Economic

Research

Service

United States 

Department of 

Agriculture

Farm Household Well-Being

Comparing Consumption- and 

Income-Based Measures

Economic

Research

Report

Number 91

February 2010

Carol Adaire Jones

Daniel Milkove

Laura Paszkiewicz
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Jones, Carol Adaire

Farm household well-being : comparing consumption- and income-based 

measures.

(Economic research report (United States. Dept. of Agriculture. 

Economic Research Service) ; no. 91)

 1. Cost and standard of living—United States. 2. Rural families—United 

States. 3. Farm income—United States. 

4. Consumption (Economics)—United States. I. Milkove, Daniel L. II. 

Paszkiewicz, Laura. 

III. United States. Dept. of Agriculture. Economic Research Service. IV. 

Title.

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A Report from the Economic Research Service

Abstract 

Household economic well-being can be gauged by the fi nancial resources (income/

wealth) available to the household or by the standard of living enjoyed by household 

members (consumption). Based on responses to USDA’s annual Agricultural Resource 

Management Survey (ARMS), a joint effort by the Economic Research Service (ERS) 

and the USDA National Agricultural Statistics Service, ERS has long published estimates 

of farm household income and wealth. This report presents, for the fi rst time, estimates of 

consumption-based measures of well-being for farm households based on new questions 

in ARMS. The consumption measure provides a different perspective from income or 

wealth on farm households’ well-being relative to that of all U.S. households. 

Keywords: household consumption, household income, household well-being measures, 

farm households, self-employed households, permanent income, permanent income 

hypothesis.

Acknowledgments 

This report benefi ted substantially from the comments of fi ve anonymous peer reviewers, 

as well as from Robert Gibbs, James MacDonald, Patrick Sullivan, and James Whittaker 

of the Economic Research Service, USDA. We also gratefully acknowledge Dale Simms 

for editorial assistance, Linda Beeler and Kathleen Kassel for support in creating the 

graphics, and Cynthia A. Ray for graphics, layout and cover design. 

Carol Adaire Jones, cjones@ers.usda.gov

Daniel Milkove, dmilkove@ers.usda.gov

Laura Paszkiewicz, paszkiewicz.laura@bls.gov

Farm Household Well-Being

Comparing Consumption- and 

Income-Based Measures

Economic

Research 

Report

Number 91

February 2010
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Farm Household Well-Being:Comparing Consumption- and Income-Based Measures / ERR-91

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Contents 

Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Well-Being of Farm Operator Households Versus All U.S. Households: 

Income and Wealth Measures, 1996-2006 . . . . . . . . . . . . . . . . . . . . . . . . 2

 Defi nitions and Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

 Income, Wealth, and Joint Income-Wealth Measures . . . . . . . . . . . . . . . 2

Creating Consumption Measures: Hypotheses, Defi nitions, 

and Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

 Consumption Behavior of Farm Households Versus 

 All U.S. Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

 Creating Consistent Expenditure and Consumption Measures 

 With ARMS and CE Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

 Data Analysis Samples and Descriptive Statistics . . . . . . . . . . . . . . . . . 10

Household Expenditure and Consumption Levels . . . . . . . . . . . . . . . . . 14

 Comparing Expenditure and Consumption Measures 

 for Farm Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

 Benchmarking Farm Household (ARMS) Estimates 

 With All U.S. Household (CE) Estimates . . . . . . . . . . . . . . . . . . . . . . . 16

The Relationship Between Household Consumption and Income . . . 17

 Propensity to Consume From Current Income: 

 Farm Versus All U.S. Household . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

 Propensity To Consume From Current Income: Households of Farms 

 With Sales of $100,000+ Versus Households of Very 

 Small Rural-Residence Farms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

 Consistency in Household Ranks in Income 

 and Consumption Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Relative Well-Being of Farm and All U.S. Households, 

as Indicated by Income and Consumption . . . . . . . . . . . . . . . . . . . . . . . 25

Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Appendix A: Data Sources and Analysis Samples . . . . . . . . . . . . . . . . 34

Appendix B: Constructing Consumption and Expenditure Measures 

in the Consumer Expenditure Survey (CE) and the Agricultural 

Resource Management Survey (ARMS) . . . . . . . . . . . . . . . . . . . . . . . . . 40

Recommended citation format for this publication:

Jones, Carol Adaire, Daniel Milkove, and Laura Paszkiewicz. Farm 

Household Well-Being:Comparing Consumption- and Income-Based 

Measures. Economic Research Report No. 91, U.S. Dept. of Agriculture, 

Economic Research Service. Feb. 2010.
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Economic Research Service / USDA

Summary

The traditional measures of a household’s economic well-being are money 

income and wealth, both of which indicate the fi nancial resources available to 

the household. An alternative measure, indicating the current standard of living 

enjoyed by a household, is the household’s consumption of goods and services. 

USDA’s Economic Research Service (ERS) has long published estimates of 

farm household income and wealth based on responses to USDA’s annual survey of farms, the Agricultural Resource Management Survey (ARMS), a joint 

effort by ERS and the USDA National Agricultural Statistics Service. This 

report presents, for the fi rst time, estimates of consumption for farm households, calculated using new survey questions in ARMS, and compares them to 

consumption estimates for all U.S. households, calculated from the Consumer 

Expenditure Survey collected by the Bureau of Labor Statistics. 

What Is the Issue?

Since 1998, median income for farm operator households has exceeded that 

of all U.S. households by 3 to 21 percent, and median farm household wealth 

has been 4-5 times that of all U.S. households. Farm household income fl uctuates from year to year more than the income of the typical U.S. household, 

due to variable farm yields and market prices. Because of their reliance on 

farm income, farm households tend to have lower income at the low end of 

the distribution and higher income at the high end of the distribution, compared with all U.S. households. Income measures suggest more farm households are disadvantaged: about 5-8 percent of farm households have negative 

household income each year, compared with around 0.1 percent of all U.S. 

households. And the offi cial U.S. poverty rate, based on comparing household income to the census poverty threshold, is 14.4 percent for persons in 

farm households compared to 12.3 percent for persons in all U.S. households. 

Because farm income is so variable, consumption is likely to be a more stable 

indicator of the household’s long-term standard of living than is its current 

income level. Households dependent on variable income sources are less 

likely than others with more stable incomes to adjust household consumption—which depends on longer term income expectations—in response to 

annual variations in household income—which are more likely to be temporary. When income is temporarily low, households with substantial wealth can 

draw down or borrow against their savings to maintain their standard of living; 

when income is temporarily high, they will be less inclined to expand discretionary purchases than similar households with more stable sources of income. 

What Did the Study Find?

We cannot track individual households over time to measure changes in consumption as income varies from year to year. Instead, we examined differences 

in spending behavior among all farm households during 2006. As expected, 

farm households consumed a larger share of current household income than all 

U.S. households when household income was low, but as household income 

increased, the increases in farm household consumption were smaller than for 

all U.S. households. To further test the role of variable household income on 

consumption, we compared two groups of farm households that vary in their 
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exposure to income variability from self-employment—those operating farms 

with annual sales of $100,000 or more (for whom, in the aggregate, farm income 

contributes more than half of household income) and those operating farms with 

annual sales of less than $10,000 and an operator with a primary occupation 

other than farming (for whom, in the aggregate, farm income contributes a small 

negative amount to household income). We found a similar pattern—on average, 

the $100,000+ farm households had higher consumption when incomes were 

low and lower consumption when incomes were high relative to households with 

similar levels of income operating very small rural-residence farms.

When households are ranked from lowest to highest based on current income 

levels, farm households have higher income per person than all U.S. households 

at all but the lowest level of household income. The net effect of predominantly 

higher income, but a lower tendency to increase consumption as income increases, 

is that the farm household distribution of consumption is very similar to that of all 

U.S. households. Farm households appear to have higher consumption at the low 

end of the distribution, and lower consumption at the upper end of the distribution, 

compared with all U.S. households. Analogously, the relative levels of disadvantage are reversed when we switch from an income-poverty rate to a consumptionpoverty rate, calculated by comparing household consumption to the census 

poverty threshold. The consumption poverty rate is lower for persons in farm 

households than for persons in all U.S. households. The divergence in income 

and consumption measures between farm and all U.S. households is even greater 

when we focus on households that operate farms with sales of $100,000 or more, 

which are more exposed to the income risks of self-employment. 

At the individual household level, there is not a close mapping between the 

income and consumption measures for farm households compared with U.S. 

households. Among households that rank in the bottom 20 percent for household income, farm households are far more likely to rank high in the consumption distribution than are all U.S. households, indicating farm households are 

more likely either to view their income as temporarily low, or to have suffi cient 

wealth to spend more than they earn. Analogously, among households that rank 

in the top 20 percent of the income distribution, farm households are far more 

likely to rank low in the consumption distribution than are U.S. households, 

indicating they view their current income as temporarily high. The greater 

divergence implies that income is a less effective proxy for consumption—an 

indicator of long-term standard of living—for farm households than for most 

other U.S. households. Consequently, consumption indicators are an important 

complement to income indicators for understanding farm household well-being. 

How Was the Study Conducted? 

The principal source for farm household data is USDA’s annual ARMS survey, 

which collects information on farm fi nances—including farm business income, 

household income, farm and nonfarm wealth, and living expenses—from a 

nationally representative sample of farm operator households. To explore farm 

household well-being in more detail, ERS in 2003 added to ARMS questions 

related to household consumption. The principal source for data on living 

expenses for all U.S. households is the Consumer Expenditure Survey collected 

by the Bureau of Labor Statistics. In addition, we use data from the Current 

Population Survey and Survey of Consumer Finances to provide income and 

wealth measures for all U.S. households over 1995-2006. 
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Introduction

How does farm household economic well-being compare to that of the 

typical U.S. household? The answer depends upon whether well-being is 

measured by available resources or by standard of living. Past research has 

relied primarily on measures of current-year money income and wealth—

indicators of resources available to the household. Many analysts agree that 

capturing standard of living by measuring goods and services consumed in 

the current year is an alternative measure of well-being with a number of 

advantages (Cutler and Katz, 1991; Hurd and Rohwedder, 2006; Johnson et 

al., 2005; Jorgenson, 1998; Meyer and Sullivan, 2003; and Rogers and Gray, 

1994). Households tend to smooth consumption over time, given temporary 

increases or decreases in income, in order to maintain their standard of living. Consequently, consumption better approximates lifetime well-being for 

a given household than current-year income. 

Theory and empirical evidence imply a more pronounced difference between 

money income and consumption for households less reliant on money 

income and/or where income is highly variable across years. The literature 

has studied two populations where income is a poor proxy for a consumption measure of well-being: low-income populations, who receive private 

and public transfers from outside of the household and who may have higher 

underreporting of income (Jorgenson, 1998; Meyer and Sullivan, 2003; 

Slesnick, 2001); and the elderly, who have relatively high levels of wealth 

but low current income (Hurd and Rohwedder, 2006). 

This report focuses on another population for which income may be a 

weak proxy for standard of living: farm households which, like other selfemployed households, typically have more variable income and higher 

wealth than the average U.S. household. 
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Well-Being of Farm Operator Households 

Versus All U.S. Households: Income and 

Wealth Measures, 1996-2006

First, we defi ne who is a farmer and identify the data sources for our reporting. We then report on patterns of well-being using traditional measures: 

income, wealth, and joint income-wealth.

Defi nitions and Data Sources

To identify our target population—households of principal operators of 

family farms—we start with USDA’s defi nition of a farm (“any place from 

which $1,000 or more of agricultural products were produced and sold, or 

normally would have been sold, during the year”). Because we are interested 

in the households of the principal farm operators, we restrict our analysis to 

“family farms,” those in which majority ownership of the farm business is 

held by the operator and relatives of the operator. Most farms (96 percent in 

2006) are family owned and operated. For family farms, we identify the principal operator of the operation, and collect information for that individual’s 

household. About 10 percent of family farms have other operators who live 

in separate households; these households are not included in the population.1

In this section, we use the full family-farm sample from USDA’s 

Agricultural Resource Management Survey (ARMS), a joint effort by ERS 

and the USDA National Agricultural Statistics Service, to describe the 

demographics and economics of farm households. (See Appendix A for 

more information about data sources.) ARMS is a major source of information for reporting offi cial USDA statistics on farm income and farm household income and wealth.2 The calculation of household income in ARMS 

includes: a detailed calculation of farm income, based on farm output, 

revenue, expenses, and depreciation; the allocation of farm income among 

stakeholders, including the principal operator, and the nonfarm income of the 

principal operator’s household from earned and unearned sources.3 ARMS 

also reports farm and nonfarm household wealth and household expenditure 

data. For all U.S. households, we rely on the Current Population Survey for 

income data and the triennial Survey of Consumer Finance for wealth data. 

Tables 1 and 2 report income- and wealth-based measures of household wellbeing for principal farm operator and all U.S. households for 1996-2006. 

Income, Wealth, and Joint Income-Wealth Measures 

Following Slesnick (2001), we start with the three standard well-being measures, all based on household money income for a given year: the level of 

income at the midpoint of the population (median household income); the 

dispersion, or inequality, of income across households (the Gini coeffi cient4); 

and the share of households below a minimum threshold of income adequacy 

(the Census poverty rate). 

In the 1930s, the per capita income for farm household members was about 

half that of nonfarm households (USDA, 1984).5 In the 1970s, median farm 

household income approached that of all U.S. households—in some years, 

 1For multiple-operator farms, a 

principal operator is identifi ed during the annual process of collecting 

economic information from farm 

businesses. About 40 percent of farms 

have more than one operator; however, 

for three-quarters of the farms with 

multiple operators, the farm is operated 

by a husband-wife team, so that both 

operators are part of the same “principal operator” household on which we 

focus.

2See ERS Briefi ng Rooms on Farm 

Income and Costs (http://www.ers.

usda.gov/Briefi ng/FarmIncome/), Farm 

Household Economics and Well-Being 

(http://www.ers.usda.gov/Briefi ng/

WellBeing/), and ARMS (http://www.

ers.usda.gov/Briefi ng/ARMS/) for more 

information. 

3Other net self-employment income 

is elicited directly from the respondent, 

as in the Current Population Survey. 

Though the CPS survey manual indicates that self-employment income is 

to be reported net of depreciation, this 

guidance does not appear on the survey 

form in CPS. Checks comparing farm 

self-employment income between CPS 

and ARMS suggest that the typical respondent does not deduct depreciation, 

resulting in lower estimates of farm 

self-employment income in ARMS than 

in CPS.

 4The Gini coeffi cient is a ratio with 

values between 0 and 1: 0 corresponds 

to perfect equality (everyone having 

exactly the same income) and 1 corresponds to perfect inequality (where 

one person has all the income, while 

everyone else has zero income). Consequently, a low Gini coeffi cient indicates 

a more equal income or wealth distribution, while a high Gini coeffi cient 

indicates a more unequal distribution.

 5Data for calculating farm household income are not available from 

ARMS or its precursor prior to 1986. 

In order to make historical comparisons 

between disposable personal incomes 

of farm and nonfarm residents, we use 

an alternate series for 1934-1983. For 

more information, see http://www.ers.

usda.gov/Briefi ng/WellBeing/glossary.

htm#disposable.
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Table 1

Income measures of well-being for farm operator and all U.S. households, 1996-2006 (in 2006 dollars)

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Farm primary operator households: 

Households (1,000) 1,717 2,012 1,872 2,148 2,121 2,094 2,115 2,085 2,061 2,034 2,022

Total household income ($)

Median 35,149 42,588 49,635 52,983 50,954 51,026 52,105 52,283 57,268 55,822 56,022

Standard error 1,667 1,915 2,191 2,074 1,633 1,781 1,159 1,938 2,395 1,587 1,043

10th percentile 5,745 3,006 7,702 9,860 8,809 7,715 7,482 8,375 10,865 10,438 9,859

20th percentile 15,291 15,547 19,103 21,030 19,814 21,677 21,172 20,760 23,218 23,165 22,400

80th percentile 83,668 87,897 96,695 100,791 97,649 98,508 102,876 99,179 114,872 114,105 108,713

90th percentile 133,148 130,028 153,214 153,688 151,321 140,884 151,410 145,950 181,948 178,559 167,570

Ratio

80:20 5.5 5.7 5.1 4.8 4.9 4.5 4.9 4.8 4.9 4.9 4.8

90:10 23.2 43.3 19.9 15.6 17.2 18.3 20.2 17.4 16.7 17.1 16.0

Index

Gini 0.647 0.624 0.590 0.582 0.587 0.591 0.589 0.587 0.578 0.583 0.582

Standard error 0.0188 0.0136 0.0124 0.0130 0.0102 0.0134 0.0162 0.0093 0.0140 0.0052 0.0092

Percent

Poverty rate per person 20.4 na na 14.3 na na 16.0 15.1 13.3 na 14.4

Negative household 

income

6.0 7.5 5.8 5.2 6.0 6.5 6.4 5.8 5.0 5.4 5.9

Farm income share 13.3 11.8 10.2 9.6 4.6 8.3 5.3 11.5 17.5 18.1 11.4

Farm + other selfemployment income share26 24 22 27 na na 18 23 30 na 25

All U.S. households:

Households (1,000) 101,018 102,528 103,874 106,434 108,209 109,294 111,278 112,000 113,343 114,384 116,011

Total household income ($)

Median 45,416 46,350 48,034 49,244 49,163 48,091 47,530 47,488 47,323 47,845 48,201

Standard error 229 214 284 230 155 147 156 206 209 160 207

10th percentile 11,401 11,542 11,982 12,519 12,390 12,170 11,902 11,550 11,641 11,658 12,000

20th percentile 18,897 19,289 19,908 20,735 20,981 20,465 20,079 19,715 19,732 19,807 20,035

80th percentile 87,032 89,556 92,647 95,875 95,733 95,094 94,160 95,229 93,934 94,712 97,032

90th percentile 117,787 122,325 125,135 130,417 131,132 129,405 127,890 129,578 129,014 130,224 133,000

Ratio

80:20 4.6 4.6 4.7 4.6 4.6 4.7 4.7 4.8 4.8 4.8 4.8

90:10 10.3 10.6 10.4 10.4 10.6 10.6 10.8 11.2 11.1 11.2 11.1

Index

Gini 0.455 0.459 0.456 0.458 0.462 0.466 0.462 0.464 0.466 0.469 0.470

Standard error 0.0043 0.0043 0.0042 0.0041 0.0030 0.0030 0.0029 0.0028 0.0029 0.0028 0.0028

Percent

Poverty rate per person 13.7 13.3 12.7 11.9 11.3 11.7 12.1 12.5 12.7 12.6 12.3

Negative household 

income

0.011 0.116 0.135 0.130 0.097 0.124 0.129 0.131 0.129 0.104 0.058

Self-employment income 

share

4.9 5.4 5.4 5.2 5.1 4.5 4.7 4.9 4.7 5.2 5.3

Income is in 2006 CPI-U-RS adjusted dollars, for households current as of March the following year. na = Estimate does not comply with ERS 

disclosure limitation practices, is not available, or is not applicable. Sources: USDA, Economic Research Service using Agricultural Resource 

Management Survey, 1996-2006 (all survey versions) for farm households, and using Current Population Survey Report P60-223, U.S. Census 

Bureau, 2007, for all U.S. households (median and mean income, Table A-1; Gini of income, Table A-3.)
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it was above the median for all U.S. households, and in other years, it was 

below it. Since 1998, median income for farm operator households has 

exceeded median income of all U.S. households by 3 to 21 percent (table 1). 

Income levels are more disparate among farm households, as refl ected 

in consistently higher Gini coeffi cients, than among all U.S. households. 

However, the Gini coeffi cients are converging: the Gini for all U.S. households rose from 0.455 in 1996 to 0.470 in 2006, implying widening income 

inequality, whereas the Gini for farm households fell from 0.647 to 0.582. 

Two other measures of dispersion, the ratio of income at the 80th and 20th 

percentiles and at the 90th and 10th percentiles, focus specifi cally on the 

distance between the upper and lower tails of the distribution. For the 80:20 

ratio, farm and all U.S. households do converge in 2006 to the same value; 

for the 90:10 ratio, the gap is shrinking (table 1). Further, farm households 

have consistently higher income-based poverty rates (14.4 percent for farm 

households versus 12.3 percent for U.S. households in 2006) and larger 

shares with negative household income each year (5-8 percent of farm houseTable 2

Wealth measures of well-being for farm operator and all U.S. households, 1995-2006 (in 2006 dollars)

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Farm primary operator households: 

Median ($) 283,006 na 337,133 435,098 375,174 386,321 376,474 455,853 487,715 517,467 548,193

Standard error 25,215 11,449 7,971 15,383 12,400 13,077 17,072 20,348 13,122 11,159

10th percentile 74,092 na 88,940 129,346 102,187 92,951 97,571 118,008 148,731 142,269 167,549

20th percentile 149,326 na 174,956 237,968 193,724 191,933 198,548 241,037 266,800 264,448 307,932

80th percentile 590,570 na 647,789 799,004 712,052 730,290 716,503 868,634 907,271 971,913 1,020,621

90th percentile 1,116,774 na 1,277,634 1,471,502 1,254,751 1,303,669 1,303,156 1,576,273 1,616,857 1,732,255 1,775,872

Ratio

75:25 4.0 3.7 3.4 3.7 3.8 3.6 3.6 3.4 3.7 3.3

90:10 15.1 14.4 11.4 12.3 14.0 13.4 13.4 10.9 12.2 10.6

Index

Gini 0.549 na 0.559 0.505 0.521 0.565 0.528 0.532 0.517 0.538 0.529

Standard error 0.0097 0.0101 0.0070 0.0138 0.0339 0.0094 0.0133 0.0129 0.0089 0.0052

All U.S. households:

Median ($)** 75,573 79,985 88,809 97,882 99,376

Standard error 2,562 3,416 3,522 4,590

10th percentile 107 53 107 213

25th percentile 13,129 12,275 14,517 14,197

75th percentile 211,348 258,527 322,038 350,645

90th percentile 500,616 611,520 834,929 887,660

Ratio

75:25 16.1 21.1 22.2 24.7

90:10 4,690 11,458 7,822 4,158

Index

Gini 0.784 0.794 0.803 0.805

Standard error 0.0043 0.0051 0.0041 0.0049

na = Estimate does not comply with ERS disclosure limitation practices, is not available, or is not applicable.

** 1996 all U.S. wealth median estimate is interpolated from 1995 and 1998 estimates.

Sources: USDA, Economic Research Service using Agricultural Resource Management Survey, 1996-2006 (all survey versions), 

for farm households, and Survey of Consumer Finances (Kennickell, Jan 2006), for all U.S. households.
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holds, compared with 0.1 percent for all U.S. households across the period) 

(table 1). 

The greater income variability among farm households from one year to 

another can be attributed to the greater share of self-employment income 

among farm households. Self-employment income is more likely to be negative in a given year due to the variability of business results, as well as to 

variability in how much production is allocated to inventory rather than sales 

in a given year and in depreciation expenses from recent capital expenditures. 

For all U.S. households, the share of income from self-employment averages 

about 5 percent over 1996-2006 (table 1). For farm households, the share of 

income from self-employment ranges from 18 to 30 percent, with the farm 

income share ranging from 5 to 18 percent. (Many of the other self-employment activities of farm households are related to farming, though not part of 

the farm business.) 

The economic strategies of farm households are diverse. The average shares 

of household income from farming increase with the farm’s sales class. Many 

households in the upper and lower ends of the income distribution are from 

the small set of households operating farms with annual sales over $100,000. 

Though these farms accounted for 16 percent of all farms in 2006, they produced 89 percent of total farm sales. 

Farm households clearly dominate all U.S. households in wealth-based measures of well-being. In 2004 (the most recent year for which wealth information is available for all U.S. households), median wealth of farm households 

was about fi ve times the estimated median wealth of all U.S. households 

(table 2.) A large share of household wealth in the farm sector is in farmland, 

which increased substantially in value relative to other assets over 1995-2006. 

In contrast to all U.S. households, where wealth is very concentrated at the 

top end of the distribution, wealth is more evenly distributed among farm 

households: the Gini coeffi cients in 2004 were 0.517 for farm households and 

0.805 for all U.S. households. 

Recognizing the variability of income across years and the importance of 

wealth to sustain consumption amid temporary declines in income, Mishra 

et al. (2002) introduced a four-quadrant well-being indicator. It separates 

households into low- and high-income and low- and high-wealth, using the 

U.S. household medians for money income and wealth as the dividing lines. 

The combination of low income and low wealth is interpreted as an indication of “economic disadvantage.” Using 2000 data, 6 percent of the U.S. 

farm population was in the low-income/low-wealth category. As the wellbeing of farm households (both income and wealth) improved over the next 6 

years, the share of disadvantaged households fell to 3 percent in 2006. 
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Figure 1 compares the four-quadrant distributions of farm and all U.S. households for 2004, the last year for which household wealth data are available 

for all U.S. households. The shares with low income are similar (43 percent 

of farm households, 50 percent of all U.S. households). The striking difference is in wealth, where 96 percent of farm households had high wealth 

(compared to 50 percent of all U.S. households.)6 For all U.S. households, 

income and wealth are positively correlated: more than two-thirds of the 

low-income group had low wealth and nearly two-thirds of the high-income 

group had high wealth. The pattern is signifi cantly different for low-income 

farm households: virtually all of them had high wealth, suggesting that for 

many, their current-year income is temporarily low. 

6The 96 percent of farm households 

with high wealth are split into two 

groups, with 56 percent having income 

higher than the U.S. median and 40 

percent having income lower than the 

U.S. median. On average, the lowincome/high-wealth group tended to 

incur farm losses during the year, and 

some portion of their off-farm income 

served to offset these losses.

Source: USDA, Economic Research Service using Agricultural Resource Management 

Survey, 2004; Current Population Survey, 2004, Bureau of Labor Statistics, U.S. Department of Labor; Survey of Consumer Finances, 2004, Federal Reserve Board.

Figure 1

Joint household income and wealth distribution, for farm and all 

U.S. households, relative to U.S. household medians, 2004

Percent

Lower incomelower wealthHigher incomelower wealthLower incomehigher wealthHigher incomehigher wealth

0

10

20

30

40

50

60

Farm households All U.S. households

“Lower” and “higher” income and wealth are defined relative to the U.S. household medians: 

in 2004 dollars, $45,817 for income and $91,700 for wealth.
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Creating Consumption Measures: 

Hypotheses, Defi nitions, and Data

In this chapter, we explore why patterns of consumption behavior may differ for farm households relative to all U.S. households. Then, we outline our 

approach for constructing consistent consumption measures in the Consumer 

Expenditure (CE) and ARMS survey data. 

Consumption Behavior of Farm Households 

Versus All U.S. Households

In its simplest form, the permanent income hypothesis (PIH) of consumption and savings behavior posits that the choices made by consumers are 

determined not by current income but by longer term income expectations.7

The concept of permanent income is based on the lifetime earning capacity 

of household real wealth, which includes both physical (real property and 

fi nancial) and human (education and experience) assets. Measured current 

income typically contains a permanent component, which is anticipated and 

planned, and a transitory element, which may be unexpected. The concept of 

consumption differentiates outlays that result in current enjoyment of goods 

and services from those that refl ect (at least in part) savings for future enjoyment, including the purchase of durable goods such as housing or vehicles, 

and fi nancial assets such as retirement accounts and insurance. 

A major implication of the permanent income hypothesis is that—in the 

face of current income variability around permanent income—consumers 

will seek to allocate resources in order to smooth the marginal utility of consumption relative to current income. Household groups with higher shares of 

transitory income, such as the households of farm operators and other selfemployed individuals, are predicted to have lower propensities to consume 

from current income. Indeed, Friedman (1957) cited this explanation for his 

fi nding that the elasticity of consumption with respect to current income was 

lower for farmers than for nonfarmers. 

Whereas 15 years ago the literature interpreted the PIH theory as badly dated, 

more recent re-formulation of the theory, combined with improved data 

availability, has reinvigorated this line of research.8 In recent years, a number of empirical studies have explored predictions from various versions of 

the permanent income hypothesis. DeJuan and Seater (2006), analyzing CE 

data, found that the income-elasticity of consumption is lower for households 

with greater transitory income. Whittaker and Effl and (2009), using 2003-05 

ARMS data, found that increases in relatively stable nonfarm income have a 

greater impact on farm household spending than do increases in farm production income, which can vary from year to year because of weather, crop failures, animal losses, and/or commodity price fl uctuations. 

The theory predicts that the level of income variability is an important driver 

of the extent of consumption-smoothing behavior. Mishra and Sandretto 

(2002) document the substantial intertemporal variability of farm household 

income over the past seven decades, and suggest that variability has not 

declined during this period. 

7The permanent income hypothesis 

is a theory of consumption attributed to 

Milton Friedman (1957).

8A prominent researcher suggested 

Friedman was more “prescient than 

primitive” in his 2001 review of the 

literature on theories of consumption 

(Carroll, 2001).
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Ideally, we would conduct the test of income variability and consumption with panel data. However, lacking panel data capturing the same farm 

households across multiple years, we test for consumption smoothing across 

income levels in our cross-sectional data for 2006. The underlying assumption is that greater income dispersion at a point in time is associated with 

greater intertemporal variability as well, so that current incomes at the 

low and high ends of the distribution are less likely to be representative of 

long-term, or “permanent,” income for farm households than for all U.S. 

households. For example, the operators of large farms, who have the highest 

average household income but whose farm income is most variable from year 

to year, are disproportionately represented at both the top and bottom of the 

income distribution. 

We compare how patterns of consumption-smoothing relative to income 

levels differ between household groups with more and less income variability. We fi rst compare farm households and all U.S. households. In addition, among farm households, we compare households operating farms with 

annual sales greater than $100,000 and households operating very small 

rural-residence farms (with sales less than $10,000 and a principal operator 

whose primary occupation is not farming).

Creating Consistent Expenditure and Consumption 

Measures With ARMS and CE Data 

In our analysis, consumption refers to own-household consumption during 

the current year. The household consumption measure of standard of living— 

the value of service fl ows received by the household in the current period—is 

closely related to living expenses (current expenditures), but differs in key 

ways, requiring three (sometimes impractical) adjustments: 

• The fi rst adjustment is to separate the investment or savings component 

of expenditures from current consumption. For consumer durables such 

as housing and vehicles, this can be done by replacing current outlays 

with the estimated annual fl ow of consumer services. Also, expenditures 

that represent savings—such as on disability/life insurance and retirement 

plans—are excluded from the consumption measure. Some argue that 

education and health expenditures are more appropriately interpreted as 

investments and should be excluded, but we do not attempt to do so here. 

• A second adjustment is to separate out net expenditures on other 

households, such as alimony and child support, gifts, and charitable 

contributions. 

• A third adjustment is to capture goods and services consumed without 

private economic transactions (and therefore without household fi nancial 

expenditures)—including leisure, public goods, and in-kind transfers 

(such as Medicare direct payments to health providers). 

The categories in the current ARMS living expense (or household expenditure) questions were modeled after the major categories used in the 

Consumer Expenditure (CE) Survey, the most comprehensive source of 

expenditure data for U.S. households. Since the ARMS questions were not 

originally designed to calculate consumption, we adjusted the categories of 

expenditures in 2006 to isolate pure consumption items. (See Appendix B 
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for more details of the mapping between CE and ARMS categories and other 

aspects of the construction of the consumption measures in the two survey 

data sets.) 

The CE survey collects data on over 200 expenditure items, whereas the 

ARMS survey now collects data on 10 items. Survey research indicates that 

the estimated value of an aggregate that depends on summing many components varies with the number of components that are measured. The reasoning is that each component is composed of subcomponents, and respondents 

will not remember all the subcomponents when reporting the value of the 

component (Weinberg et al., 1999). Thus, increasing the number of components that are queried will tend to increase the aggregate of the components.9 

By this logic, the ARMS could have a tendency to understate total expenditures. Consequently, we recognize that the ARMS data may be subject to 

a downward bias, particularly for the aggregated category “all else.” In its 

offi cial reporting of CE data, BLS does not report a consumption measure. 

However, a number of researchers have calculated a consumption measure 

from CE data (Johnson et al., 2005; Meyer and Sullivan, 2003, 2009). 

We make parallel adjustments to expenditure data in CE and ARMS in 

order to calculate consistent consumption measures from the two surveys. 

The fi rst set of adjustments relates to separating out savings components of 

expenditures. For the two durable goods, housing and vehicles, we replace 

expenditures with the value of estimated service fl ows for shelter and vehicle 

services. We retain education expenditures (in “all else”) and health expenditures (as a separate item), but drop expenditures on personal insurance and 

retirement plans in the analysis samples to calculate consumption for both 

survey samples. 

Three categories are treated as disposable goods and services (i.e., their 

expenditures are included directly in the consumption measure)—food, 

health care, and all else. And in order to drop contributions to other households from our measure of consumption, we exclude the ARMS expenditure 

category “charitable contributions and contributions to other households” and 

the CE category “cash contributions.”10

CE and ARMS provide limited opportunities to capture goods and services 

consumed without private economic transactions—our consumption measure does not include leisure, public goods, or barter. One in-kind transfer 

captured in the food category for both data sets—at least in concept—is food 

purchased with food stamps.11 In addition, ARMS allows us to include for 

farm households “in-kind farm production for household consumption.” 

Calculating Per-Person Equivalence Measures

Household consumption is subject to economies of scale, where two (or 

more) people can attain a given standard of living more cheaply in one 

household than in separate households. To achieve comparability in the perperson standard of living across households of different sizes, we adjust the 

household income and consumption measures with an equivalence scale. 

Following Johnson et al. (2005), we use the single-parameter, constantelasticity equivalence scale, an approach used more frequently in 

9The ARMS question eliciting the 

“all else” measure specifi cally mentions 

all of the major categories of consumption in the CE survey included in the 

“all else” category, including entertainment, apparel, household furnishings 

and equipment, education, child (or 

adult) care, personal care and services; 

the only major categories not mentioned are alcohol, tobacco products, 

and reading, which represented 1.1 

percent, 0.7 percent, and 0.3 percent of 

U.S. household consumption in 2006.

 10However, we do not refl ect in our 

measure the fact that some purchases 

may be given to other households as 

gifts, or that households may receive 

in-kind gifts.

11Meyer, Mok, and Sullivan (2009) 

document the under-reporting of transfers in the major U.S. economic data 

sets, including CE.
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international comparisons of inequality (Johnson and Shipp, 1999). This particular scale is given by the square root of family size and indicates that the 

resources for a two-person household must be 41 percent (and not 100 percent) more than those of a single-person household for the two households to 

have an equivalent standard of living. 

Data Analysis Samples and Descriptive Statistics

Table 3 reports descriptive statistics for the fi ve data samples employed in 

our analysis. For the two main populations, principal farm operator households and all U.S. households, the primary samples are derived from the 

2006 ARMS and CE, respectively. We create three additional sub-samples to 

support within-survey comparisons. Within CE, we pool observations over 

3 years (2005-2007) to create a sample of households that report receiving 

farm income. Within ARMS, we create two farm household subsamples that 

vary greatly in their exposure to income variability from self-employment—

households operating farms with $100,000 or more in sales and households 

operating farms with $10,000 or less in sales, in which the principal operator has a primary occupation other than farming (very small rural-residence 

farms).

Primary Analysis Samples: All Farm Households (ARMS) 

and All U.S. Households (CE) 

Detailed expenditure data are only requested on one of the fi ve ARMS questionnaires; consequently, the sample used to analyze consumption data is a 

subset (N = 4,683) of the full 5-questionnaire sample (N = 20,342) for 2006. 

For the consumption analysis, we use CE data (which are collected on a 

quarterly basis) from 2006. The distributions of demographic and economic 

variables in the analysis samples used in this section are very similar to those 

in the larger samples used in the income and wealth analysis (CPS for U.S. 

households, and the ARMS full sample for farm households), though we 

highlight below some differences in the income distributions. (See Appendix 

A for more details on the data sources and the benchmarking of the analysis 

samples.) 

For the CE sample of all U.S. households and the ARMS sample of all farm 

households, mean values of various demographic and economic characteristics expected to affect the consumption measures are reported in columns 1 

and 2 of table 3. Average household size is essentially the same for households of principal farm operators and all U.S. households (2.7 versus 2.5 

persons). Not surprisingly, the average age of principal farm operators (57) 

is greater than for the reference person in CE households (49); however, the 

average number of farm household members over age 65 is only slightly 

greater (0.5 versus 0.3 person). Farm operators are much more likely to live 

in a nonmetro area than all U.S. households (60.6 percent versus 14.6 percent), but have comparable rates of college and post-college education. 

Turning to income measures, we observe the familiar pattern of higher 

household income for farm operator households relative to all U.S. households. However, both analysis samples appear to understate income relative 

to the larger samples analyzed in table 1. The income distribution for U.S. 

households is lower in the CE data than the CPS, throughout the distribution 
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Table 3

Comparison of characteristics for CE and ARMS samples, 2006

Source CE ARMS CE ARMS ARMS

Years 2006 2006 2005-2007 2006 2006

All U.S. 

consumer 

units

All U.S. principal 

farm operator 

households

Farm 

consumer 

units 

Households of 

farms with sales of 

$100,000 or more

Households of 

very small rural 

residence farms 

Number of households or consumer units (1,000) 118,843 1,463 1,744 231 503

Sample size 35,832 4,683 1,235 2,538 574

Demographics

Age of reference person 49 57 55 52 51

Average number of persons in consumer unit:

Total 2.5 2.7 2.5 3.0 2.9

Children under 18 0.6 0.6 0.5 0.8 0.8

Persons 65 and over 0.3 0.5 0.5 0.2 0.1

Education of reference person:*

Highest degree completed was: Percent

Less than high school 14.9 11.7 13.0 7.3 7.8

High school 26.2 39.2 21.2 39.2 34.6

Some college 21.1 23.1 20.8 27.0 24.4

Associates degree 9.7 na 9.8 na na

College grad (bachelor's) and beyond 28.0 26.0 35.1 26.5 33.3

Nonmetro residence 14.6 60.6 51.9 69.0 54.8

Economics

Dollars

Income before taxes - mean 60,533 75,080 82,879 108,610 81,930

- median 44,616 55,330 63,132 72,476 67,662

Wages & salaries - mean 48,119 40,222 51,367 23,816 67,179

Self-employment income - mean 3,607 17,024 15,879 72,682 6,502

Net nonfarm business income - mean 3,483 11,294 6,245 9,589 14,748

Net farm income - mean 124 5,730 9,634 63,093 -8,245

Percent

Wage income share 79.5 53.6 62.0 21.9 82.0

Self-employment income share 6.0 22.7 19.2 66.9 7.9

Negative household income 0.1 5.9 1.5 13.7 na

Dollars

Net worth - mean na 955,708 na 1,636,325 659,501

- median na 578,650 na 1,140,075 407,734

Percent

Household owns residence 67.0 20.4 92.3 22.6 20.6

Farm owns residence na 77.1 na 73.8 77.0

Dollars

Value of residence - household owned 183,212 192,914 303,066 211,664 211,411

Value of residence - farm owned na 138,089 na 145,342 140,550

Consumer units from the Consumer Expenditure survey are selected for the farm sample if they reported any farm income (positive or negative). 

*Asked of reference person in the Consumer Expenditure survey, primary operator in Agricultural Resource Management Survey. 

na = indicates data are not available or estimate does not comply with disclosure limitation practices.

Very small rural-residence farms: farms where the principal operator indicates his primary occupation is other than farming, and whose farm has 

sales of $10,000 or less this year.

Sources: USDA, Economic Research Service using Consumer Expenditure Survey and Agricultural Resource Management Survey, 

2006 analysis sample.
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(Appendix table A2). The share of total household income from (farm and 

nonfarm) self-employment received by all households is much higher for 

farm households (22.7 percent) than for all U.S. households (6.0 percent), as 

expected. 

The CE collects limited information on wealth, but it does report whether the 

residence is rented or owned by the household and the market value of an 

owned home. The fi rst critical difference regarding home ownership between 

the two populations is that three-quarters of farm operator households report 

they live in a residence owned by the farm. Virtually all of the rest (around 

20 percent) report owning their own home, with only 2 percent reporting that 

they rent their dwelling. In contrast, among all U.S. households, two-thirds 

report owning their own home and one-third report renting. Market value of 

homes is comparable across the two groups for households that own their 

own home. But for those farm households whose home is owned by the farm, 

the market value of their residence averages 72 percent of homes owned by 

all U.S. households. 

Farm Households (CE) 

Within the CE sample of all U.S. households, we create a farm subsample by 

selecting any household that reported farm income. To get suffi cient sample 

size, we pool CE observations from 2005 to 2007. The resulting sample size 

of 1,235 includes repeat observations of the same unit (up to four quarters 

in total). (In its statistical analysis, BLS treats each quarterly observation as 

independent.) The CE farm sample scales up to a U.S. population of around 

1.7 million farm households, about 15 percent short of the USDA’s count 

of 2.0 million principal farm operators. The defi cit becomes 23 percent if 

one takes into account that the CE sample includes households of secondary 

operators as well. 

Differences in demographic and economic characteristics suggest the CE 

sample is an imperfect proxy for the farm population, as defi ned by USDA. 

Household income averages about 10 percent higher in the CE farm sample 

than in ARMS. The wage/salary share is higher in the CE sample (62.0 percent versus 53.6 percent), while the self-employment share and share with 

negative household income are lower.

Diversity Within the Farm Sector: Farms with Sales of $100,000+ 

and Very Small Rural-Residence Lifestyle Farms (ARMS) 

We exploit the diversity of the farm sector by comparing two farm household subgroups in ARMS—one that is not much exposed to the risks of selfemployment income variability (households operating farms with annual sales 

of $10,000 or less, with an operator whose primary occupation is other than 

farming—very small rural-residence farms) and one that is exposed to such 

risks (households operating farms with annual sales of $100,000 or more). 
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Though very small rural-residence farms represent about 40 percent of U.S. 

farms, they produce a negligible portion of total sales. On average, farm 

income in this group is negative (-$8,245 in 2006). Total household income 

is a third higher than for all U.S. households, but the shares of income deriving from self-employment income (from farm and nonfarm sources) and from 

wages and salary are comparable to those of all U.S. households. The share 

with negative household income cannot be reported due to small sample size, 

but the estimate is substantially smaller than the overall farm household share 

(6.0 percent).

In contrast, farms with $100,000 or more in sales represented 16 percent of 

farms and produced 89 percent of total sales in 2006. On average, the selfemployment share of household income (66.9 percent) is three times that of 

all farm households, and the share with negative household income (13.7 percent) is more than twice that of the average farm household.
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Household Expenditure 

and Consumption Levels

We focus fi rst on farm households, exploring which components contribute most 

to differences between farm household consumption and expenditures. We then 

turn to benchmarking the new ARMS measure against the CE measure. 

Comparing Expenditure and 

Consumption Measures for Farm Households 

Table 4 reports and fi gure 2 illustrates estimated means for components of 

expenditures and consumption for farm and all U.S. households. We consider 

fi rst the farm household indicators. At the aggregate level, mean farm household consumption ($42,368) is 14 percent higher than mean farm household 

expenditures ($37,288). Similarly, on a per-person basis, mean equivalentconsumption ($27,141) is also 14 percent higher than mean equivalentexpenditures ($23,810). 

The largest difference between farm expenditures and consumption is attributable to the housing component. The ARMS expenditure measure is substantially lower than consumption because three-quarters of farm households 

Table 4

Comparison of mean household expenditures and consumption by component, 

across farm operator and all U.S. households, 2006

Farm households (ARMS) All U.S. households (CE)

Expenditures Consumption Expenditures Consumption

Category $ % $ %$%$%

Food 6,968 18.7 6,968 16.4 6,003 12.5 6,003 14.3

Housing (total) 6,137 16.5 15,658 37.0 15,504 32.3 17,380 41.5

Shelter services 1,472 3.9 10,993 25.9 11,187 23.3 13,063 31.2

Operating expenses 4,665 12.5 4,665 11.0 4,317 9.0 4,317 10.3

Transport (total) 7,091 19.0 6,919 16.3 8,472 17.7 7,608 18.2

Vehicle services 3,414 9.2 3,242 7.7 4,411 9.2 3,547 8.5

Operating expenses 3,677 9.9 3,677 8.7 4,061 8.5 4,061 9.7

Health care (total) 5,097 13.7 5,097 12.0 2,609 5.4 2,609 6.2

Health/dental insurance (household share) 2,991 8.0 2,991 7.1 1,465 3.1 1,465 3.5

Out-of-pocket medical care expenditures 2,106 5.6 2,106 5.0 1,143 2.4 1,143 2.7

Personal insurance and retirement plans 2,690 7.2 -- 5,270 11.0 --

Contributions (outside of household) 1,756 4.7 -- 1,869 3.9 --

All other 7,549 20.2 7,549 17.8 8,252 17.2 8,252 19.7

Home consumption of farm produce -- 177 0.4 -- --

TOTAL (mean) 37,288 100 42,368 100 47,979 100 41,852 100

TOTAL (median) 29,770 36,000 35,959 35,159

TOTAL- per-person-equivalent (mean) 23,810 27,141 32,270 28,137

TOTAL- per-person-equivalent (median) 19,320 23,092 24,409 24,001

* Though the CE accounting does not count mortgage principal as an expenditure (but rather as a change in household assets), we do count it 

as an expenditure in our accounting here.

Sources: USDA, Economic Research Service using Agricultural Resource Management Survey, 2006, and Consumer Expenditure Survey, 

2006.
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report they live in a residence owned by the farm, and so incur no outlays 

for shelter. Because the consumption measure includes a value for housing 

shelter services for that group, the average value of housing shelter services 

jumps to $10,993 from an average expenditure value of $1,472, and the value 

of total housing (which also includes operating costs) increases from $6,137 

in mean expenditures to $15,658 in mean consumption. This adjustment 

raises total farm household expenditures by 26 percent. 

Replacing current outlays for vehicle purchases with estimated vehicle services made little difference on the aggregate level, resulting in a reduction 

relative to total expenditures of less than 0.5 percent. On the individual level, 

however, consumption is lower than expenditures for those who purchased 

vehicles in 2006, and higher for those who did not. 

Including the market value of farm production for household consumption 

adds less than 1 percent to the consumption estimate. (The value of food 

purchased with food stamps, another in-kind source, cannot be distinguished 

from other food expenditures.) The deductions of (1) retirement savings 

and life/disability insurance and (2) contributions to individuals outside the 

household represent 7.2 percent and 4.7 percent of total expenditures, respectively (table 4).

Source: USDA, Economic Research Service using Agricultural Resource Management 

Survey, 2006, and Consumer Expenditure Survey, 2006.

Figure 2

Average expenditures and consumption, by component, 

of farm operator and all U.S. households, 2006

 $ 

Farm All

U.S.

Farm All

U.S.

Farm All

U.S.

0

10,000

20,000

30,000

40,000

50,000

Food

Housing

Transport

Health care

Insurance/

retirement

Contributions

All other

Expenditures

With housing Without housing

Consumption
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Benchmarking Farm Household (ARMS) Estimates 

With All U.S. Household (CE) Estimates 

Figure 2 illustrates the expenditure and consumption measures, by component, for both farm and all U.S. households. The CE estimated mean household expenditures for all U.S. households are close to 30 percent higher than 

the ARMS estimated mean for farm households; however, if we exclude 

housing from the measure, U.S. household expenditures are essentially the 

same as farm household expenditures. 

The estimates of mean household consumption are quite similar for the two 

populations ($42,368 for farm versus $41,852 for all U.S. households). The 

per-person equivalent-consumption estimates are $27,141 for farm versus 

$28,137 for all U.S. households. 

The shares of consumption/expenditures accounted for by health care and 

food are higher for farm households than for all U.S. households; the shares 

spent on housing and “all else” are lower, with transport shares essentially 

the same. The absolute size of the differences in consumption levels between 

farm and all U.S. households is greatest for health care (+$2,488), followed 

closely by housing (-$1,744). The major difference in housing is in “shelter 

services,” which refl ects the lower housing values in nonmetro areas (Jolliffe, 

2006), where farm households are much more prevalent. Higher health care 

expenditures among farm households are consistent with fi ndings in other 

studies using alternative farm household data sets (Access Project, 2007).12 12A recent study compared health 

expenditure data from ARMS for farm 

households with data from the Medical 

Expenditure Panel Study for all U.S. 

households, which allows for more 

detailed decomposition of the differences (Jones et al., 2009). Health 

expenditures tend to be higher for all 

types of insurance coverage (including 

lack of insurance) among farm households compared to all U.S. households; 

however, the predominant source of 

the difference is the larger share of 

nonelderly farm households holding 

private direct-purchase insurance (17.9 

percent for farm households versus 6.5 

percent for all U.S. households), the 

type with the highest average household health expenditures ($7,389 for all 

U.S. households compared to $9,110 

for farm households).
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The Relationship Between Household 

Consumption and Income 

In this section, we assess whether the relationships between income and consumption for farm and all U.S. households are consistent with the prediction 

that households exposed to greater income variability will smooth consumption from current income more than households with more stable income 

over time. The fi rst test is to compare the patterns of average equivalentconsumption to average equivalent-income across equivalent-income categories. We fi rst compare the patterns for all U.S. versus all farm households. To 

assess the reasonableness of the ARMS results, we compare the patterns in 

consumption shares (food, health, etc.) by type across the income categories. 

Subsequently, to avoid the noise introduced into the comparison as a result of 

using two different surveys with different elicitation approaches for expenditures, we conduct in-survey comparisons within CE and ARMS. 

The second test will compare the consistency of individual household rankings (by quintile in the distributions) for consumption and for income, among 

farm households versus all U.S. households. 

Propensity To Consume From Current Income: 

Farm Versus All U.S. Households 

ARMS Farm Households and CE All U.S. Households 

We fi rst explore the hypothesis that farm households budget or moderate 

consumption to a greater extent than all U.S households, analyzing data from 

the best sources for each population—ARMS for farm households, and CE 

for all U.S. households. To do this, we split households in each population 

into six equivalent-income categories. Figure 3 illustrates the value of mean 

equivalent-consumption associated with mean equivalent-income for each 

population. Table 5 reports the values, along with additional economic data 

to provide insight into the extent of income risk-bearing and wealth (to support spending) within the category. 

The lowest equivalent-income category is for households with negative 

household income—where self-employment losses exceed other sources of 

income. (By separating this group out, the interpretation of shares of income 

from wages or self-employment income is much cleaner.) The income shocks 

typically needed to generate negative household income are likely transitory, so we expect that permanent income may be substantially higher for 

households with negative current income. For example, nearly 6 percent of 

farm households had negative income in 2006 (compared to 0.2 percent for 

all U.S. households), but their average household net worth of $1.3 million is 

comparable to farm households with equivalent-income of $70,000-$124,999 

(table 5). The average share that self-employment provides of total household 

income is negative in the second income category ($1-$19,999) for farm 

households, but increases to over 50 percent in the top two income groupings 

($125,000-$224,999 and $225,000 and above). 
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As expected, the ratio of consumption to income decreases as income 

increases for both farm households and all U.S. households. Also as 

expected, the fl atter consumption-income relationship for farm households 

illustrates their lower propensity to increase consumption with higher income 

in a given year, in order to accommodate greater income variability from 

year to year. 

Our expectation is that, when income is unexpectedly low, farm households 

will be less inclined to cut back essentials such as food compared to similar households with more stable income, and when income is unexpectedly 

high, they will be less inclined to expand discretionary purchases. To assess 

whether we observe such behavior, we also report—for each equivalentincome category—the consumption shares for the fi ve consumption components. We expect food shares will decline and “all else” shares will increase 

with income, except for the group with negative household income—we anticipate this group has positive and substantially higher permanent income, and 

so will display patterns comparable to a higher equivalent-income category. 

The trends across income levels in consumption shares by type are comparable 

in the two populations: consumption shares for food, housing, health care—

and for farm households, home consumption—basically decrease as income 

grows; shares for transportation increase until the upper tail of the distribution, 

where they decrease; and shares of “all else” increase across income levels. 

Households with negative household income are an exception to the pattern. 

For the most part, shares of “all else” consumption are lower for farm households; however, the rates of increase in the shares are the same for farm and all 

U.S. households. From the lowest (positive) to the highest income category, 

Note: For the two population groups, each point represents the mean equivalent-income, 

equivalent-consumption pair for the following equivalent-income categories: (<$0, 

$1-19,999, $20,000-$39,999, $40,000-$69,999, $70,000-124,999, and $125,000-224,999). 

See table 5 for data.

Source: USDA, Economic Research Service using Agricultural Resource Management 

Survey, 2006, for farm households and using Consumer Expenditure Survey, 2006, for all 

U.S. households.

Figure 3

Average propensity to consume, by equivalent-income class, 

of farm operator (ARMS) and all U.S. households (CE), 2006

Per-person consumption-equivalent ($)

0

20,000

40,000

60,000

80,000

−75,000 0 75,000 150,000 225,000

Per-person equivalent-income ($)

All U.S. households

All U.S. farm operator households
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Table 5

Average propensity to consume by income-equivalent categories, farm operator households and all U.S. households, 

2006 (2005-2007)

Category <$0 $1-

19,999

$20,000 - 

$39,999 

$40,000 

- $69,999 

$70,000 - 

$124,999

$125,000 

- $224,999

$225,000+ All

Farm operator households, 2006 (ARMS) 

Percent of farm households 5.7 21.1 29.9 26.2 12.1 3.1 1.8 100.0

Cumulative percent of farm households 5.7 26.9 56.8 83.0 95.1 98.2 100.0

Wage/salary income share -18% 63% 66% 61% 53% 36% 17% 54%

Self-employment income share 127% -17% 2% 15% 31% 49% 70% 23%

Household net worth—mean ($) 1,301,351 676,170 710,745 949,645 1,287,517 1,978,061 3,291,686 955,708

Est. market value of home 

(household or farm owned) ($) 151,561 109,859 126,395 155,384 184,343 232,155 325,531 145,697

Equivalent-income—mean ($) -36,892 12,266 30,469 52,389 90,072 163,418 476,074 48,019

Equivalent-consumption—mean ($) 28,869 19,257 23,228 29,154 37,220 41,235 57,482 27,141

Equiv-C (mean)/Equiv-Y(mean) -0.78 1.57 0.76 0.56 0.41 0.25 0.12 0.57

Equivalent-consumption shares:

 Food 17% 19% 17% 16% 15% 14% 11% 16%

 Housing 38% 39% 37% 37% 36% 36% 33% 37%

 Transport 12% 14% 16% 18% 19% 14% 17% 16%

 Health care 15% 13% 13% 11% 10% 14% 11% 12%

 All else 17% 14% 17% 18% 19% 22% 28% 18%

 Home consumption of farm produce 0.8% 0.7% 0.5% 0.3% 0.2% 0.2% 0.2% 0.4%

All U.S. households, 2006 (CE) 

Percent of U.S. households 0.2 32.0 31.5 23.4 10.1 2.3 0.5 100.0

Cumulative percent of U.S. households 0.2 32.2 63.7 87.1 97.1 99.5 100.0

Wage/salary income share -56% 57% 78% 85% 85% 79% 66% 79%

Self-employment income share 152% 1% 3% 5% 7% 11% 23% 6%

Est. market value of owned home ($) 396,374 77,605 144,668 230,244 407,460 555,752 805,280 183,212

Equivalent-income—mean ($) -31,548 11,458 29,336 51,981 88,888 158,556 352,918 39,558

Equivalent-consumption—mean ($) 39,254 17,815 24,981 33,297 45,909 67,759 95,292 28,137

Equiv-C (mean)/Equiv-Y(mean) -1.24 1.55 0.85 0.64 0.52 0.43 0.27 0.71

Equivalent-consumption shares:

 Food 13% 16% 15% 14% 12% 11% 9% 14%

 Housing 40% 46% 43% 41% 40% 37% 38% 42%

 Transport 19% 15% 19% 20% 18% 16% 14% 18%

 Health care 5% 7% 7% 6% 5% 5% 5% 6%

 All else 24% 16% 17% 20% 24% 32% 33% 20%

Farm operator households, 2005-2007 (CE) 

Percent of farm households na 10.6 29.7 36.1 16.1 4.2 na 100.0

Cumulative percent of farm households na 12.1 41.9 78.0 94.1 98.4 na

Wage/salary income share na 71% 66% 62% 66% 49% na 56%

Self-employment income share na 7% 17% 23% 14% 29% na 19%

Est. market value of owned home ($) na 179,087 268,459 253,253 428,231 564,791 na 303,066

Equivalent-income—mean ($) na 12,398 29,857 51,795 91,752 159,271 na 54,523

Equivalent-consumption—mean ($) na 20,993 24,336 29,296 43,649 55,733 na 31,469

Equiv-C (mean)/Equiv-Y(mean) na 1.69 0.82 0.57 0.48 0.35 na 0.58

Equivalent-consumption shares:

 Food na 15% 14% 14% 14% 10% na 15%

 Housing na 35% 35% 37% 33% 34% na 42%

 Transport na 21% 20% 21% 19% 17% na 18%

 Health care na 9% 11% 10% 9% 7% na 6%

 All else na 19% 20% 19% 26% 32% na 20%

Sources: USDA, Economic Research Service using Agricultural Resource Management Survey and Consumer Expenditure Survey.
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“all else” shares double from 14 percent to 28 percent for farm households and 

from 16 percent to 33 percent for all U.S. households (table 5). 

CE Farm Households and CE All U.S. Households 

Farm households retain a fl atter consumption-income relationship (than all 

U.S. households) when measured with CE data (fi g. 4), though the line is not 

as fl at as with ARMS data (fi g. 3). This pattern is consistent with expectations, given that, in the two highest income categories, the self-employment 

income shares for CE farm households are about half that of ARMS farm 

households (14 and 29 percent for CE farm households versus 31 and 49 

percent for ARMS farm households). Less dependent on self-employment 

income, CE farm households are more likely to have more stable income.

Consumption shares for farm households relative to all U.S. households in 

the CE data are consistent with ARMS for some commodities (housing is 

again lower and medical care higher for CE-farm households than for CE-all 

U.S. households), but diverge for others (the food share is lower and the “all 

else” share is higher for CE-farm households). Also, the patterns in CE farm 

consumption shares appear more random, attributable in part to the small 

sample sizes for individual income categories. Still, as elsewhere, food shares 

tend to decline with income and “all else” shares tend to increase. 

Given the small sample sizes and presumed differences in risk exposure 

between cohorts, it seems unwarranted to interpret the differences between 

the CE and ARMS farm households as indicating understatement of conNote: For the two population groups, each point represents the mean equivalent-income, 

equivalent-consumption pair for the following equivalent-income categories:(<$0, 

$1-19,999, $20,000-$39,999, $40,000-69,999, $70,000-124,999, and $125,000-224,999). 

Sample size is insufficient to report the <$0 category for U.S. farm households. See table 5 

for data.

Source: USDA, Economic Research Service using Consumer Expenditure Survey, 2006 for 

all U.S. households and 2005-2007 for all U.S. farm households.

Figure 4

Average propensity to consume, by equivalent-income class, 

of farm operator households (CE) and all U.S. households (CE), 

2005-2007

Per-person consumption-equivalent ($)

Per-person equivalent-income ($)

All U.S. households

All U.S. farm operator households

0

20,000

40,000

60,000

80,000

−75,000 0 75,000 150,000 225,000
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sumption levels at the upper end of the income distribution. At the same 

time, we are unable to rule out such measurement error.

Propensity To Consume From Current Income: 

Households of Farms with Sales of $100,000+ Versus 

Households of Very Small Rural-Residence Farms 

We exploit the diversity of the farm sector by comparing two farm household subgroups in ARMS—one that is not much exposed to the risks of 

self-employment income variability (very small rural-residence farms) and 

one that is (farms with annual sales of $100,000 or more). For households 

of large farms, equivalent-income is higher on average, but is also more 

dispersed: it is more likely to be negative and is more likely to be above 

$225,000 (table 6). As expected, households operating these large farms have 

a lower propensity to consume from current income than households operating very small rural-residence farms (fi g. 5). 

We again report shares for the fi ve components of consumption. Perhaps 

due to the smaller sample size, the patterns are less clear than with all farm 

households. The strongest trends are consistent with our predictions: the food 

share declines with income and the “all else” share increases with income 

(with one income category out of the pattern for each household type). 

Note: For the two population groups, each point represents the mean equivalent-income, 

equivalent consumption pair for the following equivalent-income categories: (< $0, 

$1-$19,999, $20,000-$39,999, $40,000-$69,999, $70,000-$124,999, $125,000-$224,999). 

There is insufficient sample size to report the < $0 and $225,000 + categories for very small 

rural-residence farm households. See table 6 for data. 

Definitions: Large farms: farms with sales of $100,000 or more. Very small rural-residence 

farms: farms where the principal operator indicates his primary occupation is other than 

farming, and whose farm has sales of $10,000 or less this year.

Source: USDA, Economic Research Service using Agricultural Resource Management 

Survey, 2006.

Figure 5

Average propensity to consume, by equivalent-income class, 

by households of large farm operators and of very small farm 

operators (ARMS), 2006

Per-person consumption-equivalent ($)

Per-person equivalent-income ($)

Very small rural-residence 

farm operator households

Large farm operator households

0

20,000

40,000

60,000

80,000

−75,000 0 75,000 150,000 225,000
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Table 6

Average propensity to consume of households of farm operators of $100,000+ sales versus very small rural-residence 

farms, by equivalent-income groups, 2006

Both income and consumption measures are reported in equivalent form.

Income-equivalent classes: <$0 $1-19,999 $20,000 - 

$39,999 

$40,000 - 

$69,999 

$70,000 - 

$124,999

$125,000 - 

$224,999 $225,000+ All

Farms with sales of $100,000 or more: 

Percent of households 13.7 14.0 21.1 21.5 16.7 9.8 3.3 100.0

Cumulative percent of households 13.7 27.7 48.8 70.3 87.0 96.7 100.0 

Wage/salary income share -14% 76% 41% 32% 19% 11% 3% 22%

Self-employment income share 119% -8% 44% 58% 70% 82% 91% 67%

Household net worth—mean ($) 1,648,679 1,352,141 1,116,385 1,370,141 1,868,172 2,709,479 3,528,134 1,636,325

Est. market value of home 

(household or farm owned ($)

152,443 132,302 130,615 146,003 164,529 227,143 235,344 155,155

Equivalent-income—mean ($) -65,996 10,443 29,308 55,068 91,296 208,431 682,774 68,229

Equivalent-consumption—mean ($) 29,477 22,359 24,673 27,646 31,776 37,256 39,465 28,540

Equiv-C (mean)/Equiv-Y(mean) -0.45 2.14 0.84 0.50 0.35 0.18 0.06 0.42

Equivalent-consumption shares:

Food 17% 17% 16% 20% 16% 15% 13% 17%

Housing 34% 36% 35% 34% 35% 38% 37% 35%

Transport 14% 11% 15% 14% 15% 13% 14% 14%

Health care 14% 16% 14% 14% 11% 13% 10% 14%

All else 19% 18% 19% 17% 22% 20% 25% 20%

Home consumption of farm produce 1% 2% 1% 1% 1% 0% 0% 1%

Very small rural-residence farms: 

Percent of households na 14.7 33.4 32.0 15.3 3.1 na 100.0

Cumulative percent of households na 14.7 48.1 80.1 95.4 98.5 na

Wage/salary income share na 100% 99% 85% 76% 66% na 82%

Self-employment income share na -8% -9% 6% 16% 26% na 8%

Household net worth--mean ($) na 464,763 447,771 662,464 991,548 1,832,898 na 659,501

Est. market value of home 

 (household or farm owned) ($)

na 111,941 123,505 148,897 201,209 267,634 na 151,791

Equivalent-income—mean ($) na 13,950 30,751 52,683 87,515 200,748 na 51,331

Equivalent-consumption—mean ($) na 17,860 23,165 30,624 39,860 56,129 na 28,763

Equiv-C (mean)/Equiv-Y(mean) na 1.28 0.75 0.58 0.46 0.28 na 0.56

Equivalent-consumption shares:

Food na 22% 19% 16% 15% 15% na 17%

Housing na 39% 35% 36% 37% 28% na 36%

Transport na 14% 17% 19% 23% 20% na 19%

Health care na 9% 10% 10% 9% 7% na 10%

All else na 16% 18% 19% 16% 31% na 18%

Home consumption of farm produce na 0% 0% 0% 0% 0% na 0%

Notes: To take account of differences in household size and economies of scale in standard of living, we adjust total household income and total 

household consumption by an equivalence scale (the square root of household size). 

Defi nitions: Large farms: farms with sales of $100,000 or more. Very small rural-residence farms: farms where the principal operator indicates his primary occupation is other than farming, and whose farm has sales of $10,000 or less this year. 

Median per-person equivalent-income is $40,493 for very small rural residence farms, and $42,103 for $100,000+ sales farms in this sample.

na = insuffi cient sample to report.

Source: USDA, Economic Research Service using ARMS analysis sample, 2006.
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Consistency in Household Ranks in Income and 

Consumption Distributions

The lack of a close mapping between current income and consumption measures for farm households compared to all U.S. households can be attributed 

to the greater discrepancy they experience between permanent income and 

current income. As such, current income is a weaker proxy for current standard of living for farm (and other self-employed households) than for all U.S. 

households. 

The two-way distributions in table 7 were inspired by the earlier work of 

Rogers and Gray (1994), who compared quintiles of income to quintiles of 

outlays for all U.S. households using 1992 CE data. If current income were 

a good predictor of consumption, we would expect households to be concentrated along the diagonals, where the household quintile ranking in the 

consumption distribution matches its ranking in the income distribution; 

alternatively, if the two were uncorrelated, a random distribution would suggest 20 percent in each cell in the income row. 

Equivalent-income and equivalent-consumption quintiles: For U.S. households, the diagonal cells have the largest share of households along each row 

in the income-consumption table. The effect is strongest for the fi rst and fi fth 

quintiles: notably, 58 percent of households in the lowest income quintile are 

in the lowest consumption quintile, and 56 percent of households in the highest income quintile are in the highest consumption quintile. The other diagonal cells have about one-third of their row totals. 

Table 7

Two-way distributions of household well-being measures by quintiles, 2006

Farm operator households All U.S. households

Equivalent 

income

quintiles

Equivalent-consumption quintiles Equivalent 

income

quintiles

Equivalent-consumption quintiles

20 40 60 80 100 20 40 60 80 100

20 38 23 12 14 13 20 58 21 10 7 5

40 28 22 27 13 10 40 27 32 22 12 7

60 18 26 22 23 10 60 11 29 29 20 11

80 7 17 25 23 28 80 3 15 28 33 21

100 8 11 15 27 38 100 1 3 11 28 56

Notes: Each row and each column sums to 100 percent (except due to rounding error).

Sources: USDA, Economic Research Services using Consumer Expenditure Survey, 

2006, and Agricultural Resource Management Survey, 2006 analysis sample.

Income

quintiles

Household net worth quintiles

20 40 60 80 100

20 25 22 18 20 15

40 28 23 23 12 14

60 19 25 22 21 13

80 19 17 23 21 20

100 10 13 14 25 38
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Farm households are more likely to be off-diagonal. For example, among 

farm households, those in the lowest income quintile are much more likely 

to be in one of the three highest consumption quintiles than is evident for 

all U.S. households (39 percent of farm versus 22 percent of all U.S. households). Analogously, farm households in the highest income quintile are 

much more likely to be in the three lowest consumption quintiles (34 percent 

of farm versus 15 percent of all U.S. households). 

Income-wealth quintiles: The fi nal two-way comparison in table 7 is income 

versus net worth quintiles for farm households. The divergence in ranking between income and wealth is particularly strong for those in the fi rst 

income-quintile (53 percent of which are in the top three wealth quintiles). 

This is consistent with households that operate commercial farms with an 

extensive asset base experiencing large income dips in a given year. 

In sum, the extensive divergence in quintile ranking between income and 

consumption indicates that current farm household income is more variable 

than the long-term, or permanent, household income that drives consumption. 

Since wealth provides a source of assets to draw down or to borrow against 

during temporary income shortfalls, the even stronger pattern of divergence 

between income and wealth quintiles for farm households further supports 

this inference. 
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Relative Well-Being of Farm and All U.S. 

Households, as Indicated by Income and 

Consumption

Household income of farm households, compared to all U.S. households, is 

higher at the mid-point of the distribution, but also is more dispersed—lower 

at the low end of the distribution and higher at the high end; as a result, farm 

household income is higher at all deciles but the fi rst, compared to all U.S. 

households (fi g. 6). Farm households also have a lower tendency to increase 

consumption as income increases than do all U.S. households. What, then, is 

the net effect of these countervailing patterns on the distribution of consumption levels in the two populations? 

To illustrate the different perspectives on relative well-being of farm and all 

U.S. households afforded by income and consumption measures, table 8 presents the values at each decile of the income and consumption distributions 

for the two populations. As a benchmark for the income data in the smaller 

consumption-analysis samples, column 1 of table 8 reports the value of equivalent-income at each decile, using CPS for all U.S. households and the full 

ARMS sample (with data from all fi ve survey versions) for farm households. 

Columns 2 and 3 report the values at the deciles of equivalent-income and 

equivalent consumption, respectively, using the CE (for all U.S. households) 

and the ARMS (for all farm households) consumption-analysis samples.

Comparing the distribution of equivalent-income in columns 1 and 2 indicates that the ARMS consumption-analysis sample understates farm household income (relative to the full ARMS sample) at the 90th percentile and the 

CE income distribution understates all U.S. household income (relative to 

CPS) throughout the distribution. As a result, the farm household dominance 

in household income appears even greater in column 2 relative to column 1, 

except at the 80th and 90th percentiles. 

Source: USDA, Economic Research Service using Agricultural Resource Management Survey 2006, 

and Consumer Expenditure Survey, 2006.

Figure 6

Values of household equivalent-income and equivalent-consumption at decile cut-points, 

all farm and all U.S. households, 2006

Dollars

10 20 30 40 50 60 70 80 90

0

20,000

40,000

60,000

80,000

100,000

All U.S. households, per-person equivalent-income

All farm households, per-person equivalent-income

All U.S. households, per-person equivalent-consumption

All farm households, per-person equivalent-consumption

Percentiles of per-person equivalent-income or equivalent-consumption
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Table 8

Distributions of household equivalent-income and equivalent-consumption, 2006

Farm operator households 1 2 3

ARMS full sample ARMS analysis sample

Per-person equivalent-income Per-person equivalent consumption

Mean $51,878 $48,060 $27,141

Decile maximum

10 $6,691 $8,060 $11,866

20 $15,405 $15,710 $15,037

30 $22,339 $22,098 $17,645

40 $29,397 $29,840 $20,720

Median 50 $35,560 $36,117 $23,092

60 $41,911 $41,936 $26,267

70 $53,007 $51,626 $30,214

80 $70,035 $64,114 $35,779

90 $107,390 $89,795 $44,250

Ratio

80:20 4.55 4.08 2.38

90:10 16.05 11.14 3.73

Percent

Poverty rate per person* 14.4 13.8 7.8

All U.S. households 1 2 3

CPS CE analysis sample

Per-person equivalent-income Per-person equivalent consumption

Mean $43,227 $39,558 $28,137

Decile maximum

10 $9,384 $8,440 $10,886

20 $14,962 $13,729 $14,589

30 $20,162 $18,777 $17,868

40 $25,786 $24,288 $20,886

Median 50 $32,067 $30,281 $24,001

60 $39,659 $36,902 $27,420

70 $48,988 $45,334 $31,727

80 $61,327 $56,564 $37,626

90 $84,400 $77,610 $48,434

Ratio

80:20 4.10 4.12 2.58

90:10 8.99 9.20 4.45

Percent

Poverty rate per person* 12.3 11.8 9.2

Notes. For comparability across households of different sizes, we report per person equivalent-income and equivalent-consumption, where 

income and consumption have been adjusted for household size.

*Analogous to the procedure for individual income poverty, individuals are determined to be in consumption poverty by comparing their total 

household consumption against the offi cial census poverty threshold used for income poverty. The census threshold incorporates an alternative 

equivalency adjustment for household size to the one employed in this study. 

Sources: USDA, Economic Research Service using Consumer Expenditure Survey, 2006, and Agricultural Resource Management Survey, 2006 

analysis sample. 
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In column 3, we see that the net effect of predominantly higher income, but a 

lower propensity to consume as income increases, is that the farm household 

distribution of consumption is very similar to that for all U.S. households. 

The similarities are strongest for the 30th, 40th, and 50th percentiles of the distribution. At the tails of the distributions, the pattern appears to be reversed 

from that of the income distribution: farm households appear better off at the 

low end of the distribution and worse off at the high end of the distribution, 

relative to all U.S. households. 

We need to qualify the results at the upper end of the distribution because we 

are not able to rule out the possibility that measurement error could understate consumption levels at the upper end; in addition, there is attrition from 

the sample of the highest-income farm households, resulting in lower income 

at the 90th percentile. 

Our fi nal indicator of well-being focuses on the low end of the distribution—

income and consumption poverty rates. A convention in the literature is to 

calculate consumption poverty by comparing a household’s consumption level 

to the census poverty threshold for the composition of that household, used 

to determine offi cial income-based poverty rates. If consumption is a better 

indicator of standard of living for households where money income is less predominant as a resource and/or where income is highly variable across years, 

then consumption poverty may be a better measure of economic disadvantage 

than the offi cial census income-based measure (Jorgenson, 1998; Meyers and 

Sullivan, 2003; Slesnick, 2001). The census poverty threshold incorporates an 

adjustment for household size (including age composition), one that is different 

from the equivalency measure employed in our data analysis. Consequently, 

poverty rates are calculated on total income and total consumption measures. 

For the farm population (based on the ARMS analysis sample), poverty drops 

from 13.8 percent (14.4 percent in full ARMS sample) based on the offi cial 

census income-poverty measure to 7.8 percent for the consumption-poverty 

measure. For all U.S. households (based on the CE analysis sample), poverty 

drops from 11.8 percent (12.3 percent in CPS) based on the offi cial Census 

income-poverty measure to 9.2 percent for the consumption-poverty measure. Whereas farm households have a higher income-poverty rate, they have 

a lower consumption-poverty rate than all U.S. households. 

In table 9 and fi gure 7, we report the per-person equivalent-income and 

equivalent-consumption distributions for households operating $100,000+ 

sales farms and very small rural-residence farms, two farm household subgroups that differ substantially in the extent of exposure to income variability 

from self-employment. Per-person equivalent-income is much more dispersed for households operating the larger farms than for households operating the very small farms, a pattern that affects both tails of the distribution: 

the larger-farm household income is lower at the low end of the distribution 

(indeed negative until the 14th percentile compared to below the 2nd percentile for the very small farms), and higher at the high end of the distribution. However, the propensity to consume is suffi ciently lower among the 

larger-farm households that the consumption distributions are very similar. 

Analogously, the income-poverty rates are quite divergent (22 percent for 

$100,000+ sales farms versus 7 percent for very small rural-residence farms), 

but the consumption-poverty rates are roughly 6 percent for both groups. 
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To further understand the relative well-being of farm households, it is also 

instructive to compare all U.S. households (table 8, fi gure 6) with the subgroup of large-farm households (table 9, fi gure 7). Though large family 

farms (farms with sales of $100,000 or more) represent only 16 percent of 

farms, they produced 89 percent of total farm sales in 2006. At the low end 

of the income and consumption distributions, large-farm households have 

substantially lower equivalent-income, but higher equivalent-consumption, 

than the population of all family-farm households—which further increases 

the farm-all U.S divergence on the two measures. The differences at the low 

end are refl ected in the poverty rates: income poverty is 22 percent among 

persons living in large-farm households, compared to 14 percent for persons in all farm households and 12 percent for all U.S. households; whereas 

consumption-poverty is 6 percent for persons living in large-farm households, compared to 8 percent in all farm households and 9 percent in all U.S. 

households. 

At the high end of the income and consumption distributions, large-farm 

households have substantially higher equivalent-income, but—due to their 

higher exposure to income risk and their lower marginal propensity to 

consume—only slightly higher equivalent-consumption than all family-farm 

households. As a result, at the upper end of the consumption distribution, the 

consumption levels of large-farm households are very similar to those of all 

U.S. households.

Source: USDA, Economic Research Service using Agricultural Resource Management Survey 2006, and Consumer Expenditure Survey, 2006.

Figure 7

Values of equivalent-income and equivalent-consumption at decile cut-points, 

households of very small rural-residence and $100,000+ sales farm operators, 2006

Dollars

Percentiles of per-person equivalent-income or equivalent-consumption

−20,000 10 20 30 40 50 60 70 80 90

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000 Very small rural-residence farm households, per-person equivalent-income

$100,000+ sales farm households, per-person equivalent-income

Very small rural-residence households, per-person equivalent-consumption

$100,000+ sales farm households, per-person equivalent-consumption
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Table 9

Distributions of household equivalent-income and equivalent-consumption, 2006

Farm operator households 1 2 3

Farms with sales of $100,000 or more Full sample Analysis sample

Per-person equivalent-income Per-person equivalent consumption

Mean $79,124 $68,229 $28,540

Decile maximum

10 -$14,209 -$7,400 $13,526

20 $9,479 $9,486 $16,417

30 $22,981 $21,564 $19,528

40 $34,640 $31,204 $21,526

Median 50 $46,694 $42,103 $24,893

60 $60,670 $55,233 $28,023

70 $79,066 $69,910 $31,704

80 $111,591 $91,325 $37,346

90 $182,642 $163,136 $45,531

Ratio

80:20 11.77 9.63 2.27

90:10 -12.85 -22.05 3.37

Percent 

Poverty rate per person* 22.1 21.7 5.8

Farm operator households 1 2 3

Very small rural-residence farms Full sample Analysis sample

Per-person equivalent-income Per-person equivalent consumption

Mean $51,530 $51,331 $28,763 

Decile maximum

10 $15,710 $17,440 $13,117

20 $22,066 $23,115 $16,127

30 $28,807 $30,572 $18,573

40 $33,404 $35,284 $21,873

Median 50 $37,528 $40,493 $24,275

60 $42,866 $47,178 $28,681

70 $51,970 $57,004 $32,497

80 $65,151 $66,052 $38,627

90 $90,478 $84,512 $47,274

Ratio

80:20 2.95 2.86 2.40

90:10 5.76 4.85 3.60

Percent

Poverty rate per person* 7.3 6.9 6.1

Notes. For comparability across households of different sizes, we report per-person equivalent-income and equivalent-consumption, where income 

and consumption have been adjusted for household size.

*Analogous to the procedure for individual income poverty, individuals are determined to be in consumption poverty by comparing their total household consumption against the offi cial census poverty threshold used for income poverty. The census threshold incorporates an alternative equivalency adjustment for household size to the one employed in this study. 

Sources: USDA, Economic Research Service using Agricultural Resource Management Survey, 2006 analysis sample. 
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Conclusions

ERS publishes indicators of economic well-being for farm operator households. To date, the focus has been on income- and wealth-based measures 

calculated from the annual survey of farm households conducted by USDA 

(ARMS). In this report, we present estimates of a consumption measure for 

farm households calculated using revised ARMS expenditure questions, and 

benchmark the measure against the Bureau of Labor Statistics’ Consumer 

Expenditure Survey (CE).

To assess the possibility of distortions introduced into the comparison 

from using surveys with different elicitation methods for expenditures, we 

conducted within-survey comparisons: within CE, we compared data for a 

sample of farm households created by pooling data for 2005-07 with data for 

all U.S. households; within ARMS, we compared data for two farm household subgroups that diverge substantially in their degree of reliance on farm 

income. The results support the reasonableness of the fi ndings. 

Citing extensive literature on household well-being, we argue on conceptual grounds that current consumption of goods and services provides an 

important complement to income and wealth in characterizing household 

economic well-being. Whereas income and wealth are important indicators 

of resources, current consumption is an indicator of current material standard 

of living. Further, consumption provides useful information about a household’s lifetime standard of living because, when households face temporary 

increases or decreases in income relative to long-term income expectations, 

they tend to smooth consumption relative to variable income in order to 

maintain a standard of living linked to their long-term income expectations. 

At an individual household level, there is not a close mapping between the 

income and consumption measures for farm households, compared with all 

U.S. households. Also, across the population, the consumption measure 

provides a different perspective than income and wealth on the distribution 

of well-being among farm households relative to all U.S. households. Farm 

households appear to have higher equivalent-income than all U.S. households 

at all income deciles but the lowest. But farm households, which are exposed 

to greater income volatility, have lower marginal propensities to consume from 

current income. The net effect is that the distribution of consumption appears 

to be similar for farm and all U.S. households. However, for farm households, 

the data suggest that consumption is higher at the low end of the distribution 

and lower at the high end of the distribution relative to all U.S. households. 

Analogously, using poverty rates as an indicator of disadvantage within the 

populations, the relative levels of disadvantage are reversed when we switch 

from an income-poverty rate to a consumption-poverty rate, calculated by 

comparing household consumption to the census poverty threshold employed 

in offi cial U.S. income poverty statistics. Whereas the income poverty rate 

is higher, the consumption poverty rate is lower for farm households relative 

to all U.S. households. The divergence in income- and consumption-poverty 

rates between farm and all U.S. households is even greater when we focus 

on households that operate farms with sales of $100,000 or more, which are 

more exposed to the income risks of self-employment. 
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References

Access Project (2007). 2007 Health Insurance Survey of Farm and Ranch 

Operators, Issue Brief No. 1, Sept., www.accessproject.org 

Buhmann, B., L. Rainwater, G. Schmauss, and T.M. Smeeding (1998). 

“Equivalence Scales, Well-Being, Inequality, and Poverty: Sensitivity 

Estimates Across Ten Countries Using the Luxembourg Income Study 

Database,” Review of Income and Wealth, Vol. 34:115-142.

Burkhauser, R.V., S. Feng, S. Jenkins, and J. Larrimore (2008). “Estimating 

Trends in U.S. Income Inequality Using the Current Population Survey: 

The Importance of Controlling for Censoring.” National Bureau of 

Economic Research Working Paper 14247.

Burkhauser, R.V., S. Feng, and S. Jenkins (2007). “Using the P90/10 Index 

to Measure U.S. Inequality Trends with Current Population Survey Data: 

A View from Inside the Census Bureau Vaults.” Institute for Social & 

Economic Research Working Paper 2007-147. Colchester: University of 

Essex. 

Carroll, Christopher D. (2001). “A Theory of the Consumption Function, 

With and Without Liquidity Constraints,” Journal of Economic 

Perspectives 15(3): 23-46. 

Carroll, Christopher D., and Miles S. Kimball (2007). “Precautionary Saving 

and Precautionary Wealth,” Palgrave Dictionary of Economics and 

Finance, 2nd Ed. 

Cutler, D., and L. Katz (1991). “Macroeconomic performance and the disadvantaged,” Brookings Papers on Economic Activity, 2. 

DeNavas-Walt, C., B.D. Proctor, and J. Smith (2007). Income, Poverty and 

Health Insurance Coverage in the United States: 2006, U.S. Census 

Bureau, Current Population Reports, P60-233.

DeJuan, Joseph, and J.J. Seater (2006). “A Simple Test of Friedman’s 

Permanent Income Hypothesis,” Economica 73:27-46. 

Federman, M., T.I. Garner, K. Short, W.B. Cutter IV, J. Kiely, D. Levine, D. 

McDough, and M. McMillen (1996). “What Does It Mean to be Poor in 

America?” Monthly Labor Review, 119(5): 3-17. 

Fernandez-Villaverde, J., and D. Krueger (2002). “Consumption Over the 

Life Cycle: Some Facts From the Consumer Expenditure Survey Data,” 

National Bureau of Economic Research Working Paper 9382.

Fisher, Jonathan D., and David S. Johnson (2006). “Consumption Mobility 

in the U.S.: Evidence From Two Panel Data Sets,” Topics in Economic 

Analysis and Policy, Brookings Economic Press, Vol. 16, issue 1.

Friedman, M. (1957). A Theory of the Consumption Function, Princeton 

University Press, Princeton, NJ. 
32

Farm Household Well-Being:Comparing Consumption- and Income-Based Measures / ERR-91

Economic Research Service / USDA

Hoppe, Robert, and David Banker (2006). Structure and Finance of U.S. 

Farms: 2005 Family Farm Report, EIB-12, Economic Research Service, 

USDA, May.

Hurd, M.D., D. McFadden, H. Chand, L. Gan, A. Merrill, and M. Roberts 

(1998). “Consumption and Savings Balances of the Elderly: Experimental 

Evidence on Survey Response Bias,” in D. Wise (ed.), Frontiers in the 

Economics of Aging, Chicago: University of Chicago Press.

Hurd, M.D., and S. Rohwedder (2006). “Economic Well-Being at Older 

Ages: Income and Consumption-Based Poverty Measures in the HRS,” 

National Bureau of Economic Research Working Paper 12680.

Johnson, D. (2004). “Measuring Consumption and Consumption Poverty: 

Possibilities and Issues.” Conference paper presented at “Reconsidering 

the Federal Poverty Measure, American Enterprise Institute, Washington, 

DC, Nov. 

Johnson, D., and S. Shipp (1999). “Inequality and the Business Cycle: A 

Consumption Viewpoint,” Empirical Economics, Vol. 24, issue 1. 

Johnson, D., T. Smeeding, and B. Torrey (2005). “Economic Inequality 

through the Prisms of Income and Consumption,” Monthly Labor Review, 

April.

Jolliffe, D. (2006). The Cost of Living and the Geographic Distribution of 

Poverty. ERR-26, Economic Research Service, USDA, Sept. 

Jones, Carol A., Hisham El-Osta, and Robert Green (2006). Economic WellBeing of Farm Households, Economic Brief #7, Economic Research 

Service, USDA, March. http://www.ers.usda.gov/Publications/EB7/

Jones, Carol Adaire, Timothy S. Parker, Mary Ahearn, Ashok K. Mishra, and 

Jayachandran N. Variyam (2009). Health Status and Health Care Access 

of Farm and Rural Populations, EIB-57, Economic Research Service, 

USDA, Aug.

Jorgenson, D. (1998). “Did We Lose the War on Poverty?” Journal of 

Economic Perspectives 12:1.

Kennickell, Arthur B. (2006). “Current and Undercurrents: Changes in the 

Distribution of Wealth, 1989-2004.” Federal Reserve Board. http://www.

federalreserve.gov/pubs/oss/oss2/papers/concentration.2004.5.pdf

Meyer, B.D., W.K.C. Mok, and J.X. Sullivan (2009). “The Under-Reporting 

of Transfers in Household Surveys: Its Nature and Consequences.” 

National Bureau of Economic Research Working Paper 15181. http://

www.nber.org/papers/w15181

Meyer, B.D., and J.X. Sullivan (2003). “Measuring the Well-Being of the 

Poor Using Income and Consumption,” Journal of Human Resources, 

XXVIII Supplement.
33

Farm Household Well-Being:Comparing Consumption- and Income-Based Measures / ERR-91

Economic Research Service / USDA

Meyer, B.D., and J.X. Sullivan (2009). “Five Decades of Consumption and 

Income Poverty,” National Bureau of Economic Research Working Paper 

14827.

Mishra, Ashok, Hisham S. El-Osta, Mitchell J. Morehart, James D Johnson, 

and Jeffrey W. Hopkins (2002). Income, Wealth and the Economic WellBeing of Farm Households, AER-812, Economic Research Service, 

USDA, July.

Mishra, Ashok, and Carmen L. Sandretto (2002). “Stability of Farm Income 

and the Role of Nonfarm Income in U.S. Agriculture,” Review of 

Agricultural Economics, Vol. 24, No. 1.

Rogers, J., and M. Gray (1994). “CE Data: Quintiles of Income Versus 

Quintiles of Outlays,” Monthly Labor Review 118(8): 32-37.

Ruggles, P. (1990). Drawing the Line, Washington, DC: Urban Institute 

Press.

Sablehaus, J., and J. Groen (2000). “Can Permanent Income Theory Explain 

Cross-Section Consumption Patterns?” Review of Economics and 

Statistics, 82(3):431-438.

Short, K., M. Shea, D. Johnson, and T. Garner (1998). “PovertyMeasurement Research Using the Consumer Expenditure Survey and 

the Survey of Income and Program Participation,” American Economic 

Review, 88(2), 352-356.

Slesnick, D. (2001). Consumption and Social Welfare, Cambridge: 

Cambridge University Press.

Slesnick, D. (1994). “Consumption, Needs, and Inequality,” International 

Economic Review, vol. 35, no. 3. 

USDA, Economic Research Service (1984). Economic Indicators of the 

Farm Sector: Income and Balance Sheet Statistics. ECIFS3-3, Sept.

Weinberg, D., C. Nelson, M. I. Roemer, and E.J. Welniak, Jr. (1999). 

“Fifty Years of U.S. Income Data From the Current Population Survey: 

Alternatives, Trends and Quality,” American Economic Review, vol. 89, 

no. 2.

Whittaker, J.B., and A. Effl and (2009). “Income Stabilization Through 

Government Payments: How Is Farm Household Consumption Affected?” 

Agricultural and Resource Economics Review 38/1:1-10.
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Appendix A: Data Sources 

and Analysis Samples

Agricultural Resource Management Survey (ARMS) 

USDA’s Agricultural Resource Management Survey (ARMS) provides 

annual observations of fi eld-level farm practices, the economics of the farm 

business, and the characteristics of the farm household for a nationally representative sample of all U.S. farms in the 48 contiguous States. The offi cial 

USDA defi nition of a “farm” is any place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, 

during the year. 

The survey data support estimation of farm business income and performance 

measures, farm sector income and value-added, production costs for crop and 

livestock enterprises, farm practices used in the production of crop and livestock commodities, and household characteristics of the principal farm operator, including demographic and fi nancial well-being measures. Continuous 

data series for household income and wealth measures exist from 1996, when 

the current format for data collection was introduced.

ARMS is a large multi-phase and multi-version survey, employing stratifi ed 

sampling procedures suited to collecting the different kinds of information.1

This analysis uses data from Phase III surveys, which collect information 

on farm income and expenditures, farm fi nancial transactions, and the farm 

operator household during the winter months immediately following the 

reference year. Several versions of the Phase III survey are distributed. One 

enumerated version (version 1), employing personal interviews with trained 

enumerators, covers farms of all types, and contains more in-depth questions than in other versions—including the household questions on living 

expenses needed for this analysis. Survey weights are developed to generate 

nationally representative estimates from version 1 data alone. In addition, 

typically two to three other personally enumerated versions are designed to 

capture detailed characteristics of specifi c commodity enterprise types; survey weights are developed to generate nationally representative estimates 

from these versions for the enterprise types surveyed. Finally, a short “core” 

version, which is distributed and returned by mail, supports State-level estimates for the 15 States with the highest values of farm production. Another 

set of weights provides nationally representative data from the pooled sample 

across all fi ve versions of the survey (the “full sample”). The systems of 

weights address sampling, nonresponse, and undercoverage (calibrating to 

independent USDA estimates).2

Analysis Samples

Full family farm sample: To report household income and wealth measures, we use data from a pooled sample of all fi ve questionnaires. Because 

we are interested in farm households, we restrict our analysis to “family 

farms,” those in which the majority ownership of the farm business is held 

by the operator and relatives of the operator. Most farms (96 percent in 

2006) are family farms. Most farms have only one operator. For multipleoperator farms, a principal operator is identifi ed during the annual process of 

1 The sample is screened for continued operation and commodity coverage 

in Phase I, conducted in the summer of 

the reference year. In the fall, randomly 

selected Phase I farms are surveyed in 

Phase II concerning their crop production practices and chemical use at the 

fi eld or production unit level. During 

the following winter, selected Phase I 

farms are surveyed in Phase III concerning business fi nances and operator 

characteristics.

2 For more information about the 

ARMS, see http://www.ers.usda.gov/

Data/ARMS/.
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collecting economic information from farm businesses.3 The unit of observation, then, is the household of the principal operator.

Expenditure/consumption analysis sample: To analyze consumption and 

expenditures, we use a sample constructed from questionnaire version 1, 

the only version in which detailed household expenditure data are elicited. 

Currently, USDA does not impute values of the living expense component 

variables. The set of variables is subject to substantial nonreporting, resulting 

in a net loss of 28 percent of the farm population. We also select for study 

two subgroups within the farm household population: farm operator households of farms with sales of $100,000 or more (“large”) and farm operator 

households of very small rural-residence farms (those where the principal 

operator indicates an occupation other than farming as his primary occupation, and whose farm has annual sales of $10,000 or less). 

To assess the implications of using the smaller version 1 sample with attrition due to missing data, we report in Appendix table A1 descriptive statistics 

for key demographic and economic variables for the expenditure/consumption analysis sample (N=4,683), the full version 1 sample (N=6,457), and the 

full sample across the fi ve versions of the survey (N=20,342). We fi nd that 

the values in the analysis sample generally were very similar to the larger 

samples. Among the demographic variables, the analysis-sample values of all 

variables—including operator age, household composition by age category, 

and education—were within +/- 5 percent of the full-sample values. 

Among the variables characterizing the distributions of farm household 

income and wealth, the only variable that was substantially different was 

median debt level. Since, on average, debt is a small fraction of assets, the 

difference is not refl ected in net wealth. 

Current Population Survey, Annual Social and 

Economic Supplement

The Annual Social and Economic Supplement (ASEC) of the Current 

Population Survey (CPS) is designed to provide timely and detailed estimates of income, poverty and health insurance coverage, and to measure 

change in those estimates at the national level. Conducted by the Bureau of 

the Census for the Bureau of Labor Statistics, the CPS ASEC is the offi cial 

source of the national poverty estimates calculated in accordance with the 

Offi ce of Management and Budget’s Statistical Policy Directive 14. (Though 

the Census Bureau also reports income and poverty estimates based on the 

American Community Survey, part of the 2010 Decennial Census Program, 

it recommends people use ASEC/CPS for national estimates because it provides more complete and thorough estimates of income and poverty.)

The sample is scientifi cally selected to represent the civilian noninstitutional 

population living in the U.S. The unit of observation is the household. About 

70,000 households are interviewed each year. 

Analysis sample: Because CPS collects data for a larger sample relative 

to CE, we use CPS to calculate estimates of well-being measures based 

on household money income for all U.S. households (tables 1 and 2). We 

also use it to benchmark the CE data, including the estimates of household 

3 About 40 percent of farms have 

more than one operator; however, for 

three-quarters of the farms with multiple operators, the farm is operated by 

a husband-wife team, so that both operators are part of the principal operator 

household on which we focus. About 

10 percent of family farms have other 

operator households associated with the 

farm, for which no data are collected.
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Appendix table A1

Comparison of ARMS analysis sample to ARMS total version 1 and ARMS versions 1-5 samples, 2006

Farm operator households 1 2 3

Analysis sample Full sample (version 1) Full sample (versions 1-5) 

Percent

Number of farm households 1,463,313 2,022,535 2,022,501

Sample size 4,683 6,457 20,342

Demographics

Age of operator 57 57 57

Average number in household - all ages 2.7 2.7 2.7

Children under 18 0.6 0.6 na

Persons 65 and over 0.5 0.5 na

Education - highest degree of operator Percent

High school 62.3% 66.6% 64.8%

College and beyond 26.0% 25.0% 25.0%

Economics 

Household income Dollars

Mean $75,080 $76,224 $77,654

Median $55,330 $55,696 $56,022

Percent

Wage/salary income share 53.6 50.5 49.8

Self-employment income share 22.5 24.8 25.4

Dollars

10th percentile $10,735 $10,151 $9,859

20th percentile $22,871 $23,310 $22,400

40th percentile $45,064 $45,930 $45,064

60th percentile $67,662 $67,370 $67,801

80th percentile $102,710 $104,349 $108,713

90th percentile $143,392 $144,565 $167,570

Ratio

80:20 4.5 4.5 4.9

90:10 13.4 14.2 17.0

Index

Gini coeffi cient 0.556 0.568 0.576

Percent

Negative household income 5.7 5.9 5.9

Poverty rate per person 13.8 13.5 14.4

Poverty rate per household 12.5 13.0 12.5

Household net worth

Dollars

Net worth, median $578,650 $587,111 $554,549

 Assets, median $629,900 $656,375 $602,750

 Debt, median $12,750 $23,400 $23,400

Index

Gini coeffi cient 0.511 0.515 0.529

Continued—
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income. For a comparison of descriptive statistics for the two samples, refer 

to the section on CE below. 

Survey of Consumer Finance (Federal Reserve Board)

The Survey of Consumer Finance (SCF), a triennial survey published since 

1989, is the major source of wealth estimates for the U.S. population. 

The SCF unit of analysis differs somewhat from that in ARMS, CPS, and 

CE. Most of the data in the survey are intended to represent the fi nancial 

characteristics of a subset of the household unit referred to as the “primary 

economic unit” (PEU). In brief, the PEU consists of an economically dominant single individual or couple (married or living as partners) in a household 

and all other individuals in the household who are fi nancially interdependent 

with that individual or couple. Typically, around 4,500 economic units are 

interviewed for the main portion of the survey. 

Analysis sample: This survey is the source of data for household wealth distributions for all U.S. households in table 2.

Consumer Expenditure Survey

The Consumer Expenditure Survey (CE) is a nationally representative sample 

conducted by the Bureau of Labor Statistics, designed to provide a continuous summary of the spending habits of U.S. households. Expenditure data are 

reported at the level of the consumer unit, which is defi ned as either a group of 

individuals who are related by blood or marriage, a single or fi nancially independent individual, or two or more persons who share resources. Interview data 

are collected from consumer units fi ve times over a 13-month period, every 3 

months over fi ve calendar quarters. In the fi rst interview, data on demographic 

characteristics for each member of the consumer unit age 14 and over and 

an inventory of major durable goods of the consumer unit are collected. In 

interviews 2-5, expenditure data for the consumer unit for the prior quarter are 

collected. Employment and income information are collected in interview 2 

Appendix table A1

Comparison of ARMS analysis sample to ARMS total version 1 and ARMS versions 1-5 samples, 2006—continued

Farm operator households 1 2 3

Analysis sample Full sample (version 1) Full sample (versions 1-5) 

Dollars

Household-owned autos

 Mean value $24,542 $25,455 na

Household dwelling

 Mean value, owned by farm $138,089 $143,052 $142,951

 Mean value, owned by household $192,914 $192,539 na

Percent

Share owned by farm 77.1 80.1 73.2

Share owned by household 20.4 18.0 26.8*

Share rented 2.4 1.9

Notes. ‘na’ means not available in survey versions other than version 1. * includes rental share as well.

Sources: USDA, Economic Research Service using Agricultural Resource Management Survey, 2006. 
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(which is carried over to interviews 3 and 4) and interview 5. (CE also includes 

a separate diary survey providing more detailed information on smaller or more 

frequent expenditures that are more diffi cult to recall.) In total, around 7,100 

households participated each quarter in 2006. 

Expenditures consist of the transaction costs, including excise and sales taxes, 

of goods and services acquired during the interview or recordkeeping period. 

Expenditure estimates include expenditures for gifts, but exclude purchases or 

portions of purchases directly assignable to business purposes. Also excluded 

Appendix table A2

Comparison of characteristics for CE and CPS, 2006

CE: 

all U.S. consumer units

CPS: 

all U.S. households

Number of households (1,000) 118,843 113,687

Sample size 73,629

Demographics

Age of reference person 49 49

Average number of persons in consumer unit: 

Total 2.5 2.5

Children under 18 0.6 0.7

Persons 65 and over 0.3 0.3

Percent

Black: * 12 12

Hispanic or Latino origin: * 11 11

Education:*

Highest level attained was:

Less than high school degree 13.0 14.4

High school 21.2 30.2

HS degree and some college 30.6 27.4

College grad and beyond 35.1 28.0

Economics:

Household income Dollars

Mean $60,533 $66,575 

Median $44,616 $48,054

Percent

Self-employment income share 6.0 5.3

Dollars

10th percentile $10,594 $12,000

20th percentile $18,333 $20,037 

40th percentile $35,044 $37,888 

60th percentile $56,153 $60,022 

80th percentile $88,687 $97,462 

90th percentile $122,707 $133,799 

Ratio

80:20 4.84 4.86

90:10 11.58 11.15

*Asked of reference person in CE, CPS.

Source: USDA, ERS using Current Expenditure Survey, 2006, and Current Population Survey 

ASEC, Feb.-April 2007 (for 2006 data).
39

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are periodic credit or installment payments on goods or services already 

acquired; however, interest applied to these balances is included in expenditures. The full cost of each purchase is recorded, even though full payment may 

not have been made at the date of purchase. CE elicits consumer-unit totals 

for multiple categories of income, using an open-ended format. If respondents 

indicate they do not know the exact amount, they are asked a followup question by a value-code elicitation format (the top code is $50,000 and up). 

Many articles have documented measurement error in the income measure 

reported in CE, which results in substantial underestimates of income, on 

average. More recently, the Consumer Expenditure Survey has implemented 

multiple imputation of income data, starting with the publication of the 2004 

tables. In multiple imputation, several estimates are made for the same consumer unit, and the average of these estimates is published. 

All U.S. household analysis sample: We use the individual interview data 

from the CE survey to report household expenditures and consumption 

measures for all U.S. households, and for comparisons of consumption and 

income within individual households. 

To benchmark the CE sample, we compare CE and CPS estimates of key 

variables in Appendix table A2. In particular, we are interested in the comparison of the income distribution. We observe in Appendix table A2 that the 

demographic and family composition characteristics have similar values in 

the CPS and CE samples. However, at each of the decile cutpoints, the values 

of income are underestimated between 6 and 12 percent, with the greatest 

underestimate occurring at the 10th percentile.
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Economic Research Service / USDA

Appendix B: Constructing Consumption 

and Expenditure Measures in the 

Consumer Expenditure Survey (CE) and the 

Agricultural Resource Management Survey 

(ARMS)

Appendix table B-1 illustrates the mapping of the CE expenditure categories 

into the common major categories used in the parallel consumption measures 

we calculate for ARMS and CE data. Column 2 identifi es the categories of 

ARMS variables. To make transparent the mapping between ARMS and CE 

categories, we identify in column 3 the subcategories of items in CE refl ected 

in each ARMS variable (as well as in variables calculated for CE data 

designed to be comparable). 

(A table with estimates of the detailed subcategories of the expenditure and 

consumption measures for the two populations is available from the authors.)

We make parallel adjustments to expenditure data in CE and ARMS in order 

to calculate consumption measures that are as consistent as possible using the 

two surveys. Three components merit particular attention. Here, we explain 

the procedures for calculating service fl ows for housing and vehicles, and the 

composition of the “all else” category in the CE and ARMS measures.

Expenditures on “All else”

ARMS: The survey question used to measure “all else” is at the end of the 

list and asks for “all other family living expenses, such as clothing, and personal care products and services; house furnishings and equipment, education 

and child (or adult) care, entertainment (hobbies, recreation, and vacations).” 

CE: The CE categories that are combined into the “all else” category for the 

farm and all U.S. household consumption measures are shelter (other lodging); household furnishings and equipment; apparel; entertainment; personal 

care products and services; reading, education; tobacco products, smoking 

supplies; alcohol; and miscellaneous. 

Housing (“shelter”) service fl ows

ARMS: To calculate housing shelter services for farm households from 

ARMS data, we apply the BEA rent-to-value ratios used in the USDA Farm 

Income Sector Accounts to account for the asset value of the household residence. The BEA rent-to-value ratios are conditional on the value of residence 

and cover imputed rent only; no expenses are deducted or added, such as 

utilities.4 We calculate values for households living in a residence owned by 

the farm as well as for households that own their residence. 

For 2006, ARMS did not collect expenditure outlays for mortgages and related 

expenses for owned houses or for purchase of vehicles, so we imputed values 

based on 2005 data. For housing, the imputations for mortgage and related 

expenditures were needed for the 20 percent of the sample that reported 

4 Source: Denise McBride, BEA, 

personal communication, June 18, 

2008..
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Farm Household Well-Being:Comparing Consumption- and Income-Based Measures / ERR-91

Economic Research Service / USDA

Appendix table B1

Mapping of expenditure and consumption components between CE and ARMS, 2006

ARMS ARMS CE CE 

Category ARMS variable 

subcategory CE subcategory Expenditures Consumption Expenditures Consumption 

Food Food Food yes yes yes yes

Housing Shelter Shelter

- Owned dwellings: 

-- Principal payments on 

mortgage Principal payments on mortgage* yes (imputed) no yes* no

-- Other mortgage-related 

expenses:

yes (imputed) no yes no

Mortgage interest and charges;

Property taxes; 

Maintenance, repairs, insurance, other 

--Shelter annual service 

fl ow Rental value of owned home (Self-report) no yes (BEA rental factors) no yes (self-report of rental value)

-Rented dwellings yes yes yes yes 

Operating expenses yes yes yes yes 

Utilities, fuels, and public services (electricity, 

gas, water, telephone, etc)

Household operations (personal services, other 

household expenses)

Housekeeping supplies

Transport Vehicle services

Owned vehicles

Net outlays Vehicle purchases (net outlay) yes (imputed) no yes no

Vehicle annual service fl ow n/a no

yes (imputed 

- user cost of 

capital) 

no

yes (imputed 

- user cost of 

capital) 

Leased vehicles and public 

transportation yes yes yes yes

Other vehicle expenses: vehicle rental, leasing, 

licensing, other 

Public transportation 

Operating expenses yes yes yes yes

Gas and motor oil

Other vehicle expenses: fi nance charges, maintenance and repairs, vehicle insurance)

Health care

Health and dental insurance 

(paid by household) Health insurance (paid by hh) yes yes yes yes

Out-of-pocket household 

medical expenditures yes yes yes yes

Medical services

Drugs

Medical supplies

All other yes yes yes yes

Shelter: Other lodging

Housing: Furnishing/equipment(appliances, etc) 

Apparel

Entertainment 

Personal care products and services

Reading

Education

Tobacco products, smoking supplies

Miscellaneous

Alcohol

Personal insurance and retirement plans yes no yes no

Life and other personal insurance

Pensions and Social Security 

Contributions (outside of household) Cash contributions yes no yes no

Home consumption n/a no yes no na

*CE does not consider mortgage principal as an expenditure (but rather as a change in household assets).
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Economic Research Service / USDA

owning their residence through the household rather than through the farm 

business. 

CE: To calculate housing shelter services for all U.S. households from CE 

data, we follow standard practice and use the self-reported rental equivalence value obtained from the consumer unit. Consumer units who own their 

own home are asked, “If someone were to rent your home today, how much 

do you think it would rent for monthly, unfurnished and without utilities?” 

For respondents who do not know the rental equivalence of their home, CE 

reported an imputed value.

Transportation service fl ows

CE: To calculate transportation services for all U.S. households, we calculate 

the user cost of capital based on Slesnick (1994, 2001) and others. In their 

formulation, the service fl ow in a given year from an asset = (r+d), where r 

= interest rate and d = depreciation rate. Starting with the original purchase 

price reported in CE, their formula is: St = (r+d)(1-d)s * P0, where P0 is the 

original purchase price and s = age of the vehicle. We assume, as Slesnick 

does, that r =.05 and d =.10. 

ARMS: To calculate transportation services for farm households, we employ 

the same approach as with CE data. Since ARMS data include the current 

asset value, the calculation simplifi es to .15*household-owned current asset 

value.