Assessing Household Wellbeing

Comparing Consumption

- and Income

-based Me

for Farm and All U.S. Households 

using USDA ARMS and BLS CE Surveys

Carol Adaire Jones

using USDA ARMS and BLS CE Surveys

Carol Adaire Jones

Economic Research Service, USDA

The views expressed are those of the author(s) and should not be attributed to ERS or U

ERS

ECONOMIC RESEARCH SERVICE
Road map Road map

• Project experience using CE data Project experience using CE data

– Research context and questions– Findings, products to date Findings, products to date– Future plans

• Challenges and recommendations Challenges and recommendations

– Project dimension context: time, geogr

demography

– Challenges in using CE data – Desireable sample and data features
Research context Research context

• ERS indicators and research progra

ERS indicators and research progra

farm household well-being

– Major data resource: Agricultural Reso

Major data resource: Agricultural Reso

Management Survey 

– Historical focus: income wealth indicat

Historical focus: income, wealth indicat

• Recent projects have expanded focu

include consumption and health include consumption and health. 
Issue: Measuring relative well-b

of farm and all U.S. househo

•

Question: Does relative well-bein

g g differ usin

g

consumption and income measures?

– Money income: measure of resources

• Most commonly used in developed countries

– Consumption: measure of standard of living

• Due to income smoothing to maintain standard of l

Due to income smoothing to maintain standard of l

time, provides a better indicator of lifetime standard 

• Hypothesis: they do differ, because past researc

indicates divergence greatest where: indicates divergence greatest where:

– Substantial share of resources is from other than mon

and/or 

– Income is highly variable
Findings

• Use of consumption measure, rather than 

expenditure proxy makes a difference foexpenditure proxy, makes

a difference fo

hh: housing measures differ substantially

• Income and consumption well-bein

g mea

tell different stories about relative well-befarm and all U.S. households:

– Comparing univariate distributions for two po

Comparing univariate distributions for two po

• Income: farm households are better off (except at f

based on income, though income is more variable

• Consumption: farm household well-being looks com

– Comparing bivariate distributions for individua

• Income, a measure of household resources, is a le

proxy for standard of living for individual farm hous

– Particularly those that rely more heavily on farm inc

Particularly those that rely more heavily on farm inc
Average consumption levels, unlike average expenditure

comparable among farm and all U S households in 2comparable among farm and all

U.S. households in 2

$60,000

$

$40 000$50,000

All Con

$37,288

$42,368

$47,979

$41,852

$30,000$40,000 Con

InsHeaTra

$ ,

$10,000$20,000 Hou

Foo

$0

Farm All U.S. Farm All U.S. 

Expenditures Consumption

Source: USDA, Economic Research Service using Agricultural Resource Management Survey 2006Bureau of Labor Statistics’ Consumer Expenditure Survey, 2006.
In 2006, household incomes were higher for farm ho

relative to all U.S. households, at all deciles except 

$80 000

Per-person equivalent-income

$60,000$80,000

All U.S. households All farm households

$40,000$20,000

$0

10 20 30 40 50 60 70 80 

Percentiles of per-person equivalent-income

Source: USDA, Economic Research Service and National Agricultural Statistics Service’s Agricultural Resource ManagBureau of Labor Statistics’ Consumer Expenditure Survey, 2006.
In 2006, consumption levels were comp

for farm and all U S households for farm and all

U.S. households

Per-person equivalent-consumption

$60,000

$80,000

All U.S. households All farm households

$40,000

,

$20,000

$0

10 20 30 40 50 60 70 80 

Percentiles of per-person equivalent-consumption

Source: USDA, Economic Research Service and National Agricultural Statistics Service’s Agricultural Resource Managemand Bureau of Labor Statistics’ Consumer Expenditure Survey, 2006.
Two-way distributions of household well-be

Income is a less effective 

py p rox

y for consum

pt

farm households, 2006

F t h h ld Farm opera

tor 

house

h

old

s All U S h h ld All

U.S. house

h

old

s

Y-eq Consumption - eq Y-eq Consumpti

Quin

- 20 40 60 80 100 Quin 20 40 60 

tiles

20 40 60 80 100 Quin

-

tiles

20 40 60 

20 38 23 12 14 13 20 57 21 10 40 28 22 27 13 10 40 27 31 22 60 18 26 22 23 10 60 12 28 29 80 7 17 25 23 28 80 3 16 27 

100 8 11 15 27 38 100 1 4 12 

Note: Values in the cells are row percents, and sum to 100% across the row.Source: USDA, Economic Research Service and National Agricultural Statistics Service’s Agricultural Resource Managemand Bureau of Labor Statistics’ Consumer Expenditure Survey, 2006.
Outputs to date to date

• Presentations: Agricultural and Applied Agricultural and Applied

Economics Association 2009 annual mee

• Publications: 

– Jones, Carol Adaire, Daniel Milkove, and Lau

Paszkiewicz, Measuring Farm Household We

C i C ti d I M Comparing Consumption and Income Measu

ERR-91, U.S. Dept. of Agri., Econ. Res. Serv

http://www.ers.usda.gov/Publications/ERR91/

– Data Feature: “Measures of Farm Household 

Being Tell Different Stories”, Amber Waves, 3(ERS’ magazine for non-specialist readers.) http://www.ers.usda.gov/AmberWaves/March10/DataFeature/
Future goals Future goals

• Report consumption measure estima

Report consumption measure estima

for subsequent years – comparing faall U.S. households

– International interest in developing stat

standards for farm hh consumption rep

• Conduct further statistical analysis• Incorporate TAXSIM to calculate 

disposable income
International interest in farm 

h h ld ti house

h

old consumption mea

• W

yy p e Cit

y Grou

p On Statistics on Rural Develo

pm

Agriculture Household Income 

– Under aegis of U.N. Statistics Division, a group o

international ex

p, y erts, mainl

y from national statisti

agencies, focused on improving and expediting international standards development for statisticamethodologies. [http://unstats.un.org/unsd/methods/citygroup

• The Global Strategy to Improve Agricultural and 

Statistics, developed under the auspices of the U.Statistical Commission. 

– http://wiki.asfoc.ibge.gov.br/Default.aspx?AspxAutoDetectCookieSu
Experience with CE data

• CE Interview Survey micro data files CE Interview Survey micro data files

• Geography/demography dimensions

– R t d lt i th ti l l l Reported results in the national level, 

– plus created a farm household sub-sam

compare against ARMS farm househocompare against ARMS farm househo(though CE sample diverged from ARMS sample on key characteristics).

• Time period: CY 2006
Challenges in using CE data Challenges in using CE data

• Sample attrition and weighting Sample attrition and weighting: W

: W

are provided on a quarterly basis. 

– Given sample attrition the weights do 

Given sample attrition, the weights do 

generate a nationally representative safor CUs with com

pp ( lete 

panel data 

(acro

quarterly interviews). 
Challenges in using CE data Challenges in using CE data

• Calculation of standard errors: Calculation of standard errors: Fo

analysis pooling all available quarter

observations standard errors of annobservations, standard errors of ann

expenditure estimates are calculated 

treating all observations as independtreating all observations as independ
Desireable data features Desireable data features

• Enable calculations of annual (12 Enable calculations of annual (12

-m

consumption expenditures for each 

• Provide current value of each vehicl

Provide current value of each vehicl

Q1 interview, as for housing)

• R t di bl i Repor

t disposable income compone

for example, calculated using TAXS

• Provide expenditures, incomes, asse

and liabilities for the same time perio