requirements changed from the pragmatic knowledge required of

monitoring and maintaining a specific manufacturing process in the plant to a theoretical

understanding of how the plant operates. The new system in this plant required production workers to interpret data received from various parts of the plant to evaluate how his

or her decisions would affect the operation of the plant as a whole.

An important factor in the decision to modernize the mill was the belief that the new technology would result in all workers at the plant—not just managers—thinking systematically about how to improve the production process. In the words of one worker, “The more I

learn theoretically, the more I can see in the information. Raw data turns into information

with my knowledge. I find that you have to be able to know more in order to do more. It is

your understanding of the process that guides you.” (As quoted in Shoshana Zuboff, In

the Age of the Smart Machine, Basic Books, 1988, p. 94.) 

In these manufacturing and services-producing examples, as with information-intensive

farming, the economic activity requires the ability to exploit information from diverse

sources to arrive at workable solutions to a variable set of problems. It is this ability of

workers to fully exploit the value of information that differentiates the new “Information

Economy” from the waning “Industrial Economy.” Computers have been central to this

transformation. However, familiarity with computers, by itself, is insufficient. Computers

only receive, store, and process data. Workers need cognitive skills to organize these

data into valuable information. Workers competent to act on this information are then able

to increase the value of services to customers or to produce exactly the good or commodity required by the market most efficiently.

The available data suggest that the integrated use of computer technology across all

aspects of farming operations is not widespread. It is less likely that using single task

Table 3

Cross-functional skills inventory of information-intensive farming

Productive use of information technology requires problem-solving and systems skills

Skill Description

Complex problem solving skills Developed capacities used to solve novel, ill-defined problems in complex, real-world

settings

Problem identification Identifying the nature of problems

Information gathering Knowing how to find information and identifying essential information

Information organization Finding ways to structure or classify multiple pieces of information

Synthesis/reorganization Reorganizing information to get a better approach to problems or tasks

Idea generation Generating a number of different approaches to problems

Idea evaluation Evaluating the likely success of an idea in relation to the demands of the situation

Implementation planning Developing approaches for implementing an idea

Solution appraisal Observing and evaluating the outcomes of a problem solution to identify lessons learned 

or redirect efforts

Systems skills Developed capacities used to understand, monitor, and improve socio-technical systems

Visioning Developing an image of how a system should work under ideal conditions

Systems perception Determining when important changes have occurred in a system or are likely to occur

Identification of downstream Determining the long-term outcomes of a change in operations

consequences

Identification of key causes Identifying the things that must be changed to achieve a goal

Judgment and decisionmaking Weighing the relative costs and benefits of a potential action

Systems evaluation Looking at many indicators of system performance, taking into account their accuracy

Source: U.S. Department of Labor and U.S. Employment Service. O*NetTM 98 Content Model (http://www.doleta.gov/programs/onet).
Rural Conditions and Trends, Vol. 10, No. 2 • 49

Agriculture and the Rural Economy

applications such as computerized bookkeeping is going to develop the problem-solving

and systems skills that are becoming increasingly important in the nonfarm economy.

However, a significant minority of farms are using computers to bring together data from

various aspects of the farm operation to aid better decisionmaking. If the skill of current

farmers hinders adopting information-intensive farming, then there is a role for vocational

agriculture in developing computer skills.

Computers Reinforce Traditional Systems Approach to Agricultural Education

Not adopting integrated farm management information systems to bring data from all

aspects of the farm operation prevents farms from capturing the full decisionmaking benefits of information technology. A traditional strength of agricultural education—to understand the farm operation as a system—is not demonstrated in the single task adoption of

the computer. This traditional focus has been noted in discussion on how technical education—preparing students for jobs in industry—needs to be reformed (Stuart A. Rosenfeld,

“Building Industrial Competitiveness in Rural Areas,” in S.R. Johnson and S.A. Martin,

eds., Industrial Policy for Agriculture in the Global Economy, Ames, IA: Iowa State

University Press, 1993, pp. 215-16):

The computer is clearly one tool that can reinforce the traditional emphasis in problemsolving and systems skills in agricultural education. Further, cross-functionality in farm

and nonfarm skills suggests that the benefits from the cross-fertilization of agricultural

and technical education curricula may be significant. The diversification of student investment in human capital carries the greatest potential benefit. Current students could commit themselves to a program of study without the attendant fear that they are preparing

themselves for a career they may never realize. For current farmers, the real cost and risk

of investing in a new set of skills may be substantially reduced if development of these

skills increases their wages in off-farm employment. However, before these strategies can

be acted upon, educational institutions must identify the possible synergies between separate curricula allowing for the development of these cross-functional skills.

The public benefits of information-intensive farming include more efficient input use; better

documentation of crop identity, food safety through “traceback” records, environmental

compliance; and more efficient output markets leading to a more viable farming sector. A

major constraint in realizing these benefits is the skill level of farmers. However, if these

same skills can help diversify and increase returns from off-farm employment, there may

be significant private incentives for farmers in making this investment. [Tim Wojan, 202-

694-5345, twojan@ers.usda.gov]

[Agricultural education] prepared youth to manage their own

businesses; to make decisions about new technologies; to

solve technical and business problems; to understand the

entire system, from seed to store; and generally to become

community leaders....Youth enrolled in vocational agriculture

learned the value of innovation, experimentation, and cooperation and learned to make decisions. Youth enrolled in industrial

programs learned to operate equipment and follow instructions.
Increased contracting

with agribusinesses has

changed the way farms

do business. Contracting

can potentially increase

efficiency in the food system and provide a means

of quickly transmitting

consumer preferences to

farms. However, farm

operators lose some

managerial independence. Farms of all sizes

have contracts, but contracting is more prevalent

on larger farms. In some

sectors, contracting

seems to have encouraged geographic shifts in

production.

Agriculture and the Rural Economy

50 • Rural Conditions and Trends, Vol. 10, No. 2

Traditionally, independent farm operators exercised complete control over their production and marketing decisions. Each farmer decided what kind of seed, fertilizer, pesticide, or breeding stock to use. When crops and livestock were ready for market, they

were sold to the highest bidder at a local market. In recent years, agriculture has become

more “industrialized.” Farm producers are becoming tied more closely to agribusinesses

that process and market food products by arrangements that coordinate the various

stages of the food production and marketing system. Industrialization is characterized by

vertical integration between farms and processors through the use of contracts, strategic

alliances, joint ventures, and franchising.

Early in the 1900’s, the food production and marketing system delivered mainly generic

farm products that consumers prepared at home. In recent years, consumers have

changed their food consumption habits to include a wider variety of food products, more

processed foods, and more food eaten away from home. An increasingly complex food

processing and distribution system developed to meet this change in demand. As raw

agricultural commodities produced by farms were transformed by nonfarm businesses

into specific food products that consumers want, the direct link between farms and consumers had weakened. In recent years, agribusinesses have sought closer ties with farm

producers through contracting and vertical integration to increase efficiency and ensure

steady supplies of commodities with specific attributes. Through this process, farmers are

becoming more closely integrated into the food-supply chain, and they are being asked to

pay more attention to consumer demands for specific product attributes. Consequently,

the distinctions between farms and nonfarm businesses are blurring.

Contracting Coordinates Food Production

Agricultural contracts are agreements between farms and companies or other farmers

that specify conditions of producing and/or marketing an agricultural product. Food

processors and other agribusinesses use contracts to coordinate production so as to produce known quantities of standardized products with specific attributes. Contracts provide

direct feedback on market preferences and rewards to those who respond. By this means,

contracts forge a stronger, more direct link between farms and urban consumers of food

and fiber products. By replacing cash transactions in the open market, contracting offers

farm operators the advantages of reducing the risks of unknown production costs for

inputs, price swings for products, and problems in seeking a market. By assuring the price

in advance, or by receiving a fee for services, farmers also reduce the risk of unknown

income. For contractors (primarily processors and packers), these arrangements assure a

ready supply of uniform, high-quality farm products and ease inventory management

problems.

There are generally two types of contracts—marketing and production. Marketing contracts are verbal or written agreements between a contractor and a grower establishing a

price formula in advance of the product being delivered. Under marketing contracts, the

contractee (farmer) retains ownership of the product and has a large degree of decisionmaking control over the production process, but has a known market and price. Typically,

a production contract requires the contractee (producer) to relinquish most control over

production decisions, and the producer does not own the commodity being produced. In

exchange, the farmer usually receives an incentive-based fee for production services, and

the contractor reimburses a portion of the farm’s operating expenses. In addition, depending on contract terms, farmers can benefit from technical advice, managerial expertise,

and access to technological advances such as high-quality breeding stock, that may not

otherwise be readily available. A further advantage of production contracts is that the

Contracting Changes How Farms Do

Business
Rural Conditions and Trends, Vol. 10, No. 2 • 51

grower and contractor share risks of both production and marketing of the commodity,

one reason why using contracts has become so popular.

Contracting Is Widespread

Contracting has been a significant and growing part of U.S. agriculture since at least

1960. Today more than 1 in 10 farm operators report income from contract arrangements.

USDA’s 1998 Agricultural Resource Management Study (ARMS) reported that the value

of products accounted for by contracting totaled $67 billion, or 35 percent of the total

value of commodities produced in the sector (table 1). Farms of all sizes use marketing

contracts. Sixty-one percent of these farms were family-owned with gross sales of less

than $250,000, and they accounted for 20 percent of the total value of production under

contract. As farms get larger, they tend to use more contracting to market and produce

their products. Over half of the large family farms were involved in some type of contracting, and they accounted for 66 percent of the total value of commodities under contract.

Nonfamily farms, such as cooperatives, nonfamily corporations, and farms with hired

managers, can be of any size and accounted for another 15 percent of the total value of

production under contract.

Over 90 percent of the total value of production under contract was accounted for by 10

commodity groups—corn, soybeans, vegetable, fruit, nursery, cotton, cattle, hogs, poultry,

and dairy (table 2). While marketing contracts can be found in the livestock industry, they

Table 1

Use of contracting by type of farm, 1998

Contracting is common among all types of farms

Small family Large family Nonfamily

Item Unit farms farms farms All

Farms:

All farms Number 1,869,201 153,212 42,296 2,064,709

All farms Percent 90.5 7.4 2.0 100.0

Farms with contracts Percent 61.0 34.1 4.9 100.0

Value of production:

Total Million dollars 63,205 102,650 25,995 191,851

Contract value Million dollars 12,911 44,035 10,144* 67,090

Production contracts Million dollars 4,175* 17,624 5,413* 27,212

Marketing contracts Million dollars 8,736 26,410 4,731 39,878

Share of contract 

value Percent 19.2 65.6 15.1 100.0

Share of farms type with:

Contracts Percent 7.8 53.0 27.5 11.5

Production contracts Percent 1.3 19.2 2.6 2.6

Marketing contracts Percent 6.7 37.1 26.3 9.4

Value of production 

under contract Percent 20.4 42.9 39.0 35.0

Note: Coefficients of variation (C.V.’s) of estimates are less than 25 percent unless indicated otherwise. The C.V. is computed by dividing the estimate’s standard error by the estimate and multiplying by 100. Lower C.V.’s indicate more reliable estimates.

*C.V. is greater than 25 and less than or equal to 50.

Source: 1998 USDA Agricultural Resource Management Study.

Agriculture and the Rural Economy
Agriculture and the Rural Economy

52 • Rural Conditions and Trends, Vol. 10, No. 2

are used in pricing many crops, particularly specialty crops such as fresh vegetables and

fruit. More than 194,000 farms had at least one marketing contract during 1998. The

share of commodities produced under marketing contract has increased slightly over the

last few years, from 16 percent in 1991 to 21 percent in 1998. Topping the list of crops

produced under marketing contracts were fruits and vegetables, with $9.5 billion sold

through contract, 45 percent of the value of all fruits and vegetables produced. Other

crops with large shares of production value under marketing contract were cotton ($2 billion or 50 percent); corn ($2.4 billion or 12.5 percent); soybeans ($2.1 billion or 11.7 percent); and sugar beets ($1 billion or 76 percent). Almost all fluid milk is sold under marketing orders, but because neither a quantity nor a final price is set before the sale, milk producers may or may not consider the process a “contract.”

Production contracts accounted for 14 percent of the total value of production in 1998 and

approximately 3 percent of the farms had at least one production contract. Production contracts are used more on larger farms than are marketing contracts—and are more likely to

be for livestock. Poultry and poultry products accounted for 55 percent of the total value of

commodities under production contracts, and cattle and hogs another 36 percent.

Contracting Reduces, but Does Not Eliminate, Managerial Responsibility

Day-to-day management plays a key role in returns to farmers, even though, with contracting, the farmer’s role in marketing and production practices may be limited. In animal

production contracts, expert husbandry of the animals can positively contribute to the

farmer’s bottom line. And, contracting for a specific commodity is not the only decision

that the farmer makes. In addition to producing for the cash market, farmers can and do

have marketing and production contracts for the same or other commodities. And, farmers

may contract with businesses or other farmers to gain access to inputs. For example,

some farmers contract with other farmers for feed or replacement heifers. The farmer’s

skills in financial management, acquiring other inputs, coordination and management of

Table 2

Share of contract value of production for selected commodities, 1998

A few commodities account for most of the value of contract production

Commodity share Share of commodity

of all contract produced under

Commodity production contract

Percent

Corn 3.7 13.1

Soybean 3.2 12.2

Cotton 3.0 50.6

Vegetables 7.5 45.4

Fruit 8.7 56.7

Cattle 11.7* 25.3*

Hogs 5.5 42.9

Poultry 24.3 94.9

Dairy1 22.7 54.8

All other commodities 9.7 14.4

All commodities 100.0 35.0

Note: Coefficients of variation (C.V.’s) of estimates are less than 25 percent unless indicated otherwise. The

C.V. is computed by dividing the estimate’s standard error by the estimate and multiplying by 100. Lower C.V.’s

indicate more reliable estimates.

*C.V. is greater than 25 and less than or equal to 50.

1Fluid milk is typically produced under a marketing order. However, because neither price nor quantity is specified before sale, farmers may or may not consider this a “contract.”

Source: 1998 USDA Agricultural Resource Management Study.
Rural Conditions and Trends, Vol. 10, No. 2 • 53

Agriculture and the Rural Economy

the production of other commodities, and allocation of time provide returns to successful

entrepreneurship.

Not all aspects of contract arrangements are positive for farmers. Since contracts usually

specify certain practices, the loss of entrepreneurial capacity is perhaps the largest disadvantage to the farmer. Contract risk may occur when prices in the open market exceed

those specified by the contract, or the contract may be terminated on short notice.

Contractors may require upgrades to buildings and other infrastructure, resulting in investment risk that may not be foreseen by the grower. Buildings, for example, may not be

readily convertible to alternative uses if a contract is terminated. In addition, growers

operating under a relative performance system may be at an unfair disadvantage, since

companies may not have the incentives to maintain strict accuracy in the accounting and

allocation of inputs among growers. Issues between growers and integrators have led to

lawsuits on various occasions, and several States have adopted some form of legislation

regulating production contracts in agriculture.

The poultry industry has been organized as a fully integrated supply chain since new

technology in breeding, disease control, and grading eggs made large-scale commercial

broiler production possible in the 1950’s. From the hatchery to the grower to transportation to the processing plant and then to consumers, contracts coordinate the market. To

reduce transportation costs for chicks and feed, farms cluster around contractor facilities.

In addition, birds do not travel well, so having farms close to the primary processor

reduces losses in transit. The close coordination of marketing with specialized complexes,

complete with a well-developed infrastructure of local support services, now provides a

competitive advantage for the southern regions of the United States.

Compared with other farms, broiler farms have lower net income, but the contract

arrangements disguise some of the financial characteristics of contract farms. Farmers

selling their products in the open market, by definition, receive the full market value of the

product when it is sold. For broiler operations, however, the fees the farmer receives for

caring for the chickens are different from the value of the chickens. Because contractors

are intensely involved in the risks and expenses of broiler production—they own the birds

and provide feed, medical services, management advice, and a market outlet—they earn

a large proportion of the market value of the chickens.

Thus, the comparatively low sales and low income of broiler operations are somewhat

misleading. Broiler farms with sales over $50,000 have about half the asset investment of

comparable size nonpoultry farms, mainly because the contractor owns the birds and provides most of the inputs. This sharing of the resources through contracts may provide

avenues for young or beginning farmers to build their businesses with lower capital

requirements. On average, broiler producers retained approximately 39 cents per dollar of

gross sales versus 21 cents for nonpoultry farms. In addition, broiler farm households provided fewer hours to farm work (and more to off-farm work). Household income for broiler

operations was 84 percent of the average for all U.S. households in 1997. Off-farm

income is a higher proportion of their household income than on comparable farms.

However, households associated with broiler operations had lower average income from

off-farm businesses and unearned income (interest, dividends, Social Security, etc.) than

comparable households without broiler enterprises. Lower household income of households with broiler operations can be attributed in part to broiler operators’ lower average

age and fewer years of education compared with other farm operators. And, Southern

farmers may find poultry production an attractive employment alternative, given fewer offfarm employment opportunities than in Midwestern States.

Supply-chains have recently expanded to include the hog industry. Instead of farrow-tofinish operations, farmers can now specialize in each stage of production. Thus, the

farmer and contractor share input costs and management expertise. Again, adoption of

new technology has led to the increased use of contracts. Because technology has

allowed farmers to reduce their costs by increasing pigs per litter and weight per hog,

they can take advantages of economies of size and scope. Changes in the supply-chain
Agriculture and the Rural Economy

54 • Rural Conditions and Trends, Vol. 10, No. 2

have fueled the growth of hog farms. The number of farms with more than 2,000 head of

hogs increased from 29 percent in 1992 to 55 percent in 1997. With the increasing number of hogs produced, new markets were opened and exports have become increasingly

important to the hog industry in the 1990’s.

Contracting in the hog industry occurred very quickly. In less than 7 years, the industry

went from about 10 percent of the hogs under contract to more than 50 percent (fig. 1).

According to ARMS data, in 1998, the value of hogs under contract was $3.7 billion, or 43

percent of the total hog value of production. Because of the longer life cycle of hogs,

there is opportunity for contracting between each stage—breeding and farrowing, nursery,

finishing, and processing. Under production contracts, integrators or other farmers move

hogs from each stage of production to the next stage. With marketing contracts, processors buy hogs for slaughter from farmers or integrators. Farmers can and do have both

types of contracts.

Contracts Change Market Structure

Economists use farmers as an example of classic price takers. Successful farmers typically survived by lowering their costs of production, actively marketing their products, and

using strategies that helped them respond to changes in the market. Integration through

contracts in the hog and poultry industry, and now in the grain industry, provides a way to

lower costs, achieve access to the market, and respond to changes in consumer

demands. But contracting changes the way that markets function. Intermediate prices are

not visible as they are in an open market, and the only price that is public is the price to

the consumer. Thus, competitors and researchers have a more difficult time measuring

efficiencies in the production and intermediate marketing processes.

While economic incentives within agriculture continue to encourage structural change,

environmental concerns, corporate farm laws, and conflict with nonfarm neighbors will

help determine the direction of this change. Increased industrialization has environmental

0 20 40 60 80 100

Open market

Vertical

integration

Contracting

Percent

Figure 1

Share of hog production by type of vertical coordination, 1970-99

Hog contracting increased rapidly during the 1990’s

 P=preliminary.

 Source: Compiled by ERS from various studies. See Steve W. Martinez, Vertical Coordination in the Pork and 

Broiler Industries. AER-777, USDA/ERS, April 1999.

1999P

1993

1980

1970
Rural Conditions and Trends, Vol. 10, No. 2 • 55

Agriculture and the Rural Economy

and social costs. Growth of large concentrated livestock operations near population centers may create conflicts over odor and waste disposal. In many areas, farm expansion

may be limited because of farms’ proximity to environmentally sensitive lands. In these

areas, cost-saving opportunities through expanded production may become fewer. As

population increases or environmental regulations prevent expansion, incentives may shift

production back to more traditional producing areas or to new areas with opportunities for

economic growth.

In addition to changing the way markets function and in the location of markets, contracting changes who does business. Contractors provide markets and may provide inputs

and sometimes financing. Thus, a concern is that contract farms will be less likely to purchase inputs and market output in their local community. As farms consolidate and deal

more exclusively with outside contractors, rural communities with close ties to commodities could have fewer farms and fewer businesses to keep the local economy healthy.

Because farmers are sharing the value of production with other businesses, that shared

portion of the profits may not benefit the local economy.

Contract production is likely to increase, despite concerns that opponents may voice.

Industrialized agriculture has produced economic efficiencies through specialization,

mechanization, mass production and lower transaction costs. Management of the production process continues to be consolidated. At the same time, the reduced dependence of

communities on farming and related services (such as farm supply and equipment dealers, grain elevators, mills, and livestock markets) will continue a trend that has been

underway for many years. These changes, however, do not mean that small communities

must inevitably decline. Rural communities dependent on traditional farming may need to

seek new sources of economic growth. Communities will need to explore opportunities to

provide new services that meet the unique needs of farmers, such as market development, processing, packaging, transportation, and information.

Neither does contracting or vertical integration mean the end of the family farm. Ninetyeight percent of farms continue to be family owned and operated. Basic commodities will

continue to be produced in massive quantities in the most cost-efficient manner, most

often by large-scale family-owned operations. Rather than focusing on lowering production costs, or expanding operations, farmers can create market power by producing higher

value, attribute-specific commodities that consumers demand. With recent advances in

communications technology, such as the Internet, farmers will be able to participate in

strategic alliances, formal contractual or similar arrangements to create linkages with

businesses, and ultimately consumers, all over the world. [Janet Perry, 202-694-5583,

jperry@ers.usda.gov; David Banker, 202-694-5559, dbanker@ers.usda.gov]
Agriculture and the Rural Economy

56 • Rural Conditions and Trends, Vol. 10, No. 2

ERS Research on Contracting and Risk Management in

Agriculture

Contracting, other forms of vertical coordination, and risk management have become

more important in U.S. agriculture during the 1990’s. ERS has published a number

of reports on these important changes in how farms and agricultural businesses are

managed. Many of the ideas and data summarized in this article are based on these

reports, which are listed here for the interested reader. Each report was published by

ERS and is available from the ERS web site.

Joy Harwood and others, Managing Risk in Farming: Concepts, Research, and

Analysis, AER-774, March 1999.

<http://www.econ.ag.gov/epubs/pdf/aer774/index.htm>

Farm Business Economics Branch, Farmers’ Use of Marketing and Production

Contracts, AER-747, December 1996.

<http://www.econ.ag.gov/epubs/pdf/aer747/index.htm>

Janet Perry, David Banker, and Robert Green, Broiler Farmers Organization,

Management, and Performance, AIB-748, March 1999.

<http://www.econ.ag.gov/epubs/pdf/aib748/index.htm>

Steve Martinez, Vertical Coordination in the Pork and Poultry Industry, AER-777,

April 1999. <http://www.econ.ag.gov/epubs/pdf/aer777/index.htm>

William McBride, Change in U.S. Livestock Production, 1969-92, Economic Research

Service, AER-754, July 1997. <http://www.econ.ag.gov/epubs/pdf/aer754/index.htm>
Although actual urbanized area accounts for

only 2.9 percent of the

U.S. land base, urban

influence affects about

17 percent of the

Nation’s agricultural land.

Local, State, and Federal

governments have

increased their efforts

toward preserving agricultural lands and their

associated rural amenities.

Rural Conditions and Trends, Vol. 10, No. 2 • 57

Agriculture and the Rural Economy

I

n recent decades, urban development has pushed outward from city centers, in a form

that increasingly intersperses urban activities with farm activities in traditionally rural

areas. Farmers in urbanizing areas sometimes face constraints on their farming activities

when new neighbors object to odors, dust, noise, chemical use, disposal of farm wastes,

and other agricultural practices. Farmland values inevitably rise above their value in agricultural production as land becomes valued for its future use in nonfarm activities (see

box, “Importance of Farm Real Estate”). Factors unrelated to agricultural production, such

as urban proximity and potential for recreational use, become important determinants of

farmland values. Many consumers and rural residents alike feel that the irregular pattern

of development that typically accompanies recent urbanization affects the quantity and

quality of some nonmonetary benefits stemming from agricultural land use that previously

may have been taken for granted. These nonmonetary benefits can include recreational

opportunities, aesthetic enjoyment from viewing landscapes and wildlife, environmental

quality, and nostalgia related to the moral, historic, and cultural significance of rural life.

But, since these “rural amenities” cannot be bought and sold in a marketplace, collective

action is needed to conserve them. While it is neither the sole nor, in all cases, the best

form of response to these felt needs, government effort to preserve farmland has become

an increasingly common approach. In recent decades, local, State, and Federal governments, as well as nongovernmental organizations, have increased their efforts toward

preserving agriculture-related amenities via legislative initiatives to preserve farmland.

Growing Conflict Over Land Use Priorities

As the United States has become increasingly urban, with approximately 79 percent of

the population currently residing in urban places, residential and commercial development

has spread further from city centers, consuming more agricultural land in traditionally

rural areas. The unplanned, relatively low density growth is often typified by discontiguous

residential development (often interspersed with idle land, and often connected by commercial corridors along busy roads) that relies on automobiles for transportation. The level

terrain that makes farmland advantageous for agricultural production also makes these

lands attractive for housing and commercial uses. The favorable climates that are associated with major national production centers for many high-valued fruit and vegetable

crops mean that these areas, especially, are subject to intense pressure from urban

development.

Farmland is no longer an unlimited resource, as it was at the time of westward expansion,

resulting in more conflicts over land use priorities. Nowhere is this conflict more evident

and more intense than at the urban fringe, which is the principal interface between agricultural and nonagricultural uses of farmland. Along urban fringes, conflicts develop

between farmers and new suburban neighbors over farm odors, early morning noise,

commuting inconvenience, perceived health hazards posed by chemical applications, and

so forth. Farmers also may face greater economic pressure from water and land use

restrictions. Some farms on the urban fringe face crop-yield deterioration from urban

smog, theft, and vandalism. Although production near urban areas also has some offsetting economic advantages, the rural/urban conflicts, plus the economics of rising farmland

values and property taxes, give some farmers incentive to sell farmland for nonfarm

development. In some cases, the land remains in use for the production of agricultural

products, but the type and intensity of agricultural production changes.

Urbanization Affects a Large Share of

Farmland 
58 • Rural Conditions and Trends, Vol. 10, No. 2

How Much Farmland Subject to Urban Influence?

In recent years, concern over farmland preservation has been renewed. State and local

governments have implemented or considered farmland preservation measures. For

example, an unusually large number of State and local initiatives to influence urban development were on the November 1998 ballots, potentially adding to an already long list of

existing programs. The Federal Government has also taken an increasing interest in the

issue. This widespread concern may be a reaction to the spread of urban influence far

beyond the borders of statistically defined “urbanized areas” (see appendix “Data and

Definitions” in this issue for the precise definition). “Urban-influenced” is a broader term

(defined later for purposes of this analysis), referring to farmland subject to the spreading

economic and social influence of “urbanized areas.”

Although urban influence affects farms and rural areas in a number of ways, its effect on

land values is probably the easiest to observe. When urban development spreads to rural

areas, the value of urban fringe farmland increases as its value for future commercial,

industrial, and residential uses grows. For most parcels in urban-influenced areas, crop

and livestock production generates relatively less in net returns per acre than would

nonagricultural uses. Consequently, when urbanization spreads to rural areas, the market

price of potentially developable farmland is driven above its economic value for farm use.

In States where farmland is in great demand for conversion to urban use, relatively large

proportions of the market value of farmland is attributable to the nonfarm demand.

USDA’s National Agricultural Statistics Service annually collects information on farmland

values via the national June Agricultural Surveys (JAS), (see box, “Urban Influence: Data

and Classification”). Using data from the JAS for 1994-96 in conjunction with a

Geographic Information System (GIS), we examine two aspects of urbanization: How

large is the urban-influence zone in terms of farmland acres? And how much does this

influence change farmland values? For the United States, the average value of parcels

not subject to urban influence is $640 per acre (fig.1). The average value is nearly three

times higher for those parcels classified as “urban-influenced,” averaging $1,880 per acre.

Combining those two categories, the average value for “all” farmland is $850 per acre.

640

1,880

850

Not urban-influenced Urban-influenced All farmland

0

400

800

1,200

1,600

2,000

Dollars per acre

Source: Calculated by ERS from USDA’s National Agricultural Statistics Service, June Agricultural Survey data.

Figure 1

Average farmland values by classification, 1994-96

Urban influence raises farmland values

Agriculture and the Rural Economy
Rural Conditions and Trends, Vol. 10, No. 2 • 59

Agriculture and the Rural Economy

The effect of urbanization on farmland values can be estimated by assuming that the

value of agricultural parcels not subject to urban influence represents the value of land for

purely agricultural use. The effect of urbanization, then, can be estimated by finding the

difference between market value and agricultural value. Applying that technique to the

analysis of JAS data yields results indicating that urban influence accounts for 25 percent

of the market value of all U.S. farmland ($210 of the $850 per acre average) (fig.2). For

parcels within the urban-influence zone, urban influence constitutes 66 percent of market

value ($1,240 of the $1,880 per acre average).

While the large direct effect of urbanization on farmland values is well known, the extent

of the urban-influence zone is less understood. In Ohio, for instance, where the State’s

farmland is subject to the sometimes overlapping influence of three large, yet widely

spaced metropolitan areas, a large proportion of the State’s farmland is urban influenced.

The statistical design properties of the JAS data can be used to estimate the number of

acres subject to urban influence (see box, “Urban Influence: Data and Classification”).

Using the same rural/urban-influenced classification scheme, ERS estimates that about

17 percent of U.S. farmland acres are subject to urban influence (fig. 3).

The national perspective obscures the wide regional variation in urban influence. One

would expect that the most heavily populated areas, such as along the eastern seaboard,

would yield the largest effects on farmland value and the largest percentages of farmland

acres that are subject to urban influence. This is borne out by results from an analysis of

20 Land Resource Regions as defined by USDA’s Natural Resources and Conservation

Service. Figure 4 illustrates three regions for which results are reported in table 1: the

predominantly agricultural Northern Plains, the moderately urbanized Corn Belt, and a

heavily urbanized area labeled the North Atlantic Slope covering parts of Virginia,

Maryland, New Jersey, and southeastern Pennsylvania.

In the Northern Plains, very little farmland is subject to urban influence. Only 9 percent of

acreage is classified as urban-influenced (table 1). In this region, the average value of all

farmland is only 6 percent higher than the average value of strictly agricultural land.

 Source: Calculated by ERS from USDA’s National Agricultural Statistics Service, June Agricultural 

Survey data.

Figure 2

Urban-influenced and rural components of average farmland values, 1994-96

Urban influence adds an average of 25 percent to U.S. farmland values

Dollars per acre

2,000

1,600

1,200

800

400

1,240

640

210

640

Urban influence

component

Agricultural

component

Urban-influenced farmland All farmland
Agriculture and the Rural Economy

60 • Rural Conditions and Trends, Vol. 10, No. 2

Not urban-influenced

Urban-influenced farmland

 Source: Calculated by ERS from USDA’s National Agricultural Statistics Service, 

June Agricultural Survey data.

Figure 3

Rural versus urban-influenced farmland, 1994-96

While less than 3 percent of land is officially designated as "urban," 17 percent of

farmland is "urban-influenced"

17%

83%

Figure 4

Selected land resource regions

Three regions represent a wide range of urban influence

Northern Plains

Corn Belt

North 

Atlantic

Slope

Source: USDA.
Rural Conditions and Trends, Vol. 10, No. 2 • 61

Agriculture and the Rural Economy

However, for the 9 percent of farmland classified as urban-influenced, the urban-influence

accounts for nearly 40 percent of its market value.

The Corn Belt has large amounts of rural farmland, but is subject to considerably higher

levels of urban-influence than the Northern Plains. In the Corn Belt, the urban influence

component is about 14 percent of the market value of all farmland, about twice that of the

Northern Plains (table 1). For the 22 percent of farmland acres that are subject to urban

influence, that influence accounts for nearly 42 percent of market value, a percentage that

is similar to the corresponding effect in the Northern Plains.

The North Atlantic Slope is one of the most urban-influenced regions in the United States.

For this region, urban-influence accounts for about 48 percent of market value of the

region’s farmland (table 1). About 55 percent of the region’s farmland is classified as

urban-influenced. For urban-influenced parcels, about 63 percent of farmland’s market

value is attributable to the urbanization effect.

Agricultural Land Provides Multiple Benefits

In addition to producing the Nation’s food and fiber, farms have always provided many

auxiliary products that are socially beneficial, including wildlife habitat (with various

species generating value through viewing, hunting, preservation, etc.), surface water control (including storage in lakes, streams, and reservoirs and flood control), groundwater

recharge, wetlands, aesthetic experiences from viewing pastoral scenes, and open space.

Until recent decades, there was little concern over loss of such benefits due to conversion

of agricultural land to urban-related uses because these products were supplied in abundance. But as the land base becomes more urbanized, the nonpecuniary benefits associated with agricultural production become more valuable and important relative to food and

fiber production, and losses of those amenities become a source of concern.

Evolving Importance of Governmental Policy in Preservation of Rural Amenities

With the loss of farms and interspersion of urban-related activities, consumers may perceive a loss of “rural amenities,” “landscape amenities,” or “visual amenities.” But, there is

no market mechanism through which consumers can express their desires to retain these

aesthetic products. As a consequence, some form of social action may serve as a substitute for the land market’s allocative functions.

Due partially to legal and cultural tradition, State and local land use policies have been

the primary means of preserving rural amenities. Voters and taxpayers across the United

Table 1

Indicators of urban-influence for three selected regions

The geographic extent of urban influence and its degree of influence on farmland values varies considerably across regions

Urban-influence component Market value

of market value of farmland

Acres All farmland Urban-influenced Not-urban- Urban- All

influenced influenced influenced

Percent of Percent Dollars per acre

agricultural

land base

Northern Plains 9 6 40 290 480 310

Corn Belt 22 14 42 1,090 1,860 1,260

North Atlantic

Slope 55 48 63 1,970 5,300 3,790

Source: Estimated by ERS from USDA’s National Agricultural Statistics Service, June Agricultural Survey data.
Agriculture and the Rural Economy

62 • Rural Conditions and Trends, Vol. 10, No. 2

States have consistently supported State and local initiatives to encourage retention of

private land as undeveloped or “open space” land. Even though these State and local programs can take many forms, including retention of undeveloped land in the form of publicly accessible parks and recreation areas, many open space programs focus on retention of agricultural uses of land, in part reflecting the predominant presence of agriculture

in many rural areas. All 50 States have right-to-farm laws. All 50 States have some form

of use-value assessment or preferential taxation favoring farmland. Conservation easements can be purchased in 20 States, at least 20 counties have transferable development

rights programs, 16 States have agricultural district laws, and 24 States allow agricultural

protection zoning (American Farmland Trust, Saving American Farmland: What Works,

Washington, DC, pp. xiii).

The Federal role in farmland protection, while limited, appears to be expanding. The

Farmland Protection Policy Act of 1981 required Federal agencies to conduct reviews for

the purpose of “minimiz[ing] the extent to which Federal programs contribute to the

unnecessary and irreversible conversion of farmland to nonagricultural uses.” The necessary administrative rules to implement the law were adopted in 1994. The Farms for the

Future program, created by the 1990 farm bill, authorized a pilot program under which

federally subsidized loans to State and local governments were used for purchase of agricultural conservation easements on farmland. The Federal Agricultural Improvement and

Reform Act of 1996 (FAIR) superseded the latter program and directed USDA to carry out

a program to purchase agricultural conservation easements on prime and unique farmland for the purpose of protecting it from nonagricultural uses. It authorized up to $35 million (from CCC funds administered by NRCS) in matching funds for State and local farmland protection programs. More recently, Vice President Gore announced a $9.5-billion

bond proposal to curb urban sprawl and proposed $1 billion in tax credits and grants to

help communities preserve farmland, limit sprawl, and invest in cities.

Federal policies continue to have profound, indirect impacts on land use and rural landscapes, just as they have in the past. The Conservation Reserve Program (CRP) is a

recent example, where Federal policy has the effect of holding land in open space uses

for 10 years, even though the primary intent of the program was to remove marginal cropland from production. As originally conceptualized, the CRP’s purpose was soil conservation. Over time, however, policymakers recognized preservation of water quality and

enhancement of wildlife habitat as additional environmental benefits of the CRP program.

Incorporation of these latter considerations into CRP enrollment criteria highlights growing

interest in the “multifunctionality” of farmland. In addition, many other Federal programs

and policies, including estate and income tax laws, commodity programs, and highway

location affect land use allocations. Furthermore, the U.S. Government has played a role

in preserving aesthetic landscapes for at least 125 years by designating large tracts of

land as national parks, wilderness areas, and national forests.

The interest in public provision of open space amenities is not limited to the United

States, and the involvement of national governments in protecting and enhancing rural

amenities has become a contentious issue in international discussions concerned with

agricultural trade liberalization. A number of European countries have national programs

in place to conserve agricultural landscapes. The densely populated UK is an example

where national policies (and budget outlay) are explicitly directed at preserving (and

sometimes enhancing) desirable characteristics of the rural landscape. Member countries

of the EU and Japan have used Organization for Economic Cooperation and

Development (OECD) and World Trade Organization (WTO) venues to argue that preserving landscape amenities is sufficient reason to subsidize certain farmland activities in

order to retain these amenities and that these subsidies should not be seen as violations

of recent trade agreements—a position the United States and others refute. More information regarding trade issues surrounding rural amenities can be found by visiting the

Issues Center (archive on the ERS homepage under the title, “Multifunctionality in the

WTO,” or directly at <http://www.ers.usda.gov/whatsnew/issues/multifunction/index.htm>.

[Charles H. Barnard, 202-694-5602, cbarnard@ers.usda.gov]
Rural Conditions and Trends, Vol. 10, No. 2 • 63

Agriculture and the Rural Economy

Urban Influence: Data and Classification 

Farmland values data from the June Agricultural Surveys, pooled for 1994-96, consist of more

than 75,000 observations. The data are operator opinions, and the sample segments are georeferenced, meaning that parcel location information (approximate) is available in the form of

latitude and longitude. Each parcel was classified as urban-influenced or not-urban-influenced

based on an index of urban proximity derived from Census tract population data using statistical

smoothing techniques available in Geographic Information System (GIS) software. In geographer’s terminology, the index is derived from a “gravity” model of urban development, which provides measures of accessibility to population concentrations. The index accounts for both population size (within a 50-mile radius) and location of the parcel relative to that population (distance). The index increases as population increases and/or as distance from the parcel to the

population decreases—hence, the “gravity” analogy. The urban-influenced and not-urban-influenced categories were determined by examining the distribution of the index across sampled

parcels in “totally rural” census tracts. Census tracts were assigned to the “totally rural” category based on 1990 commuting data and Census Bureau geographic definitions (see appendix B,

“Definitions” in this issue). In this analysis, “totally rural” means that the tract does not contain

any part of a town of 2,500 or more residents and the primary commuting pattern was to sites

within the tract. Parcels were classified as urban-influenced if their population accessibility

index exceeded the 95th percentile of the index’s distribution for the set of “totally rural” tracts in

the region (LRR) containing the parcel.

	





Farm real estate plays an important role in the farm economy. Farmland values, in most areas

determined largely by capacity to produce food and fiber, are an important indicator of the

well-being of the farm sector. Farm real estate is the major asset of the farm sector, traditionally accounting for about three-fourths of total U.S. farm assets. Consequently, changes in

farmland value directly affect the balance sheets and solvency of farm operators who own land

in urbanizing areas. In addition to being the largest single investment item in a typical farmer’s

portfolio, farm real estate is the principal source of collateral for farm loans, enabling farm

operators to finance the purchase of additional farmland and equipment or to finance current

operating expenses.
The latest Economic

Census reports are a

valuable source of information to analysts and

policymakers in business,

Federal, State, and local

governments. The data

are the first to use the

new NAICS industry

classification system,

which includes new categories for emerging

industries in high-tech

manufacturing, communications, and services.

64 • Rural Conditions and Trends, Vol. 10, No. 2

The 1997 Economic Census

The 1997 Economic Census provides detailed information on all nonagricultural industries in the United States. Census data are a rich source of information for policymakers, business analysts, marketing specialists, planners, and economic development officials. The census includes data on sales, employment, pay, costs, and capital expenditures. Analysts can use the data to compare pay in different industries, find out what

inputs and components are purchased by various types of manufacturers, learn what

types of retail stores are the most important outlets for a particular product, or evaluate

the extent to which local businesses are capturing local retail business. Many data items

are available for geographic areas, including States, metropolitan areas, and counties.

Every 5 years, the U.S. Bureau of the Census collects data from establishments in all

U.S. industries. The bulk of the reports from the most recent 1997 Economic Census was

scheduled for release in 1999, but specialized reports, such as merchandise line sales for

retail businesses, will be released in years 2000 and 2001. A guide to the Economic

Census data can be found on the Internet at <http://www.census.gov/epcd/www/

guide.html>. The 1997 Census is the first to use the new North American Industrial

Classification System (NAICS), an updated classification of industries that replaces the

Standard Industrial Classification (SIC). The NAICS system better reflects today’s economy and makes it easier to find data on new emerging industries in high technology, communications, and service sectors that were previously lumped with other industries in the

SIC system (see box, “The North American Industrial Classification System”). The 1997

Census is the first to be released primarily on the Internet and CD-ROM. Electronic

reports can be accessed at the census web site <http://www.census.gov/prod/

www/abs/economic.html>. Analysts can conduct their own database queries to create

customized reports on industries or geographic areas at the Census Bureau’s “American

Factfinder” web site <http://factfinder.census.gov>. Only summary reports will be published in printed format.

The Economic Census covers all nonagricultural industries, including mining, manufacturing, construction, utilities, wholesale and retail trade, transportation and warehousing, and

services (separate censuses of agriculture and governments were also conducted in

1997). Number of establishments, employees, payroll, and value of output (sales, revenue, value of production) are collected for all industries. Other items, including worker

wages and hours, benefits, costs, energy consumption, purchases and expenditures, are

collected for selected industries. Data are summarized in industry and geographic reports.

Industry series reports provide detailed tabulations of national and State data for specific

industries. Geographic area series reports available for some industries tabulate basic

data for each county, metropolitan area, and place.

As this issue of Rural Conditions and Trends was being written, only a small portion of the

data had been released. In this issue, we provide two brief examples of how the

Economic Census data can be used. First, an analysis of the semiconductor industry

shows how industry report series data can be used to profile an important industry. We

then provide a brief analysis of retail trade patterns in Montana to show how geographic

area series data can be used to analyze regional development issues. [Fred Gale, 202-

694-5349, fgale@ers.usda.gov]

Economic Census Provides Detailed Picture

of U.S. Industry
Rural Conditions and Trends, Vol. 10, No. 2 • 65

The 1997 Economic Census

The North American Industrial Classification System

The North American Industrial Classification System (NAICS) is replacing the Standard Industrial Classification system in the reporting of industry statistics by the Federal Government. The 1997 Economic Census is the first data

product to use the NAICS system. NAICS was developed jointly by the United States, Canada, and Mexico to provide a uniform statistical system across North America. Information on the classification system and how it compares with the SIC codes can be found on the Internet at <http://www.census.gov/epcd/www/naics.html>.

The NAICS codes follow a hierarchy, with two-digit codes assigned to broad sectors such as mining, construction,

manufacturing, and six-digit codes for the most detailed industries. For example, manufacturing industries NAICS

codes begin with “3” as the first digit. NAICS 334 is Computer and Electronic Product Manufacturing. That category

includes six subcategories represented by four-digit codes 3341 through 3346 listed in table 1. The most detailed

industries have six-digit codes. The Semiconductor and Other Electronic Components (NAICS 3344) category has

eight six-digit industries. Seven of these industries correspond exactly to codes in the old SIC classification.

However, establishments in NAICS 334418, Printed Circuit Assembly, were formerly found in three different SIC categories: 3577, 3679, and 3661. The value of the NAICS is in its ability to more easily analyze data for newly

emerged industries such as Printed Circuit Assembly, which were hidden in various categories in the SIC classification. However, it also presents a difficulty in matching new data tabulated under the NAICS system with earlier SICbased data.



	


				


NAICS Description SIC Description

334 Computer and Electronic Product Manufacturing

3341 Computer and Peripheral Equipment Manufacturing

3342 Communications Equipment Manufacturing

3343 Audio and Video Equipment Manufacturing

3344 Semiconductor and Other Electronic Components 

334411 Electron Tube Manufacturing 3671 Electron tubes

334412 Bare Printed Circuit Board Manufacturing 3672 Printed circuit boards

334413 Semiconductor and Related Devices 3674 Semiconductors, related devices

334414 Electronic Capacitor Manufacturing 3675 Electronic capacitors

334415 Electronic Resistor Manufacturing 3676 Electronic resistors

334416 Electronic Coil, Transformer, and Other Inductors 3677 Electronic coils, transformers

334417 Electronic Connector Manufacturing 3678 Electronic connectors

334418 Printed Circuit Assembly (Electronic Assembly) 3577 Computer peripheral equipment, 

not elsewhere classified

3679 Electronic components, not 

elsewhere classified

3661 Telephone and telegraph apparatus

(consumer external modems)

334419 Other Electronic Component Manufacturing 3679 Electronic components, not 

elsewhere classified

3345 Navigational, Measuring, Electromedical, 

and Control Instruments Manufacturing

3346 Manufacturing and Reproducing Magnetic and 

Optical Media

Source: U.S. Bureau of the Census.
Economic Census data

show that semiconductor

manufacturing is a rapidly growing industry. It is

geographically concentrated, but rural areas

may become more

attractive to semiconductor manufacturers.

66 • Rural Conditions and Trends, Vol. 10, No. 2

The 1997 Economic Census

As microprocessors have been introduced into more and more products, the semiconductor manufacturing industry has grown rapidly. The Semiconductor Association of

America reported worldwide semiconductor sales of over $11 billion per month in mid1999. U.S. employment in the sector grew more than 25 percent from 1993 to 1999. Over

that same period, other manufacturing industries generally posted only slight gains in

employment (fig.1). Semiconductor manufacturing jobs are also highly paid, averaging

$18 per hour for production workers in mid-1999, compared with an average for all manufacturing of under $14.

Drawn by the allure of the industry’s growth in high-paying skilled jobs, relatively low

emission of pollutants, and its “high-tech” image, economic development officials have

offered expensive enticements for companies to locate semiconductor plants in their communities or States. The 1997 Economic Census provides information about growth in production, capital expenditures, employee earnings, and materials purchases for the semiconductor industry. This type of information can help local and State officials make

informed decisions about industry recruitment, regional planning, and other issues.

Industry Shipments More Than Doubled Between 1992 and 1997

The 1997 Economic Census reports 980 companies operating 1,082 establishments in

the North American Industrial Classification (NAICS) category 334413, “Semiconductors

and Related Devices” (table 1). Comparison with the 1992 Economic Census shows that

the industry added 157 companies and 160 establishments between 1992 and 1997.

(NAICS category 334413 is equivalent to the Standard Industrial Classification (SIC) cateSemiconductor Industry Growing Rapidly

1990 91 92 93 94 95 96 97 98 99

80

90

100

110

120

Index (1990=100)

Figure 1

Employment growth in semiconductor and all manufacturing industries, 1990-99

Employment in semiconductor manufacturing grew rapidly during the mid-1990’s

Source: ERS analysis of Bureau of Labor Statistics data.

Semiconductors

All manufacturing
Rural Conditions and Trends, Vol. 10, No. 2 • 67

gory 3674 used in previous economic censuses, facilitating easy comparison with previous years.) Employment rose by 25,919 jobs, a 15-percent increase. However, these

increases appear to understate the actual growth of the industry. The number of production workers (those actually involved in production operations, excluding most administrative, management, and research personnel) and the number of hours each increased

about 25 percent. Even more rapid growth in the value of industry shipments indicates

that production grew even faster than labor input. The value of industry shipments rose a

staggering 135 percent during 1992-97, reaching $78 billion in 1997. This figure is not

adjusted for inflation—semiconductor prices actually fell in price. The rapid growth in

value added suggests that worker productivity increased considerably.

The value of shipments may overstate the physical product turned out by the industry

because the value is double-counted when intermediate products produced by one establishment are sold to another establishment within the same industry to manufacture a

final product. The Economic Census reports value added, a measure of output that avoids

the double-counting problem. Value added is the difference between the value of product

shipments and the cost of materials, supplies, containers, fuel, purchased electricity, and

contract work. In 1997, the semiconductors industry purchased materials and supplies

valued at nearly $15 billion, and produced value added of $63.75 billion. The value of

materials purchases grew by only 52 percent between 1992 and 1997, much slower than

the 135 percent growth in value of product shipments. This means that value added grew

even faster than shipments—174 percent—between 1992 and 1997.

Growth in Worker Productivity and Wages

Value added per worker, a common measure of worker productivity, was $321,760 for the

semiconductor industry in 1997 (table 1). This value is considerably higher than for other

industries. In related electronic components industries (such as circuit boards, capacitors,

electron tubes) value added per worker ranged between $50,000 and $100,000. The total

for all manufacturing was not available at the time of writing, but the 1996 estimate from

the Census Bureau’s Annual Survey of Manufactures was $93,737. Since semiconductor

industry value added grew faster than the number of workers between 1992 and 1997,

productivity (as measured by value added per worker) also grew rapidly. Value added per

worker grew by $186,000 in the 5 years from 1992 to 1997, an increase of 138 percent.

The 1997 Economic Census

Table 1

Production and employment in the U.S. semiconductor industry, 1992-97

All measures indicate rapid growth in the semiconductor industry

Item Unit 1992 1997 Percent change

Companies Number 823 980 19.1

Establishments Number 922 1,082 17.4

Value of shipments Billion dollars 33.2 78.0 135.1

Cost of materials Billion dollars 9.8 15.0 52.0

Value added Billion dollars 23.3 63.7 173.6

Capital expenditures Billion dollars 3.1 10.5 237.5

Employment Number 172,200 198,119 15.1

Production workers Number 84,800 105,781 24.7

Payroll Million dollars 6,893 9,994 45.0

Benefits Million dollars 1,564 2,250 43.9

Value added per worker Dollars 135,290 321,760 137.8

Earnings per worker Dollars 40,030 50,450 26.0

Benefits per worker Dollars 9,080 11,360 25.0

Production worker hourly wage Dollars 13.54 16.36 20.8

Capital expenditures per worker Dollars 18,121 53,165 99.3

Note: Data are for NAICS sector 334413 for 1997 and SIC 3674 for 1992. Not adjusted for inflation.

Source: ERS analysis of U.S. Bureau of the Census, Economic Census.
68 • Rural Conditions and Trends, Vol. 10, No. 2

The 1997 Economic Census

Increases in wages are usually linked to growth in worker productivity. As the value of output produced by a worker increases, companies are willing to pay workers more. The

Economic Census data show that wages grew rapidly in the semiconductor industry, but

growth in wages absorbed only a small share of the increase in productivity. Wages and

salaries per worker rose from $40,030 to $50,450 between 1992 and 1997, an increase

of 26 percent. The general level of inflation was 12.7 percent over the period, so this represents an increase in real wages. Nonwage benefits rose at a similar rate of 25 percent,

from $9,080 to $11,360 per worker. However, earnings for production-line workers grew

more slowly. Average hourly wages for semiconductor production workers grew 20.8 percent from $13.54 to $16.56. While growth in wages did not keep up with growth in value

added in the semiconductor industry, the growth in both wages and employment experienced by the industry stands in contrast to the generally stagnant picture in most U.S.

manufacturing industries. Wages in the semiconductor industry were significantly higher

and grew faster than wages in other manufacturing industries. Earnings per worker for all

manufacturing were $33,770 in 1997, $16,230 less than the average for the semiconductor industry. Average wages for all manufacturing rose only 10 percent between 1992 and

1997, less than half the 26-percent increase in the semiconductor industry. In addition,

total manufacturing employment fell by 6.9 percent between 1992 and 1997.

Another indicator of the semiconductor industry’s rapid growth is its high level of capital

expenditures. The industry made an average of $53,000 in capital expenditures for every

employee in 1997. This is a very high rate of investment per worker. In 1996, capital

expenditures for all manufacturing were less than $7,500 per worker (the data for 1997

were not available when this article was written), so clearly the semiconductor industry

was expanding capacity more rapidly than other manufacturing sectors were. The high

investment of capital per worker is consistent with the high and increasing productivity

indicated by the value added per worker figures. Total capital expenditures in 1997 were

$10.5 billion, including $1.9 billion spent on buildings and facilities, and $8.6 billion spent

on machinery and equipment. The industry’s assets were valued at $59.57 billion at the

end of 1997, over $300,000 per worker.

A Variety of Raw Materials Are Purchased

The Economic Census provides detailed information on the range of products made and

the materials consumed by each industry. Materials purchases can help analysts evaluate

the backward linkages to suppliers in a particular industry. Knowledge of what materials

are purchased by manufacturers is helpful in determining whether a community has adequate access to suppliers to attract a plant in a given industry. It is also useful for estimating local economic impacts of manufacturing plants. The census lists 35 types of materials, components, equipment, and parts that are consumed by manufacturers in the semiconductor industry. They are summarized in 10 categories shown in figure 2. The largest

single categories of materials are hyperpure silicon (the basic raw material for semiconductors) and semiconductors themselves, each of which had purchases of $1.5 billion in

1997. (Semiconductors are purchased as intermediate products to be used in the manufacture of semiconductor-based microprocessors, integrated circuits, and other products.)

Other expenditures are for a variety of raw materials, including basic metals and alloys,

plastics, chemicals, and gases, fabricated metal products, computing, communications,

optical equipment, instruments, and a large “other materials” category, for which materials

were not specified. Expenditures for many materials increased rapidly between 1992 and

1997, indicating that growth in semiconductor production benefited many supplying industries. Expenditures on silicon more than doubled from $675 million to $1.5 billion, and purchases of bolts, nuts, screws, washers, and rivets rose from $3 million to $16.7 million

between 1992 and 1997. Other expenses collected by the Economic Census include

quantity of electricity consumed, expenditures on electricity, purchased services, and

rental payments.
Rural Conditions and Trends, Vol. 10, No. 2 • 69

The 1997 Economic Census

Semiconductor Manufacturing Is Geographically Concentrated

Semiconductor manufacturers are desirable targets of industry recruiters because they

are a growing industry, pay high wages, and employ a relatively educated labor force.

While Economic Census data paint a picture of a rapidly growing industry, the prospects

of recruiting semiconductor plants for rural communities appear discouraging.

The semiconductor industry is geographically concentrated in the West, Southwest, and

Northeast. The two dominant States, California (27.6 percent) and Texas (28.7 percent),

had a combined share of 46 percent of semiconductor jobs in 1997 (table 2). However,

their share of industry value added was smaller, at 35.3 percent. Arizona, with only onethird as many semiconductor workers as California, recorded value added of $9.7 billion,

only 12 percent less than California’s total. Oregon and Washington also had shares of

value added much greater than their share of employment.

California and Texas received the largest share of semiconductor capital expenditures, but

the ratio of capital expenditures to workers suggests that capacity is expanding rapidly in

other States. On average, the semiconductor industry made about $53,000 in capital

expenditures per worker. In Oregon and Washington, investment was far higher, at

$143,500 and $117,000 per worker, respectively. Investment in Arizona and Florida was

also above the average, at $74,000 and $65,000 per worker. Texas, Colorado, and

Minnesota each had capital expenditures of between $50,000 and $60,000 per worker. All

other States had expenditures below $50,000 per worker, including California, at $44,800.

The semiconductor industry is heavily urbanized. According to the Census Bureau’s

County Business Patterns data, only 62 out of 940 semiconductor manufacturing establishments were in nonmetro areas. (Economic Census data on establishments by county

had not yet been released when this article was written.) Three-fourths (682) of semiconductor manufacturing establishments were located in large metropolitan areas with population of 1 million or more. Another 15.6 percent of establishments were in metro areas

with populations of 500,000 to 1 million, and only 26 establishments were in small metro

areas.

In 1995, 50 nonmetro counties had semiconductor establishments, with estimated

employment totaling nearly 8,000 jobs (5 percent of the industry total). Nonmetro establishments were scattered across the country, but were largely concentrated in the West,

Silicon

Semiconductors

Other electronic

components

Silicon chips

Basic metals Chemicals, plastics, gases

Metal products

Equipment

Paper products

Other

 Source: ERS analysis of U.S. Bureau of the Census, 1997 Economic Census.

Figure 2

Semiconductor industry purchases of materials, 1992

Semiconductor manufacturers purchase a variety of raw materials
70 • Rural Conditions and Trends, Vol. 10, No. 2

The 1997 Economic Census

Northeast, and Midwest (fig. 3). Pennsylvania had the most nonmetro semiconductor

establishments (seven), followed by Iowa (six). However, most of these establishments

were very small. The three Oregon establishments accounted for about half of nonmetro

employment in semiconductors.

Rural Locations May Become More Attractive

The semiconductor industry appears to be on the upswing of the “product cycle.”

According to the product cycle theory, new, innovative industries tend to prefer urban

locations where they have access to new ideas, knowledge, and innovation. The geographic concentration of semiconductor establishments seems to be in line with this theory. However, the product cycle suggests that rural locations may become more attractive.

As the semiconductor industry matures, it may become more conscious of costs and less

concerned about innovation, making rural areas with lower land and facilities costs more

attractive. A couple of other factors may brighten prospects for rural areas to gain a

greater share of this industry. Advances in telecommunications improve access to information in rural areas, and natural amenities of rural areas may be particularly attractive to

environmentally conscious managers and employees in this industry. However, rural areas

also must compete with overseas locations in Asia and other regions where labor costs

are often lower and environmental and other regulations can be less stringent. [Fred Gale,

202-694-5349, fgale@ers.usda.gov]

Table 2

Semiconductor employment, value added, and capital expenditures by State, 1997

California and Texas are the leading employers in the semiconductor industry, but several other States 

had higher levels of capital investment per worker

Capital

Capital expenditures

State1 Employment Value added expenditures per worker

Number Million dollars Thousand dollars

California 54,597 10,969.1 2,446.4 44.8

Texas 37,088 11,549.2 2,110.9 56.9

Arizona 18,070 9,701.8 1,346.4 74.5

Massachusetts 9,387 1,358.5 261.1 27.8

Oregon 8,309 7,075.8 1,192.6 143.5

Pennsylvania 7,916 3,514.5 230.4 29.1

New York 7,830 625.6 98.7 12.6

Colorado 4,953 1,093.8 258.7 52.2

Florida 3,452 513.6 224.3 65.0

Washington 3,104 350.3 363.5 117.1

Minnesota 2,036 264.7 106.1 52.1

New Jersey 1,934 241.1 74.4 38.4

Ohio 1,932 278.5 35.2 18.2

North Carolina 1,796 166.9 81.9 45.6

New Hampshire 1,450 209.8 57.4 39.6

Connecticut 629 91.9 11.1 17.6

Utah 613 8.5 6.6 10.7

Maryland 594 42.8 18.1 30.4

Wisconsin 519 34.1 1.7 3.2

Illinois 407 38.8 9.6 23.6

Michigan 331 21.2 5.6 16.9

Other States 31,172 15,596.7 1,592.3 51.1

Total 198,119 63,747.2 10,532.9 53.2

1States with less than 100 employees and those for which operations of individual firms might be disclosed are not shown.

Source: Calculated by ERS from U.S. Bureau of the Census, 1997 Economic Census data.
Rural Conditions and Trends, Vol. 10, No. 2 • 71

The 1997 Economic Census

 Metro

 Nonmetro

Figure 3

Metro and nonmetro semiconductor establishments, 1995

Semiconductor manufacturers are geographically concentrated in the West, Northeast, Midwest, and parts of

Texas and Florida

 Source: Calculated by ERS from U.S. Bureau of the Census, 1995 County Business Patterns data.

Establishments
Economic Census data

show differences in

spending in rural States

like Montana. The mostrural counties lose about

40 percent of their retail

spending to larger towns

and cities, but the effects

on local economies are

small and stable.

72 • Rural Conditions and Trends, Vol. 10, No. 2

The 1997 Economic Census

Economic Census data are a rich source of information about geographic patterns ofretail trade, a sector that provides about 15 percent of rural jobs. Many rural communities are concerned about the loss of local retail activity to larger towns and cities. Loss of

retail trade means not only loss of jobs, but also symbolizes decline of small town “main

streets.” State and local officials are also interested in retail trade because sales taxes are

an important source of revenue in most States. This article shows how Economic Census

data can be used to analyze retail sales, using Montana as a case study. (When this article was written, geographic data were available only for Montana and nine other Western

States, but data for most States should be available by the time of publication.) 

In 1997, Montana had 5,042 retail establishments with at least one employee and those

establishments together had sales of $7.78 billion. (Data for nonemployer establishments

will be released later.) The largest retail sectors were automotive dealers ($2.1 billion),

food and beverage stores ($1.3 billion), general merchandise stores ($1.1 billion), building materials and garden supply stores ($932 million), and gasoline service stations

($754 million). Seven other retail sectors had sales ranging between $150 million and

$250 million.

High Transportation- and Building-Related Spending 

Montana’s retail sales per capita in 1997 were $8,853. Figure 1 compares retail sales per

capita for Montana with nine other States for which data were available at the time this

article was written. Retail sales in Montana were lower than in seven other Western

States. Of the 10 States for which data were available, only California and New Mexico

Completely Rural Montana Counties Lost

Fewer Retail Dollars in 1997

South Dakota

Nevada

Colorado

Utah

Arizona

Idaho

Wyoming

Montana

New Mexico

California

0 4,000 8,000 12,000 16,000

15,869

10,854

10,415

9,668

9,655

9,637

9,438

8,853

8,692

8,176

Dollars

Source: Calculated by ERS from 1997 Economic Census data.

Figure 1

Per capita retail sales for 10 States, 1997

Montana sales per capita are lower than in most neighboring States
Rural Conditions and Trends, Vol. 10, No. 2 • 73

had lower sales than Montana. South Dakota’s sales are clearly higher than other States.

Closer inspection of the data shows that this is due to high sales by “nonstore retailers,”

largely due to the presence of Gateway Computers in North Sioux City, South Dakota.

(When this category is excluded, per capita sales in South Dakota are similar to sales in

other States.) Nevada and Colorado have per capita incomes about $7,000 higher than

other States in the region and are important tourist destinations, which probably accounts

for their high per capita sales. Comparing Montana and Idaho (two States with nearly

identical per capita incomes) per capita sales by category shows that higher sales of

motor vehicles and nonstore retailers account for the higher level of per capita retail sales

in Idaho.

Comparing per capita retail sales by category between California, a largely urban State,

and Montana provides insight about different retail patterns between urban and rural

States (fig. 2). Montana’s higher retail sales can be attributed to higher sales in motor

vehicles, gasoline stations, building materials and garden supply stores, and general merchandise stores. Greater expenditures on motor vehicles and gasoline reflect the greater

reliance on automobile transportation in a sparsely populated State like Montana, in comparison with California. Building and garden supplies sales may reflect greater construction, home improvements, and landscaping in Montana, which was gaining population in

the mid-1990’s. The greater amount of open space in Montana also may increase spending on landscaping and gardening supplies. Higher spending in general merchandise

stores reflects the greater popularity of discount mass merchandisers in rural areas. In

contrast, California had higher retail sales in clothing, health and personal care, and electronics and appliance stores. These reflect differences in preferences and spending on

luxury items in California, where personal income is higher. Per capita spending in other

types of stores was very similar between the two States.

The 1997 Economic Census

Motor vehicle and parts dealers

Food and beverage stores

General merchandise stores

Building material and garden

Gasoline stations

Sports, hobby, book, music

Clothing

Miscellaneous store retailers

Health and personal care stores

Furniture

Nonstore retailers

Electronics/appliance

0 500 1,000 1,500 2,000 2,500

California

Source: Calculated by ERS from 1997 Economic Census data.

Type of retail establishment

Dollars

Montana

Figure 2

Per capita retail sales by sector, Montana and California, 1997

Montana residents spent more per capita at motor vehicle dealers, gas stations, general

merchandise stores, and building material and garden supply stores
74 • Rural Conditions and Trends, Vol. 10, No. 2

Large Share of Spending Leaks From Completely Rural Counties

While per capita sales do not vary that much from State to State, they vary considerably

across counties, since residents of small communities often cross county lines when they

make shopping trips to large towns and cities. Comparing retail sales for rural and urban

Montana counties makes this clear (fig. 3). Completely rural counties (with less than

2,500 people living in urban places) had per capita retail sales of $4,700 in 1997, about

$4,150 under the Statewide average. Less-urbanized nonmetro counties (where between

2,500 and 10,000 people live in urban places) had per capita sales of $6,100, still considerably less than the Statewide average. Urbanized nonmetro counties (with at least

10,000 people living in urban places) had per capita sales of $10,800, and the two metropolitan counties in Montana (the Great Falls and Billings metro areas) had sales of

$11,600. Higher incomes in the more urbanized counties may explain part of the difference in sales, but it seems clear that retail expenditures are “leaking” from small rural

counties to more urbanized “retail trade centers.” Using Statewide average per capita

retail sales as an estimate of retail expenditures per person with an adjustment for differences in income, one can estimate a “pull factor” that estimates the extent to which a

community captures retail expenditures of its residents. Completely rural counties capture

an estimated 60 percent of their residents’ retail expenditures, which means residents

make 40 percent of their retail expenditures outside their county of residence. Less-urbanized nonmetro counties do better, capturing 80 percent of local retail trade. In contrast,

urbanized nonmetro counties attracted per capita sales that were an estimated 15 percent greater than expenditures by their residents, while sales in metro counties were 18

percent higher than their residents’ estimated expenditures.

The employment effects of these retail trade patterns are fairly small. In dollar terms,

about $740 million in retail expenditures “leaked” from completely rural and less-urbanized

counties, combined. Assuming one job for every $161,000 of retail sales (the State average), that translates to an equivalent of about 4,600 retail jobs. That works out to an average of 96 jobs per county lost to retail sales leakage for the 58 completely rural and less17,211 16,871

21,098

22,255

Completely rural Less-urbanized Urbanized

nonmetro

Metro

0

5,000

10,000

15,000

20,000

25,000

Dollars

Source: ERS analysis of 1997 Economic Census.

Figure 3

Per capita income and retail sales by Montana county type, 1997

Per capita sales are much lower in rural counties

Per capita

income

Per capita

sales

4,686 6,107

10,787 11,609

The 1997 Economic Census
Rural Conditions and Trends, Vol. 10, No. 2 • 75

The 1997 Economic Census

urbanized Montana counties. In 1997, the average retail job paid about $15,400 in

Montana.

Leakage From Completely Rural Counties Seems To Have Fallen

The most interesting question is whether the rate of leakage is accelerating. Comparison

with 1992 data indicates that completely rural Montana counties actually reduced their

leakage between 1992 and 1997. Using the same method to estimate pull factors for

1992 yields an estimated leakage rate of 47 percent for completely rural counties, higher

than the 40 percent estimated for 1997. However, for less-urbanized Montana counties

the leakage rate rose slightly from 16 to 20 percent. This comparison is not entirely valid

because the composition of the retail trade sector changed, due to the new North

American Industrial Classification System (NAICS). The biggest change in the NAICS is

the exclusion of eating and drinking places, which were included in the Standard

Industrial Classification retail sector in 1992 (see box, “NAICS Excludes Food Service

From Retail Sector”). However, eating and drinking places are one of the most geographically dispersed industries, so leaving this sector out should increase the rate of retail

leakage. More careful analysis is needed to arrive at stronger conclusions, but it appears

that rural retail is fairly stable in Montana. The situation may be quite different in other

rural regions, however. Earlier research found that leakage was falling in Western rural

areas, but increasing in farming areas of the Midwest and Great Plains. [Fred Gale, 202-

695-5349, fgale@ers.usda.gov]

NAICS Excludes Food Services From Retail Sector

Food service establishments (formerly eating and drinking places, SIC 58) were a large retail

sector under the Standard Industrial Classification system, but the NAICS now classifies this as

a service industry. Montana food service establishments had sales of $861 million in 1997, so

the sector’s exclusion from the retail sector makes it difficult to compare retail figures between

the NAICS and SIC classifications. Other problems are introduced by the NAICS inclusion of a

small number of wholesaling establishments that sell directly to the public. These establishments were formerly classified as parts of several wholesale sectors under the SIC. Analysts

cannot adjust for this change using published data, but the share of sales in these sectors is so

small that the effect on most analyses will not be noticeable.
Data Sources

76 • Rural Conditions and Trends, Vol. 10, No. 2

Appendix A: Data Sources

Census of Agriculture is an enumeration of all U.S. farms conducted every 5 years. A

farm is currently defined as any place that sells, or normally would sell, at least $1,000 of

agricultural products annually. USDA conducted the most recent Census of Agriculture in

1997. For publications and more information, see <http://www.nass.usda.gov/census/>.

The U.S. Bureau of the Census conducted agricultural censuses for 1992 and earlier

years.

County Business Patterns. The U.S. Bureau of the Census publishes an annual series,

the County Business Patterns, that provides estimates of employment, establishments,

and payroll by industry for each U.S. county. These data are the most comprehensive

source of information on geographic patterns of employment for detailed industries. For

more information, access to databases and electronic publications, see <http://www.census.gov/epcd/cbp/view/cbpview.html>. The Census Bureau does not publish data that

could disclose information about the operations of individual companies or establishments. To account for these confidential data, ERS uses an enhanced County Business

Patterns file (acquired from a private vendor) that imputes values for the suppressed data.

Employees totally exempt from the Federal Insurance Contribution Act (farm operators

and other self-employed persons, hired farm workers, most government employees, railroad workers, and domestic service workers) are not counted by County Business

Patterns.

Economic Census is an enumeration of all nonagricultural businesses conducted by the

U.S. Bureau of the Census at 5-year intervals. Data on number of establishments,

employment, payroll, output or sales, and other variables are collected from all U.S. business establishments. The most recent economic census was in 1997. Preliminary data

are described in several articles in this issue. For more information, see <http://www.census.gov/epcd/www/guide.html>.

Macroeconomic Data. The economic indicators used to monitor macroeconomic

changes in the U.S. economy are derived from Federal sources. Measures of inflation,

including the consumer and producer prices indexes, productivity, employment cost, and

employment and unemployment data are developed by the U.S. Department of Labor’s

Bureau of Labor Statistics (BLS), see <http://www.bls.gov>.

National income and product account (NIPA) information on capital investment, gross

domestic product, and net exports is produced by the Bureau of Economic Analysis

(BEA), U.S. Department of Commerce. On October 28, 1999, BEA released new NIPA

estimates that incorporate a number of major definitional and statistical improvements

designed to better measure the evolving U.S. economy. Information about BEA’s recent

comprehensive revision of the NIPA accounts is available at

<http://www.bea.doc.gov/bea/an1.htm>. Macroeconomic data and Food and Fiber System

estimates published in this issue of Rural Conditions and Trends reflect the revised NIPA

data, and may not match data published in earlier issues.

Information on monetary policy (including changes in interest rates and foreign exchange

rates) and industrial production data are obtained from the Federal Reserve Board.

Employment Data. Data on metro and nonmetro employment and unemployment reported in this issue come from three sources. The monthly Current Population Survey (CPS),

conducted by the Bureau of the Census for the Bureau of Labor Statistics, U.S.

Department of Labor, provides detailed information on the labor force, employment,

unemployment, and demographic characteristics of the metro and nonmetro population.

The CPS derives estimates based on interviews of a national sample of about 47,000

households that are representative of the U.S. civilian noninstitutional population 16 years

of age and over. Labor force information is based on respondents’ activity during 1 week

each month. Among the data products of the CPS are the monthly files, the earnings

microdata files, and the March Annual Demographic Supplement (known as the March

CPS). For more information, see <http://www.bls.gov/cpshome.htm>.
Rural Conditions and Trends, Vol. 10, No. 2 • 77

Appendix A: Data Sources

BLS county-level employment data, the Local Area Unemployment Statistics (LAUS), are

taken from unemployment insurance claims and State surveys of established payrolls

which are then benchmarked to State totals from the CPS. The BLS data series provides

monthly estimates of labor force, employment, and unemployment for individual counties.

For more information, see <http://www.bls.gov/lauhome.htm>.

BEA employment data, unlike the household data collected by the CPS and BLS, provide

establishment data on the number of jobs rather than the number of workers. The BEA

data are taken primarily from administrative reports filed by employers covered under

unemployment insurance laws and from information from the Internal Revenue Service

and the Social Security Administration. Thus, jobs and earnings for these jobs are counted at the place of work and are based on a virtual universal count rather than a sample.

The BEA data provide detailed information on the number of jobs and amount of earnings

by industry at the county level. A shortcoming of the BEA data is the 2-year lag between

when they are collected and when they are available for analysis.

Each of these data sets has its advantages and disadvantages. The CPS furnishes

detailed employment, unemployment, and demographic data for metro and nonmetro portions of the Nation. The LAUS provides less detailed employment data than the CPS, but

offers very current employment and unemployment information at the county level. The

BEA provides estimates of the number of jobs and earnings by industry for individual

county areas (as well as States and metropolitan areas). For access to the BEA database, see <http://fisher.lib.virginia.edu/reis/index.html>.

While these data sources are likely to provide different estimates of employment conditions at any point in time, they generally indicate similar trends. For a comprehensive listing of regional economic data available online, see <http://www.econdata.net>.

June Agricultural Survey is a national survey of farmland values conducted annually by

USDA. For more information about USDA estimates of agricultural land values, see

<http://usda.mannlib.cornell.edu/reports/nassr/other/plr-bb/>.

Agricultural Resource Management Study (ARMS) is an annual survey that collects

detailed information on financial status, production, and management of a nationwide

sample of U.S. farms. The ARMS survey is conducted annually by USDA’s National

Agricultural Statistics Service, and is the most comprehensive national annual data available on farm financial and operating characteristics. The sample is chosen carefully to be

representative of all U.S. farm operations. The ARMS is a probability-based survey, where

each respondent represents a number of farms of similar size and type. Thus, the sample

data can be expanded to represent the entire farm sector for the contiguous 48 States.
Definitions

Appendix B: Definitions

78 • Rural Conditions and Trends, Vol. 10, No. 2

Farming-dependent county — Farming contributed a weighted annual average of 20

percent or more of total labor and proprietor income over the 3 years of 1987-89. County

typology codes are described in Peggy J. Cook and Karen L. Mizer, The Revised ERS

County Typology: An Overview, RDRR-89, U.S. Department of Agriculture, Economic

Research Service, December 1994.

Farm Types

Small family farms – Sales less than $250,000 per year.

Larger family farms – Sales above $250,000 per year.

Nonfamily farms – Farms organized as nonfamily corporations or cooperatives, as well as

farms operated by hired managers.

Goods-producing industries. Industries that primarily produce physical goods or commodities: farming, agricultural services, manufacturing, mining, and construction.

Input-output model. An economic model that represents the economy as a set of sales

and purchases between sectors, final demands, and payments to labor, capital, profits,

and indirect business taxes.

Land in farms (farmland or agricultural land) consists primarily of agricultural land used

for crops, pasture, or grazing on any place from which $1,000 or more of agricultural

products were produced and sold, or normally would have been sold, during the census

year.

Metropolitan Statistical Areas (MSA’s) are defined by the Office of Management and

Budget in terms of counties, except in New England, where the definitions are in terms of

cities and towns. Additional contiguous counties are included in the MSA if they are economically and socially integrated with the core county. Metro areas are divided into central

cities and areas outside central cities (suburbs). Throughout most of this publication,

“urban” and “metro” have been used interchangeably to refer to people and places within

MSA’s. The entire territory of the United States is classified as metropolitan (inside an

MSA or CMSA) or nonmetropolitan. In this issue, the article, “Urbanization Affects a Large

Share of Farmland,” uses a measure based on farmland values to identify areas where

land values are subject to urbanization effects to show that urbanization can affect places

outside of MSA’s.

Nonmetro areas. Counties outside MSA or CMSA boundaries. Throughout this publication, “rural” and “nonmetro” are used interchangeably to refer to people and places outside of MSA’s.

Regions

Bureau of Economic Analysis regions:

New England—Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and

Vermont.

Mideast—Delaware, District of Columbia, Maryland, New Jersey, New York, and

Pennsylvania.

Great Lakes—Illinois, Indiana, Michigan, Ohio, and Wisconsin.

Plains—Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota.

Southeast—Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North

Carolina, South Carolina, Tennessee, Virginia, and West Virginia.

Southwest—Arizona, New Mexico, Oklahoma, and Texas.

Rocky Mountain—Colorado, Idaho, Montana, Utah, and Wyoming.

Far West—Alaska, California, Hawaii, Nevada, Oregon, and Washington.
Rural Conditions and Trends, Vol. 10, No. 2 • 79

Appendix B: Definitions

Services-producing industries. Industries that produce services, rather than physical

goods: transportation, communications, and public utilities; finance, insurance, and real

estate; wholesale trade; retail trade; services.

Totally rural census tracts, as defined by ERS, are delineated based on 1990 commuting data and Census Bureau geographic definitions. In this analysis, “totally rural” means

that the tract does not contain any part of a town of 2,500 or more residents and the primary commuting pattern was to sites within the tract.

Urban and rural population are Bureau of the Census definitions. The urban population

basically comprises all persons living in incorporated or census-designated places of

2,500 or more inhabitants. The population not classified as urban constitutes the rural

population.

Urbanized area comprises one or more places and adjacent densely settled surrounding

territory that together have a minimum population of 50,000 persons.
Latest Trends in Nonfarm

Jobs and Earnings

Appendix C: Latest Trends in Nonfarm Jobs and Earnings

80 • Rural Conditions and Trends, Vol. 10, No. 2

With the release of 1997 data by the Bureau of Economic Analysis (BEA), we can update

the analysis of nonfarm jobs and earnings that was published in Vol. 9, No. 3 of RCaT.

When BEA releases a new year of data, it also revises the previous 2 years’ estimates.

The data shown here do not match data for the same years published in earlier issues of

RCaT because of the BEA revisions and because ERS has converted earlier years’ earnings to 1997 dollars.

Jobs

Nonfarm jobs increased by 2.0 percent during 1996-97, slightly slower than the 2.3 percent job growth in metro areas (app. table 1). That nonmetro rate of job growth is slower

than the 2.5 percent annual growth nonmetro areas averaged during 1991-97. During

1996-97, the agricultural services, construction, transportation and public utilities, retail

trade, finance, insurance and real estate, and services industries added jobs at a faster

than average rate in both nonmetro and metro areas. Federal Government employment

declined. Retail trade; agricultural services; and finance, insurance, and real estate added

jobs at slightly faster rates in nonmetro than in metro areas. Both metro and nonmetro job

growth was fastest in the Rocky Mountain and Southwest regions. Nonmetro job growth

was between 1.7 and 2.2 percent in other regions. Metro job growth rates exceeded nonmetro growth rates in each region.

Earnings per Nonfarm Job

Real earnings per nonfarm job increased during 1996-97, by 1.3 percent in nonmetro

areas and 2.1 percent in metro areas (app. table 2). Both of these increases exceeded

average earnings growth over the 1991-97 period. Nonmetro earnings grew in all sectors

except construction and transportation and public utilities. The fastest earnings growth in

nonmetro areas was in manufacturing and wholesale trade. In metro areas, jobs in mining; wholesale trade; finance, insurance, and real estate; and manufacturing had the

fastest earnings growth.

Real nonfarm earnings per job increased in all regions. Metro earnings growth exceeded

nonmetro earnings growth in all regions. Among nonmetro regions, earnings growth was

highest in the New England, Great Lakes, Plains, and Southeast regions, at 1.5 percent.

Among metro regions, earnings growth was highest in the New England, Southwest, and

Far West regions.

Trends in Earnings per Nonfarm Job, 1969-97

Average nonmetro earnings per job were $9,813 less than average metro earnings in

1997. Even after adjusting for inflation, this is the largest gap measured since the data

series began in 1969. The gap between metro and nonmetro earnings per job has

widened in most years since 1979 (app. table 3). In 1997, average nonmetro earnings

were 70.1 percent of metro earnings, down from 70.7 percent in 1996. The nonmetrometro earnings ratio peaked at 81 percent in 1979. [Fred Gale, 202-694-5349,

fgale@ers.usda.gov]
Rural Conditions and Trends, Vol. 10, No. 2 • 81

Appendix C: Latest Trends in Nonfarm Jobs and Earnings

	


	
 


Change from previous Annual average

year, 1996-97 change, 1991-97

Nonmetro Metro Nonmetro Metro Nonmetro Metro

Thousands Percent Percent

Total nonfarm jobs 25,875 127,581 2.0 2.3 2.5 2.1

By industry:

Agricultural services, forestry, fisheries,

and other1 508 1,465 4.8 4.3 4.9 5.2

Mining 344 489 .2 1.7 -3.0 -3.2

Construction 1,552 6,813 2.7 4.4 4.6 3.6

Manufacturing 4,433 14,983 .6 1.3 1.3 .1

Transportation and public utilities 1,153 6,398 3.0 3.4 2.6 2.4

Wholesale trade 867 6,311 1.9 2.5 1.5 1.4

Retail trade 4,804 21,552 2.1 1.9 3.3 2.5

Finance, insurance, and real estate 1,315 10,463 3.8 3.7 3.3 1.8

Services 6,526 41,702 2.9 3.6 3.6 3.6

Government and government enterprises 4,373 17,407 .9 .5 1.0 .3

Federal civilian 363 2,451 -.6 -2.3 -1.1 -1.7

Federal military 380 1,785 -1.5 -2.6 -3.1 -3.2

State and local 3,631 13,170 1.3 1.5 1.9 1.3

State 990 3,786 .3 .5 1.5 1.1

Local 2,642 9,383 1.7 1.9 2.0 1.4

By BEA region:

New England 1,160 7,175 1.8 2.4 1.9 1.7

Mideast 1,808 23,198 1.8 1.9 1.2 .9

Great Lakes 4,407 21,002 1.7 1.9 2.5 2.0

Plains 4,014 7,567 2.0 2.5 2.5 2.5

Southeast 8,576 27,852 1.8 2.8 2.4 3.0

Southwest 2,423 13,747 2.7 3.9 2.5 3.5

Rocky Mountain 1,545 3,823 2.9 3.7 4.5 4.4

Far West 1,942 23,218 2.2 2.9 2.6 1.6

1Other are employees of foreign embassies working in the United States.

2Government enterprises are government agencies that cover a substantial portion of their operating costs by selling goods and services to the public

and that maintain their own separate accounts—for example, the Postal Service.

Source: Calculated by ERS using data from the Bureau of Economic Analysis.
Appendix C: Latest Trends in Nonfarm Jobs and Earnings

82 • Rural Conditions and Trends, Vol. 10, No. 2

Appendix table 2—Earnings per nonfarm job, by industry and BEA region, 1997

Change from previous Annual average

year, 1996-97 change, 1991-97

Industry and region Nonmetro Metro Nonmetro Metro Nonmetro Metro

Dollars Percent Percent

Earnings per nonfarm job 22,986 32,799 1.3 2.1 0.5 1.1

By industry:

Agricultural services, forestry, fisheries, 12,265 16,390 0.1 1.6 -3.4 -1.6

other1

Mining 41,544 57,986 1.8 6.6 1.6 5.2

Construction 25,502 34,536 0.0 1.2 0.4 0.3

Manufacturing 32,207 47,607 2.7 2.9 1.2 1.6

Transportation and public utilities 33,999 45,544 -.4 1.5 -.2 1.0

Wholesale trade 28,862 44,458 2.8 3.2 1.4 1.6

Retail trade 13,764 17,311 1.4 1.8 -.1 .3

Finance, insurance, and real estate 17,030 37,180 .1 3.0 2.2 5.1

Services 18,958 29,974 1.7 2.2 1.1 1.0

Government and government enterprises 26,397 34,445 1.0 1.1 .8 .9

Federal civilian 41,309 48,664 1.5 2.0 1.9 2.0

Federal military 17,288 22,990 .9 1.0 .7 1.1

State and local 25,860 33,351 1.0 1.0 .6 .6

State 28,853 33,527 .8 1.3 .2 .4

Local 24,739 33,280 1.1 .9 .7 .7

By BEA region:

New England 24,489 35,551 1.5 2.7 .2 1.2

Mideast 24,471 37,706 .8 1.7 .2 1.3

Great Lakes 23,934 32,809 1.5 2.2 .8 1.3

Plains 21,326 30,533 1.5 2.2 .8 1.3

Southeast 22,981 29,103 1.5 1.9 .7 1.1

Southwest 21,684 31,482 1.0 2.7 .2 1.5

Rocky Mountain 21,890 29,074 1.1 2.3 .3 1.5

Far West 24,502 33,602 .4 2.6 -.2 .9

Note: Change from previous years is in real 1997 dollars. Previous years’ earnings were converted to 1997 dollars using chain-type personal consumption expenditures price index.

1Other are employees of foreign embassies working in the United States.

2Government enterprises are government agencies that cover a substantial portion of their operating costs by selling goods and services to the public

and that maintain their own separate accounts—for example, the Postal Service.

Source: Calculated by ERS using data from the Bureau of Economic Analysis.
Rural Conditions and Trends, Vol. 10, No. 2 • 83

Appendix C: Latest Trends in Nonfarm Jobs and Earnings

Appendix table 3—Real earnings per nonfarm job, 1969-97

Change from previous year

Metro-nonmetro Earnings

United States Nonmetro Metro earnings gap1 ratio2 Nonmetro Metro

1997 dollars Percent

1969 27,416 21,837 28,590 6,753 76.4 NA NA

1970 27,756 22,147 28,937 6,790 76.5 1.4 1.2

1971 28,238 22,597 29,441 6,843 76.8 2.0 1.7

1972 29,106 23,324 30,348 7,023 76.9 3.2 3.1

1973 29,277 23,680 30,473 6,793 77.7 1.5 0.4

1974 28,529 23,332 29,640 6,308 78.7 -1.5 -2.7

1975 28,449 23,543 29,503 5,960 79.8 .9 -.5

1976 29,296 24,512 30,340 5,828 80.8 4.1 2.8

1977 29,529 24,552 30,613 6,061 80.2 .2 .9

1978 29,764 24,877 30,821 5,944 80.7 1.3 .7

1979 29,516 24,731 30,541 5,810 81.0 -.6 -.9

1980 28,832 24,025 29,849 5,824 80.5 -2.9 -2.3

1981 28,595 23,682 29,628 5,946 79.9 -1.4 -.7

1982 28,488 23,309 29,571 6,262 78.8 -1.6 -.2

1983 28,744 23,393 29,855 6,462 78.4 .4 1.0

1984 29,301 23,854 30,418 6,564 78.4 2.0 1.9

1985 29,528 23,798 30,680 6,882 77.6 -.2 .9

1986 29,776 23,695 30,980 7,285 76.5 -.4 1.0

1987 29,998 23,409 31,299 7,889 74.8 -1.2 1.0

1988 30,183 23,366 31,518 8,152 74.1 -.2 .7

1989 29,875 23,066 31,210 8,144 73.9 -1.3 -1.0

1990 29,814 22,737 31,209 8,472 72.9 -1.4 0

1991 29,529 22,476 30,934 8,458 72.7 -1.1 -.9

1992 30,341 22,862 31,849 8,987 71.8 1.7 3.0

1993 30,338 22,925 31,842 8,918 72.0 .3 0

1994 30,255 22,907 31,761 8,855 72.1 -.1 -.3

1995 30,359 22,741 31,921 9,180 71.2 -.7 .5

1996 30,521 22,701 32,117 9,416 70.7 -.2 .6

1997 31,144 22,986 32,799 9,813 70.1 1.3 2.1

Note: Earnings were converted to 1997 dollars using chain-type personal consumption expenditures price index.

NA = Data for years prior to 1969 were not available to compute change.

1Earnings gap is the difference between metro and nonmetro earnings in 1997 dollars.

2Earnings ratio is nonmetro earnings as a percentage of metro earnings.

Source: Calculated by ERS using data from the Bureau of Economic Analysis.
Two Methods of

Measuring Farm-Linked

Employment

Appendix D: Two Methods of Measuring Farm-Linked Employment

84 • Rural Conditions and Trends, Vol. 10, No. 2

The Economic Research Service uses two methods to measure economywide employment related to agriculture: farm and farm-related employment (FFR) and the food and

fiber system (FFS). Both methods are widely respected, and, while they provide different

employment totals, both point to the continued importance of farm-related jobs in an era

when direct farm employment has declined to modest levels. Both methods also recognize the wide-ranging influence of farm-related activity in the U.S. economy beyond the

farm gate.

The two methods each have strengths and weaknesses. The FFS estimates are based on

a method that explicitly models the interrelationships between various sectors of the

economy. The FFS estimates have a close relationship to the U.S. Department of

Commerce’s National Income and Product Accounts. The FFR estimates have the advantage of rich geographic detail that can provide valuable information about the importance

of agriculture in various regions of the country.

Farm and Farm-Related Employment

The Census Bureau’s enhanced County Business Patterns data are combined with farm

employment data from the Bureau of Economic Analysis to estimate farm and farm-related employment (app. tables 4 and 5). Farm and farm-related employment includes jobs

not only in farm production, but also in its closely related industries—agricultural services,

forestry, and fishing; agricultural inputs; and processing and marketing of agricultural

goods—as well as industries peripherally related to farming—wholesale and retail trade of

agricultural products and indirect agribusiness. Farm and farm-related industries are identified as industries having 50 percent or more of their national workforce employed in providing goods and services necessary to satisfy the final demand for agricultural products.

An exception to this criterion is indirect agribusiness, in which percentages range

between 32 and 50 percent. [Alex Majchrowicz, 202-694-5355, alexm@ers.usda.gov]

Food and Fiber System

The Food and Fiber System (FFS) is the set of producers of goods and services required

to assemble, process, and distribute raw farm products to U.S. and foreign consumers.

FFS employment estimates (app. table 6) are developed using a national input-output

model that describes input use and factor payments for each sector of the economy. The

model is used to estimate the amount of employment in each sector needed to support

the final demands for agricultural products. Thus, this measure includes jobs in all sectors

of the economy, even those where the link to agriculture is weak. However, unlike the FFR

measure, the FFS estimates do not count all jobs in a particular sector; only the jobs

needed to support demand for agricultural products are counted. The FFS measure is

available at the State and national levels. [William Edmondson, 202-694-5374, wedmonds@ers.usda.gov]
Rural Conditions and Trends, Vol. 10, No. 2 • 85

Appendix D: Two Methods of Measuring Farm-Linked Employment

Appendix table 4—Share of total State employment by farm and farm-related industry, 1996

Total farm Total farm Farm production, Agricultural

and farm- and farm- agricultural processing Agricultural

related related services, forestry, Agricultural and wholesale and Indirect

State industries industries and fishing inputs marketing retail trade agribusiness

Jobs Percentage of total employment

United States 22,732,653 15.1 2.3 0.3 2.1 10.1 0.4

Alabama 426,442 18.6 2.8 .4 4.8 10.2 .5

Alaska 58,993 16.5 4.2 .1 2.2 10.0 —

Arizona 306,809 13.2 1.2 .2 .6 11.1 .1

Arkansas 282,053 20.5 5.0 .6 5.1 9.0 .8

California 2,481,102 14.4 2.1 .2 2.0 10.0 .3

Colorado 355,115 14.3 1.8 .2 1.3 10.7 .2

Connecticut 218,945 11.0 .7 .1 .7 9.2 .3

Delaware 60,096 13.4 1.1 .2 2.4 9.4 .3

Florida 1,107,739 14.6 1.6 .2 1.0 11.6 .2

Georgia 739,493 17.1 1.7 .3 3.9 10.7 .6

Hawaii 115,601 16.0 1.9 .1 1.3 12.7 —

Idaho 143,066 21.2 6.5 1.1 3.0 10.4 .4

Illinois 935,488 13.6 1.6 .6 1.6 9.2 .5

Indiana 519,146 15.4 2.5 .3 1.4 10.6 .5

Iowa 411,527 22.9 7.3 1.6 3.9 9.7 .5

Kansas 305,497 18.9 5.3 .8 2.7 9.7 .4

Kentucky 412,498 19.9 5.6 .3 3.0 10.5 .5

Louisiana 336,026 15.1 2.3 .4 1.6 10.4 .5

Maine 117,120 16.7 2.5 .1 3.1 10.6 .4

Maryland 340,413 12.2 1.1 .1 1.0 9.9 .2

Massachusetts 472,957 12.3 .5 .1 1.3 10.0 .4

Michigan 730,341 14.1 1.7 .2 .9 11.0 .3

Minnesota 482,814 15.7 3.7 .6 1.9 9.1 .4

Mississippi 262,395 19.2 4.6 .5 4.2 9.4 .5

Missouri 537,976 16.6 4.0 .5 2.2 9.5 .4

Montana 95,607 19.3 6.2 .6 .8 11.6 .2

Nebraska 245,857 22.1 6.7 1.7 4.0 9.5 .2

Nevada 105,717 10.8 .7 .1 .4 9.6 .1

New Hampshire 95,340 13.5 .9 .1 1.2 11.0 .4

New Jersey 527,408 11.9 .5 .1 1.6 9.2 .5

New Mexico 130,318 14.9 2.7 .1 .8 11.0 .3

New York 1,167,099 12.1 .8 .1 1.5 9.3 .3

North Carolina 848,279 19.1 2.3 .3 6.3 9.7 .6

North Dakota 97,140 23.2 9.5 1.6 2.1 10.0 —

Ohio 900,114 14.1 1.7 .2 1.1 10.6 .5

Oklahoma 310,319 17.2 5.1 .3 1.5 10.2 .2

Oregon 342,671 18.0 4.6 .3 1.6 11.2 .3

Pennsylvania 926,621 14.2 1.3 .2 2.3 10.0 .4

Rhode Island 71,169 13.2 .5 .1 1.8 10.4 .5

South Carolina 378,757 18.3 1.7 .2 5.0 10.8 .7

South Dakota 106,669 22.7 8.6 1.0 2.7 10.1 .3

Tennessee 553,057 17.4 3.2 .3 3.1 10.2 .5

Texas 1,602,979 15.0 2.8 .2 1.6 10.1 .3

Utah 159,012 13.3 1.7 .2 1.4 9.8 .3

Vermont 60,810 16.8 3.0 .2 1.7 11.6 .3

Virginia 561,827 14.4 1.9 .2 2.5 9.4 .4

Washington 523,318 16.4 3.4 .3 1.6 10.8 .4

West Virginia 121,284 14.8 2.9 .2 1.2 10.2 .2

Wisconsin 550,168 17.6 3.7 .6 2.4 10.1 .8

Wyoming 51,246 17.1 4.6 .4 .5 10.6 1.0

— = Less than 0.1 percent.

Source: Calculated by ERS using Department of Commerce data.
Appendix D: Two Methods of Measuring Farm-Linked Employment

86 • Rural Conditions and Trends, Vol. 10, No. 2

Appendix table 5—Share of total nonmetro employment by farm and farm-related industry, 1996

Total farm Total farm Farm production, Agricultural

and farm- and farm- agricultural processing Agricultural

related related services, forestry, Agricultural and wholesale and Indirect

State industries industries and fishing inputs marketing retail trade agribusiness

Jobs Percentage of total employment

United States 6,146,906 23.1 7.5 0.8 4.2 10.1 0.5

Alabama 178,567 28.3 5.9 .8 11.2 9.4 1.0

Alaska 39,343 21.0 7.2 .2 3.8 9.7 —

Arizona 44,814 16.7 2.3 .2 .3 13.9 .1

Arkansas 162,874 24.9 7.9 1.0 6.7 8.8 .6

California 100,182 21.7 8.1 .5 1.4 11.5 .2

Colorado 95,647 21.3 6.0 .5 1.8 12.9 .1

Connecticut 19,392 15.0 1.8 .1 2.2 10.1 .8

Delaware 18,014 27.8 3.9 .7 9.8 13.4 —

Florida 89,868 22.1 6.9 .6 1.7 12.4 .5

Georgia 280,333 24.5 4.5 .7 8.7 9.8 .8

Hawaii 39,121 22.5 5.7 .1 2.1 14.7 —

Idaho 105,815 24.6 8.7 1.4 3.3 10.8 .5

Illinois 204,119 22.0 7.7 1.6 2.4 9.7 .6

Indiana 164,905 19.3 5.8 .7 2.4 9.7 .8

Iowa 265,085 28.7 12.2 2.1 4.6 9.2 .6

Kansas 181,209 26.5 10.9 1.4 4.6 9.2 .4

Kentucky 225,477 24.9 9.8 .5 4.3 9.8 .5

Louisiana 89,024 21.2 7.5 1.0 3.2 8.8 .8

Maine 66,627 17.6 3.5 .1 2.9 10.6 .5

Maryland 39,103 20.2 4.3 .4 3.2 12.1 .2

Massachusetts 7,549 15.1 2.6 .1 1.1 10.8 .5

Michigan 142,954 18.8 5.1 .3 1.1 11.8 .5

Minnesota 214,225 26.2 10.4 1.5 4.1 9.7 .5

Mississippi 196,023 22.3 6.3 .7 5.7 9.0 .6

Missouri 224,699 25.3 11.0 .9 4.1 9.0 .3

Montana 75,465 20.3 7.6 .5 .7 11.3 .2

Nebraska 155,611 31.4 13.8 2.7 5.4 9.4 .1

Nevada 17,060 13.1 3.0 .4 .3 9.4 .1

New Hampshire 37,367 13.7 1.2 .1 1.1 10.9 .3

New Jersey NA

New Mexico 59,203 18.8 5.4 .3 .9 11.6 .6

New York 114,712 16.7 4.0 .3 1.5 10.6 .3

North Carolina 315,097 26.1 4.7 .5 10.6 9.7 .8

North Dakota 64,532 29.7 16.1 2.0 2.5 9.1 —

Ohio 201,865 19.4 5.2 .7 2.3 10.4 .9

Oklahoma 152,682 24.8 11.5 .7 2.8 9.7 .3

Oregon 118,327 23.8 8.8 .6 1.8 12.3 .4

Pennsylvania 154,557 18.7 3.7 .3 3.5 10.7 .5

Rhode Island 5,759 13.2 1.0 — .3 11.9 —

South Carolina 123,367 24.4 3.4 .3 9.5 10.4 .8

South Dakota 76,490 26.5 12.8 1.4 2.8 9.5 .1

Tennessee 203,150 24.0 7.7 .5 5.9 9.2 .7

Texas 375,302 27.1 13.5 .8 3.3 9.2 .3

Utah 45,384 19.4 5.6 .4 2.0 11.1 .4

Vermont 41,453 17.3 3.5 .3 1.5 11.9 .2

Virginia 168,651 24.0 6.1 .5 7.4 9.3 .8

Washington 119,918 26.0 10.5 .9 2.3 11.4 .9

West Virginia 66,768 15.6 4.3 .2 1.5 9.5 .2

Wisconsin 219,209 24.5 8.7 1.3 3.2 10.4 .8

Wyoming 40,008 19.1 5.9 .4 .7 10.7 1.4



— = Less than 0.1 percent.

NA = Not applicable. New Jersey has no nonmetro counties.

	

				

		
	

Rural Conditions and Trends, Vol. 10, No. 2 • 87

Appendix D: Two Methods of Measuring Farm-Linked Employment

	


	
		

Item 1991 1992 1993 1994 1995 1996 1997 1998

Millions of jobs

Total civilian labor force 126.3 128.1 129.2 131.1 132.3 133.9 136.3 137.7

Food and fiber system employment 23.5 23.1 23.6 24.3 24.7 24.5 24.6 24.8

Percent

Food and fiber system share of labor force 18.6 18.0 18.3 18.6 18.7 18.3 18.1 18.0

Food and fiber system employment by sector: Millions of jobs

Farm sector 2.0 1.9 1.8 1.9 2.0 2.0 1.9 1.8

Nonfarm sector 21.5 21.2 21.8 22.4 22.7 22.5 22.7 23.0

Food processing 1.6 1.5 1.5 1.5 1.5 1.4 1.4 1.4

Manufacturing 2.6 2.5 2.5 2.5 2.4 2.4 2.3 2.2

Transportation, trade and retailing 7.9 7.9 8.1 8.4 8.6 8.6 8.8 9.0

Eating and drinking places 6.1 6.0 6.3 6.5 6.6 6.6 6.7 6.8

All other 3.4 3.3 3.4 3.5 3.6 3.5 3.6 3.6

Billions of dollars

Total Gross Domestic Product (GDP) 5,986.2 6,318.9 6,642.3 7,054.3 7,400.5 7,813.2 8,300.8 8,759.9

Total food and fiber system GDP 881.8 924.8 971.4 1,077.1 1,140.8 1,216.5 1,323.3 1,367.2

Percent

Food and fiber system share of GDP 14.7 14.6 14.6 15.3 15.4 15.6 15.9 15.6

Food and fiber system GDP by sector: Billions of dollars

Farm sector 71.1 75.5 73.1 78.3 75.3 86.7 84.5 74.3

Nonfarm sector 810.7 849.3 898.3 998.8 1,065.5 1,129.8 1,238.8 1,292.9

Food processing 110.9 112.9 120.0 134.4 145.8 144.1 158.8 166.9

Manufacturing 131.6 135.4 143.0 164.5 180.6 193.2 209.6 215.2

Transportation, trade and retailing 261.0 278.0 294.7 328.7 347.8 376.9 419.1 441.4

Eating and drinking places 110.4 117.6 127.3 141.4 148.7 161.0 181.0 188.1

All other 196.7 205.5 213.3 229.9 242.6 254.5 270.3 281.3

Note: These improved estimates of Food and Fiber employment and GDP differ slightly from data tables published in previous issues of RCaT, due to 

extensive revisions to the National Income and Product Accounts data used in the ERS calculations.

Source: Calculated by ERS from supporting ERS economic models using data from the Bureau of Economic Analysis, Bureau of Labor Statistics, and

Bureau of the Census.
Economic Activity

Triggered by Agricultural

Trade

Appendix E: Economic Activity Triggered by Agricultural Trade

88 • Rural Conditions and Trends, Vol. 10, No. 2

Estimates of economic activity related to agricultural exports show that exports make an

important contribution to the farm sector and to the U.S economy as a whole (app. table

7). In 1998, the United States exported $51.8 billion of agricultural products, down from

$57.3 billion in 1997. Exports fell further to $48.3 billion during 1999. The decline in dollar

value of exports is due to falling prices for bulk commodities, large world supplies, weak

global demand as a result of economic crises in Asia, Russia, and Latin America, and a

strong U.S. dollar.

Agricultural exports play an important role in the economy, supporting jobs on farms, in

food processing, other manufacturing plants, and in the transportation and trade sectors.

Agricultural exports generated an estimated 808,000 jobs in 1998, of which 320,000 were

on farms. The impact of agricultural exports on the U.S. economy is far-reaching. Every

dollar of exports generated an additional $1.31 in economic activity in supporting sectors.

Imports of agricultural products were worth $37.1 billion in 1998, up from $36.3 billion in

1997. In 1999 they rose further to $37.9 billion. Since agricultural exports exceeded

imports, the United States had a positive trade balance in agricultural products of $14.7

billion in 1998. The positive agricultural trade balance shrank in 1998 and will fall again in

1999-2000 if exports decline as expected. About $9 billion of imports were such commodities as bananas, coffee, and tea that do not compete with U.S. products. The remaining $28.1 billion is comprised of imports, such as meat, dairy products, fruits, nuts, vegetables, sugar, and wines that compete with U.S. products.

Processed agricultural products have more extensive impacts on the U.S. economy than

exports of bulk unprocessed commodities. Nonbulk products account for most of the economic activity generated by agricultural exports. In 1998, they accounted for 478,000 of

the 808,000 jobs attributed to agricultural exports. Each dollar of nonbulk agricultural

exports (fresh fruits and vegetables and “value-added” processed products) generated an

additional $1.52 in supporting activity, compared with $0.92 for each dollar of bulk exports

(grains, oilseeds, and cotton). For the first time since calendar year 1991, bulk exports

have generated more U.S. jobs per $1 billion of exported commodity than processed. In

1998, $1 billion of bulk exports supported 16,900 U.S. jobs, compared with 14,800 for

nonbulk exports. Also for the first time in 1998, the U.S. imported more processed or highvalue foods than it exported, resulting in a negative trade balance in nonbulk commodities. Part of this shift in trading patterns is due to a redefinition and reclassification, by

ERS, of what is a “bulk” commodity. Up until 1997, estimates of economic activity related

to agricultural trade used U.S. Department of Commerce (Bureau of Economic Analysis

and Bureau of Census) classifications of commodities. In 1998, this analysis switched to a

classification scheme used in other ERS publications to maintain consistency across

agency products. [William Edmondson, 202-694-5374, wedmonds@ers.usda.gov]
Rural Conditions and Trends, Vol. 10, No. 2 • 89

Appendix E: Economic Activity Triggered by Agricultural Trade

	


			
	
	


1996 1997 1998

Item Total Total Total Bulk Other

Billion dollars

Economic activity generated by 

agricultural exports 139.9 130.8 119.7 37.5 81.5

Exports 60.4 57.3 51.8 19.5 32.3

Supporting activities 79.5 73.5 67.9 17.9 50.0

Farm 21.9 16.6 14.2 0.8 13.4

Food processing 6.7 6.2 5.7 .1 5.6

Other manufacturing 15.5 16.2 15.1 5.1 10.0

Trade and transportation 9.7 10.9 10.8 3.0 7.8

Other services 25.6 23.6 22.1 8.9 13.2

Percent

Farm share of total income from exports 34 29 27 39 19

Nonfarm share 73 77 79 96 73

Export multiplier (additional business activity

generated by $1 of exports) 1.32 1.28 1.31 .92 1.52

1,000 jobs

Employment generated by agricultural exports 859 871 808 330 478

Farm 292 321 320 182 138

Nonfarm 566 550 488 149 339

Food processing 86 90 78 0 78

Other manufacturing 70 76 65 20 45

Trade and transportation 196 175 155 59 96

Other services 214 209 190 70 120

Employment per billion dollars of 

agricultural exports 14.2 15.2 15.6 16.9 14.8

Percent

Share of farm workforce supported by 

agricultural exports 8 9 9 5 4

Billion dollars

Agricultural imports 33.6 36.3 37.1 4.3 32.8

Complementary 8.2 9.4 9.0 0.0 9.0

Competitive 25.4 26.9 28.1 4.3 23.8

Domestic equivalent of economic activity

generated by competitive imports 62.8 63.9 66.7 8.2 58.5

Agricultural trade balance 26.8 21.0 14.7 15.2 -.5

Net business surplus of agricultural trade 68.9 57.5 44.0 29.3 14.7

Source: Calculated by ERS from supporting ERS economic models using data from the Bureau of Economic Analysis, Bureau of Labor Statistics,

and Bureau of the Census.