0 

Building a Consumption Poverty Measure: Initial Results Following 

Recommendations of a Federal Interagency Working Group

Grayson Armstrong, Caleb Cho, Thesia I. Garner, Brett Matsumoto, Juan Munoz, & Jake Schild

March 1, 2022

Affiliation and Address for all authors:

Bureau of Labor Statistics

2 Massachusetts Ave NE

Washington, DC 20212

Email Addresses:

Contact Author: Thesia I. Garner, garner.thesia@bls.gov

Other Authors: Grayson Armstrong, Armstrong.Grayson@bls.gov; Caleb Cho, Cho.Caleb@bls.gov, Brett 

Matsumoto, Matsumoto.Brett@bls.gov ; Jake Schild, Schild.Jake@bls.gov; Juan Munoz, 

Munoz.Juan@bls.gov 

JEL Codes D12, I32

Key Words: consumption, poverty measurement, U.S. Consumer Expenditure Surveys 

Abstract 

Consumption is a well-being measure that is determined by a combination of resources (e.g., income, inkind benefits, assets, debt, time) available households, their circumstances, and their preferences. In 

this study, we derive consumption poverty statistics using a consumption measure that includes the 

flow of services from owner occupied housing and vehicles and in-kind transfers. The base data are from 

the U.S. Consumer Expenditure Survey Interview from 2015 through 2020. The consumption poverty 

rate (using an absolute threshold anchored to the 2015 relative consumption poverty rate) declines 

from 16.8 percent in 2015 to 11.5 percent in 2020.

_____________________________________________________________________________________

Note: Public access to the computer code used to produce the results presented in this paper is available at: 

https://github.com/tigarner/Consumption-Measurement-and-Poverty

Acknowledgements: This research was presented during a session at the ASSA-AEA Annual Meetings; the paper is 

forthcoming in the American Economics Association (AEA) Papers and Proceedings 2022 volume. We would like to 

thank Dominic Smith, who provided guidance in the production of the vehicle flow of services; Josh Klick for his 

assistance with the Chain-CPI-U; Bob Martin, who provided assistance in developing the rent imputation modeling; 

Adam Safir, Scott Curtin, and Brett Creech, who provided support throughout the project; and Leslie Hodges, 

Courtney Paolicelli, and Saied Toossi from USDA, who provided amazing guidance regarding the NSLP and WIC. 

Discussions with Liana Fox (Census Bureau), Kevin Corinth (University of Chicago), Jim Sullivan (University of Notre 

Dame), and Richard Burkhauser (Cornell, emeritus) have greatly improved this research. We also appreciate the 

discussion and comments from those who attended the BLS Consumption Symposium in September 2021 and 

FESAC meeting in December 2021.
1

In this study, we derive consumption-based poverty statistics, and for comparison, also 

poverty statistics for expenditures and income. This research builds on the Bureau of Labor 

Statistics (BLS) initiative to produce a consumption measure of well-being at the consumer unit 

level, and recommendations from the Interagency Technical Working Group (ITWG) on 

Evaluating Alternative Measures of Poverty.1 We begin to implement the ITWG 

recommendations by producing a consumption measure that includes the flow of services from 

owner occupied housing and the stock of vehicles owned, as well as public in-kind transfers.2

Poverty statistics for 2015-2020 are presented. The primary data are from the U.S. Consumer 

Expenditure Survey, Interview component. 

Consumption is a well-being measure that is determined by a combination of resources 

(e.g., income, assets, debt, time) available to individuals, their circumstances, and their 

preferences (see, Jappelli and Pistaferri 2017). It can be viewed as a variable reflecting what has 

been achieved. In the standard economic model, individual utility is a function of consumption. 

Given this direct tie to utility, some consider consumption to be a better unidimensional 

measure of wellbeing as compared to income. Various consumption measures are in use for the 

study of poverty (e.g., Meyer and Sullivan 2012) and inequality (e.g., Fisher, Johnson, and 

Smeeding 2015).

Estimates of consumption can be derived from expenditures for most categories of 

goods and services; however, expenditures alone are not sufficient. The value of the in-kind 

1 Additional results and updates for this research project will be posted at https://www.bls.gov/cex/consumptionresearch.htm. 2 See the Appendix A for the list of recommendations from the ITWG related to creating a comprehensive measure 

of consumption and a discussion of how the measures in this paper begin to implement these recommendations.
2

benefits from the government and private sector (e.g., employers), the flow of services from 

owner-occupied housing and owned vehicles, and the value of home production for own 

consumption should be counted as well. Finally, some types of expenditures like education and 

healthcare may be better thought of as investments rather than providing current 

consumption. In our preliminary measure of consumption, home production, education, and 

healthcare are not included but the other components of consumption are.

When using our most comprehensive consumption measure and relative poverty 

thresholds, consumption poverty is 16.8 percent in 2015 and falls to 14.2 percent in 2020. This 

contrasts with relative income poverty which is 22.5 percent in 2015 and remains at 22.5

percent in 2020. We also consider absolute poverty measures. For these measures, we anchor 

the thresholds for each measure so that the poverty rates in 2015 are equal to the relative 

consumption poverty rate in 2015, and update the thresholds using the Chained CPI-U. When 

using this method, income poverty falls from the anchor rate of 16.8 percent to 13.6 percent, 

while consumption poverty falls to 11.5 percent. Relative to the entire U.S. population, a 

person is more likely to be at risk of consumption poverty (below 60 percent of the median of 

adult equivalized consumption) if they are living in consumer units where the reference person 

is Black non-Hispanic, Hispanic, has a lower level of education, or has children.

I. Data and Methods

In this section we provide a brief description of the data and the construction of our 

consumption measure.

3 The primary data source for the measure is the U. S. Consumer 

3 For additional details regarding the CE Survey, the measures, and thresholds, see Appendix B.
3

Expenditure Survey (CE) Interview component. Using the restricted-use microdata, we 

construct total quarterly expenditures (denoted tot_exp) at the consumer unit level.4 We 

construct several consumption measures, but for this paper we only present the most 

comprehensive measure which includes the flow of services from owner occupied housing and 

the stock of vehicles owned, and public in-kind benefits. Public in-kind benefits include those 

for rental assistance, Low Income Home Energy Assistance Program (LIHEAP), the National 

School Lunch Program (NSLP), and the Supplementary Nutrition Program for Women, Infants, 

and Children (WIC). Supplemental Nutritional Assistance Program (SNAP) benefits are implicitly 

already counted in food expenditures as the assumption is that SNAP benefits are used first 

before income or credit. Excluded are expenditures for the following: those associated with 

owning a primary residence or vacation home; the purchase and financing of vehicles; cash 

contributions; life, endowment, annuities, and other personal insurance; retirement, pensions, 

and Social Security; healthcare; and education. For comparison, we also construct an income 

measure defined as after tax and transfer income plus the value of the same public in-kind 

benefit programs that enter the consumption measure.

Our initial measures exclude the value of home production. While home production 

would ideally be included in a comprehensive measure of consumption, we are still conducting 

4 A consumer unit comprises either: (1) all members of a particular household who are related by blood, marriage, 

adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a 

roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is 

financially independent; or (3) two or more persons living together who use their income to make joint 

expenditure decisions. Financial independence is determined by the three major expense categories: Housing, 

food, and other living expenses. To be considered financially independent, at least two of the three major expense 

categories have to be provided entirely, or in part, by the respondent. (https://stats.bls.gov/cex/csxgloss.htm )
4

research on the best way to incorporate home production into the measure.5 Estimating the 

value of home production requires data on time use. Time use data is not collected in the CE, so 

the CE must be linked with a different data source to impute a value for home production.6

In the Figures we limit our results to those based on the purely relative thresholds, and 

absolute thresholds that results when poverty rates for all our measures (consumption, 

expenditures, and income) are anchored to the same initial poverty rate.7 The relative poverty

thresholds are defined as 60 percent of the national population weighted equivalized median 

measure value. The poverty rate is defined as the percentage of people who are this threshold. 

The absolute thresholds are based on anchoring the threshold for each measure so that each of 

the resulting poverty rates is equal to the relative consumption poverty rate for 2015 (16.8

percent). Each of consumption, expenditures, and income thresholds, associated with this 

initial 16.8 percent rate in 2015, are updated for later years using the all items chained CPI-U.

For this analysis, adult equivalized consumption, expenditures, and income are produced 

for each consumer unit. Consumer unit level values are converted to equivalized values using a

three-parameter equivalence scale.8 It is these adult equivalence values, when weighted by the 

5 In September 2021, the BLS contracted with an outside vendor to investigate options to use available data to 

produce a consumption measure that can be incorporated with CE expenditures data at the consumer unit level. 

Results of this study are expected by the end of September 2022.

6 A similar challenge arises in incorporating home production into measures of household income (Frazis and 

Stewart 2011).

7 While anchoring to the initial consumption poverty rate is useful for showing changes over time between 

different measures, the preferred approach in much of the literature for constructing absolute thresholds is to 

anchor to an initial poverty threshold (rather than an initial rate). This approach is used so “that different measures 

do not diverge simply because of differing changes at different points in the distribution of resources (Meyer and 

Sullivan 2012, p. 143).” 8 This scale was developed by Betson (1996) and used in several BLS and Census Bureau studies (e.g., Fox and 

Burns 2021, Garner et al. 2016).
5

population and ranked from lowest to highest allow us to derive each of the relative thresholds 

and the absolute thresholds anchored to the 2015 consumption poverty rate.

II. Results

In this section, we present the poverty results for the different measures discussed in 

the previous section. For exposition purposes, we have converted quarterly adult equivalized

consumption, expenditures, and income for all consumer units to annualized values for 

consumer units with two adults and two children. 

Figure 1 shows the median annualized real consumption, expenditures, and after-tax

income with in-kind benefits at the equivalized consumer unit level for 2015 to 2020. Median 

expenditures are less than median after-tax income. Median expenditures and consumption 

have similar trends over this period and show less of an increase than median after-tax income. 

Annualized real median after-tax income increases by 13.0 percent from 2015 to 2020, while 

median consumption increased by 6.7 percent over the same period. The year 2020 is notable 

as it reflects the impacts of the COVID-19 pandemic and the associated recession. In 2020, 

median after-tax income increased while median expenditures and consumption fell. It is 

notable that after-tax income plus the value of in-kind benefits rose during the recession.9 The 

2020 CE annual report notes that the decline in expenditures is due to the decline in certain 

type of expenditures during the pandemic such as transportation, food away from home, and 

9 Real post-tax median (non-equivalized) household income also increased in the CPS-ASEC in 2020 (Shrider, et al 

2021). 
6

apparel and services (BLS 2021). These declines were only partially offset by increases in other 

categories such as food at home and housing.10

Figure 1: Annualized Medians in Real 2015 Dollars for All Consumers Units Equivalized to 2 Adults+2 Children CUs

Note: The Chained CPI-U is used to calculate real 2015 dollars.

Table 1 shows, for 2015, the demographic characteristics of the entire U.S. population 

compared to those in poverty, defined using after tax income with in-kind benefits and 

consumption. The demographic characteristics for the U.S. population are based on the full CE 

sample; the CE sample, when weighted, is designed to be nationally representative. All statistics 

are for people as opposed to consumer units. Both black non-Hispanics and Hispanics 

constitute a much larger percentage of those in poverty compared to their representation in 

the U.S. population.11 People living in consumer units in which the reference person has at 

most a high school education are more likely to be poor than as represented in the U.S. 

population. Those living in consumer units with children are more likely to be consumption 

10 Incorporating home production, which we plan to do in future versions of the consumption measure, is likely to 

be important for understanding consumption dynamics during COVID-19 as households substituted to home 

production for food and childcare.

11 It should be noted, standard errors for the demographic characteristics have not yet been produced. Thus, no 

claims can be made about the statistical significance of the difference between the U.S. population and those in 

poverty, or between income and consumption poverty. 

 $40,000.00

 $45,000.00

 $50,000.00

 $55,000.00

 $60,000.00

 $65,000.00

2015 2016 2017 2018 2019 2020

After tax income with in-kind benefits Tot_exp Consumption
7

poor compared to the U.S. population; and those living in consumer units with children are 

more likely to be consumption poor as opposed to income poor. The income poor are most 

likely to live in consumer units with no earners, while those who are consumption poor are 

most likely to live in consumer units with a combination of earners (reference person, spouse, 

others). People who live in single mother consumer units are more likely to be income poor as 

opposed to consumption poor. 

Table 1. Characteristics of All People Compared to Those Living in Consumer Units Who are Poor with Poverty Rate Anchored to 

2015 Consumption Rate: 2015Q2-2016Q1

Characteristic U.S. 

Population

Below 

Consumption 

Threshold

Below After-Tax 

Income with In-kind 

Benefits Threshold

Below Both 

Consumption and 

Income 

Thresholds

Race/Ethnicity of Reference Person

White Non-Hispanic 64.7% 47.9% 49.6% 45.9%

Black Non-Hispanic 12.5% 20.9% 19.4% 21.7%

Hispanic 16.3% 25.5% 24.2% 26.8%

Other 6.5% 5.7% 6.9% 5.6%

Education of Reference Person

Less than High School Graduate 13.0% 31.6% 28.4% 37.2%

High School Graduate 23.4% 32.2% 29.3% 30.8%

Some College 21.6% 21.7% 23.2% 20.9%

Associate Degree or Higher 42.0% 14.5% 19.1% 11.0%

Consumer Unit Composition based on Marital Status

Single Mother Consumer Units 5.8% 11.4% 13.4% 14.6%

Married Couple Consumer Units with Others 44.0% 42.4% 30.0% 32.5%

Single Person Consumer Units 11.8% 11.6% 20.3% 16.5%

Married Couple Consumers Units with No 

Others 17.8% 4.7% 8.8% 4.3%

Other Consumer Units 20.6% 30.0% 27.5% 32.1%

Whether Consumer Unit Has Members in Age Group

0-17 Years 51.2% 64.6% 53.5% 62.3%

18-64 Years 89.3% 94.4% 90.2% 94.5%

Greater than 64 21.7% 16.9% 21.0% 15.2%

Consumer Unit Earner Composition

Reference Person Only 20.9% 24.4% 28.9% 28.3%

Reference Person and Spouse Only 26.2% 10.4% 5.7% 4.2%

Spouse Only 7.1% 6.9% 8.1% 8.1%

Consumer Units with Other Earners 31.2% 37.8% 22.8% 26.1%

No Earners 14.7% 20.6% 34.5% 33.3%

Notes: All results are person weighted (family size times CU weight). Full Sample N=25,797 unweighted consumer units.
8

Figure 2 shows the relative poverty rates based on consumption, expenditures, and 

after-tax income including in-kind benefits from 2015 to 2020. In 2015, the after-tax income 

poverty rate (22.5 percent) is substantially higher than the expenditure and the consumption 

poverty rates. From 2015 to 2020, the poverty rates for expenditures and consumption 

declined (2.3 and 2.6 percentage points, respectively) while the after-tax income poverty rate 

was unchanged. 

Figure 2: Relative Poverty Rates by Measure: 2015-2020

Note: Relative poverty thresholds are calculated at 60% of the median value for each measure.

Figure 3 shows the poverty rates based on consumption, expenditures, and after-tax 

income with in-kind benefits from 2015 to 2020 based on the absolute thresholds that result 

from anchoring the expenditures and income poverty rates to the 2015 poverty rate for 

consumption (16.8 percent in 2015). All the poverty rates show a substantial decline over this 

period. The consumption poverty rate has the largest decline over this period, 5.3 percentage 

points, and reaches 11.5 percent in 2020. The after-tax income with in-kind benefits poverty 

rate declines by less over the period, falling to 13.6 percent in 2020 for a drop of 3.2 percentage 

points. 

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

22.0%

24.0%

26.0%

2015 2016 2017 2018 2019 2020

After tax income with in-kind benefits Tot_exp Consumption
9

Figure 3: Absolute Poverty Rates by Measure: 2015-2020

Note: All thresholds are anchored to 2015 relative consumption poverty rate.

III. Summary and Conclusions

In this paper, we present results from a preliminary measure of total consumption. Although 

broader and more in line with the theoretical measurement objectives than consumption 

measures based only on less comprehensive measures, there are other areas that still need to 

be added but require additional research before they can be incorporated into the measure. 

One area that will be included in future versions is the value of home production. Another area

of consideration is the treatment of medical care and health insurance (often referred to 

together as healthcare). Whether healthcare should be included in a measure of consumption is 

controversial, and in the future, we plan to have versions with and without healthcare.12 Finally, 

there are some categories of expenditure that are not covered by the CE Interview Survey. So, 

in future versions, we plan to integrate data from the CE Diary to capture expenditures missing 

from the Interview. 

12 The ITWG recommended creating versions with and without healthcare, where the version with healthcare 

could reflect something less than the full value for some households.

10.0%

11.0%

12.0%

13.0%

14.0%

15.0%

16.0%

17.0%

18.0%

2015 2016 2017 2018 2019 2020

After tax income with in-kind benefits Tot_exp Consumption
10

References

Betson, David. 1996. “Is Everything Relative? The Role of Equivalence Scales in Poverty 

Measurement,” U.S. Census Bureau Poverty Measurement Working Paper.

Bureau of Labor Statistics (BLS). 2021. “Consumer Expenditures in 2020”. BLS Report 1096. 

https://www.bls.gov/opub/reports/consumer-expenditures/2020/pdf/home.pdf. 

Accessed on 2022-01-11.

--- 2014-2020. Consumer Expenditure Survey Interview Component Microdata. 

Fisher, Jonathan, David S. Johnson, and Timothy M. Smeeding. 2015. “Inequality of income and 

consumption in the U.S.: Measuring the trends in inequality from 1984 to 2011 for the 

same individuals.” Review of Income and Wealth, 61(4), 630-650.

Fox, Liana E., and Kalee Burns. 2021. “The Supplemental Poverty Measure: 2020.” U.S. Census 

Bureau, Current Population Reports, P60-275.

Frazis, Harley, and Jay Stewart. 2011. “How does household production affect measured 

income inequality?” Journal of Population Economics. 24. 3-22.

Garner, Thesia I., Marisa Gudrais, and Kathleen Short. 2016. “Supplemental Poverty Measure 

Thresholds and Noncash Benefits,” presented at The Supplemental Poverty Measure 

Workshop, Brooking Institution, Washington, DC. https://www.bls.gov/pir/spm/smpthresholds-and-noncash-benefits-brookings-paper-4-16.pdf. Accessed 2022-01-11.

Interagency Technical Working Group (ITWG). 2021. “Final Report of the of the Interagency 

Technical Working Group on Evaluating Alternative Measures of Poverty.”

https://www.bls.gov/evaluation/final-report-of-the-interagency-technical-workinggroup-on-evaluating-alternative-measures-of-poverty.pdf. Accessed on 2022-01-11. 

Jappelli, Tullio, and Luigi Pistaferri. 2017. Economics of Consumption: Theory and Evidence. 

Oxford University Press. New York, NY.

Meyer, Bruce D., and James X. Sullivan. 2012. “Winning the War: Poverty from the Great 

Society to the Great Recession.” Brookings Papers on Economic Activity, Fall, 133-183.

Shrider, Emily A., Melissa Kollar, Frances Chen, and Jessica Semega. 2021. “Income and Poverty 

in the United States: 2020.” U.S. Census Bureau, Current Population Reports, P60-273.
11

Appendix A. ITWG Recommendations

The ITWG, in their final report, made specific recommendations regarding the development of a 

measure of consumption to be used for poverty statistics.13 While the working group referred 

to consumption as a resource measure, it is our position that consumption is an outcome, or 

well-being, measure as opposed to a resource measure. That aside, in this section we 

summarize the primary recommendations regarding the development of a consumption 

measure, equivalence scales in developing a poverty threshold, and the role of the BLS in 

particular. 

The recommendations can be divided into those that are broader in scope and those that focus 

on the specifics of consumption poverty measurement. Broader recommendations include that 

the BLS be the federal government agency to develop a measure of consumption, which will be 

used to produce poverty statistics, and that the BLS engage with stakeholders and experts 

throughout the development of the measure. Specific recommendations regarding the 

construction of the measure include the following: (1) two new sets of research measures of 

consumption-based resources be produced, one that includes a value of health insurance and 

one that does not; (2) education not be considered part of consumption because education is 

generally considered an investment in human capital; (3) service flows from owner-occupied 

shelter and the value of the service flows from owned vehicles be included in consumption; (4) 

administrative data be used to supplement or replace survey collected data, but when such 

data are not available, regression-based modeling should be used to improve the quality of 

estimates of expenditures and in-kind program participation; (5) in the development of a 

poverty threshold, an equivalence scale be applied that accounts for the potentially differing 

needs of adults and children and economies of scale; and (6) that the CE Interview be used as 

the source of data for this work. See below for a list of the recommendations related to 

consumption and the BLS.

In our study, we implement several of these recommendations. First, with the presentation of 

results from this study, we begin our engagement with stakeholders and experts on poverty 

measurement. Second, we use the CE Interview as the primary data set to produce our 

consumption measure and poverty statistics. Third, we include in consumption the flow of 

services from owner-occupied housing and the flow of services from vehicles. Fourth, we 

exclude health and education as components of consumption, which partially implements the 

recommendation of producing versions with and without values for health insurance. Fifth, we 

use regression-based modeling in combination with administrative in-kind benefits data. And 

finally, we applied an equivalence scale that accounts for the differing needs of adults and 

children and economies of scale in consumption. 

13 For the full report, published on January 14, 2021, see ITWG (2021). 
12

Recommendations of the Interagency Technical Working Group (ITWG) on Evaluating 

Alternative Measures of Poverty14 Focused on Consumption or the Bureau of Labor Statistics 

(identified by recommendation number in the report)

1. The Working Group recommends that the Census Bureau and the Bureau of Labor Statistics 

engage with stakeholders and other experts throughout the development of the recommended 

measures, including soliciting additional public comment as needed. In particular, the Working 

Group recommends expert input through a National Academy of Sciences panel.

5. The Working Group recommends that the Bureau of Labor Statistics develop and publish two 

new sets of research measures of consumption-based resources, one that includes a value of 

health insurance and one that does not.

6. The Working Group recommends that the Census Bureau and the Bureau of Labor Statistics 

use, where available and when appropriate, administrative data to supplement or replace the 

use of survey data for developing the recommended measures.

14. The value of health insurance should not depend on the disability or health status of 

individuals.

17. The Working Group recommends that expenditures on education be excluded from the 

recommended extended income-based and consumption-based resource measures because 

education is generally considered an investment in human capital.

19. The Working Group recommends continued research and additional stakeholder and expert 

engagement on whether and how to treat education within resource measures.

22. The Working Group recommends, taking into consideration the advantages and 

disadvantages for each of the above approaches for correcting for missing or misreported data, 

the application of all three approaches, where appropriate, in the following order: Methods 

that combine administrative data with survey data are the preferred approach for adjusting 

survey data to correct for misreporting and missing data. These methods may involve direct 

replacement of survey responses with administrative reports when research supports the 

quality of the administrative records relative to survey reports. The administrative data need to 

be available for use in production and the administrative data must also be available in a timely 

fashion. When survey reports conflict with administrative records for particular individuals, 

research should examine criteria to determine which source to use for the poverty estimates. 

Consistent with Foundations for the Evidence-based Policymaking Act of 2018, efforts to

14 From Final Report of the Interagency Technical Working Group on Evaluating Alternative Measures of Poverty, 

January 14, 2021. Available at https://www.bls.gov/evaluation/final-report-of-the-interagency-technical-workinggroup-on-evaluating-alternative-measures-of-poverty.pdf 
13

encourage and facilitate data sharing across government agencies should be strengthened. 

Research to assess ways in which survey data might be made more comparable to 

administrative data (e.g., changing the reference period for income from the previous 12 

months to the previous calendar year) should be encouraged. Regression-based modeling (with 

or without individual-level or aggregate administrative

data) can also improve the quality of estimates of income, expenditures, and program 

participation. These regression-based techniques can be used, for example, when sharing 

agreements do not allow for direct substitution, there are significant lags in the availability of 

administrative data, or administrative data are not available for all geographies or years. 

Regression-based modeling such as Sequential Regression Multiple Imputation (SRMI) should 

replace hot deck imputations where feasible and continued research should be conducted to 

improve these methods as new tools and techniques become available. Some rules-based 

adjustment may be necessary for some programs and income sources. For example, if program 

rules assign automatic eligibility for Medicaid to all TANF and SSI

recipients, it could be logical to assign program receipt to all survey respondents who are 

known to participate in either of these two programs. In a similar vein, if there are school 

districts in which all students are deemed eligible for free school lunch, they should be assigned 

participation in free school lunch if they report that their children regularly eat school meals.

24. The Working Group recommends that the Census Bureau and the Bureau of Labor Statistics 

continue to research, and possibly implement, ways to reduce survey burden and improve the 

quality of resulting data through increased access and use of administrative data in surveys, 

including the ... CE.

25. The Working Group recommends funding support of the work to develop the new 

recommended measures, including funding to support BLS to research the nature and 

construction of a potential consumption-based poverty measure and improve the CE program 

in support of improved poverty measurement. A proposal requesting $7.1 million was included 

in the fiscal year 2021 President’s Budget.

26. The Working Group recommends that the Bureau of Labor Statistics use the CE Interview 

Survey data to research and develop a consumption-based resource measure.

27. The Working Group recommends that the value of service flows from owner-occupied 

shelter and the value of the service flows from owned vehicles be included in the consumption 

resource measures.

28. The Working Group recommends that the CE Interview serve as the primary data source for 

the production of the consumption resource measures, with estimates produced at the state 

level.

29. The Working Group recommends that the current CE Interview Survey serve as the interim 

data source for the production of the consumption resource measures, with estimates 
14

produced at the Census Division level.

32. The Working Group recommends that by the time the proposed resource measures are 

ready to be published, BLS and the Census Bureau should work to identify an interim solution 

for each set of the measures for applying thresholds to produce a full poverty measure. BLS and 

the Census Bureau should consider input from experts (per the previous recommendation) as 

available to inform the applied methodology. The interim methodology applied need not be the 

final methodology chosen for application to the resource measures. The intention of this 

recommendation is to ensure the ability

to publish poverty measures using the proposed resource measure recommendations.

33. The Working Group recommends that the BLS conduct a study of price indexes appropriate 

for use in updating thresholds that would be used in combination with consumption and 

income as defined in this report.

34. The Working Group recommends that an expert panel conduct a study of and make a 

recommendation regarding the application of equivalence scales that would be most 

appropriate for the income and consumption resource measures recommended in this report. 

In the interim, the Working Group recommends that for any resource measures produced an 

equivalence scale be applied that accounts for the potentially differing needs of adults and 

children and economies of scale.
15

Appendix B. Data and Methods

CE Interview Survey

The U. S. Consumer Expenditure Survey (CE) Interview component is the base data set upon 

which the consumption measure and poverty statistics are derived. The CE is a household 

survey sponsored by the BLS and is designed to measure expenditures at the consumer unit 

level.15 The survey has two components, an Interview and a Diary; each instrument has its own 

sample, and thus, Diary and Interview responses cannot be combined at the consumer unit 

level. The Interview is designed to be administered, by personal interview, four times to each 

consumer unit (CU) at three-month intervals. The reference period for expenditures for almost 

all goods and services is the three months prior to the interview. The Diary component is a 

record keeping instrument designed to collect expenditures on frequently purchased categories 

of goods and services during two consecutive weeks. For each instrument, demographic 

information and income are collected; the reference period for income is the previous 12 

months.16 Consumer units can enter the Interview and Diary samples anytime during a calendar 

year; thus, reported expenditures and income can reflect those in overlapping calendar years. 

The BLS estimates that less than one quarter of all CUs participating in the Interview provide 

data for a calendar year (Erhard 2021). For this study, we use data from the Interview only; 

approximately 97 percent of total expenditures, when defined as those reflected in the 

integration of Diary and Interview data, are collected in the Interview.17 Items such as postage 

and nonprescription drugs are not collected in the Interview Survey. Also not collected are 

detailed food and beverage expenses, but these are collected with global questions in the 

Interview.18

One challenge with using the CE Interview data is that it is difficult to generate representative 

annual expenditures at the consumer unit level since not all consumer units participate in all 

four interviews, and when they do, the expenditures do not necessarily reflect those made in a 

calendar year. Thus, for this study, we use quarterly data from 2015Q2 through 2021Q1 to 

produce the spending and consumption measures and resulting poverty statistics. We refer to 

each year in our series by year, for example 2015 with quarterly data collected in 2015Q2-

15 A consumer unit comprises either: (1) all members of a particular household who are related by blood, marriage, 

adoption, or other legal arrangements; (2) a person living alone or sharing a household with others or living as a 

roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is 

financially independent; or (3) two or more persons living together who use their income to make joint 

expenditure decisions. Financial independence is determined by the three major expense categories: housing, 

food, and other living expenses. To be considered financially independent, at least two of the three major expense 

categories are to be provided entirely, or in part, by the respondent. (https://stats.bls.gov/cex/csxgloss.htm ) 16 For additional information in the CE, see: https://stats.bls.gov/cex/home.htm . 17 This percentage is calculated using 2020 internal Interview only data (Interview only tabular data released by 

request) and Integrated Diary and Interview published data (from https://stats.bls.gov/cex/tables/calendaryear/mean/cu-all-multi-year-2013-2020.pdf ) . Mean Interview only total expenditures equal to $59,384 and mean 

Integrated total expenditures equal to $61,334.

18 See BLS Handbook of Methods (2021). https://stats.bls.gov/opub/hom/cex/pdf/cex.pdf
16

2016Q1. With this approach we assume that each quarter represents an independent sample 

that is representative of the U.S. population.19 

Different measures of expenditures and consumption are produced. We start with the CE 

publication definition of total expenditures,20 but subtract miscellaneous expenditures since 

they are not collected each quarter. Our most comprehensive measure of consumption 

includes the flow of services from owner occupied housing and the stock of vehicles owned, 

and public in-kind benefits. Excluded are expenditures for the following: those associated with 

owning a primary residence or vacation home; the purchase and financing of vehicles; cash 

contributions; life, endowment, annuities, and other personal insurance; retirement, pensions, 

and Social Security; healthcare; and education. 

For comparison, we also produce an income measure using after tax income in the CE with the 

value of public in-kind benefits added. CE income also includes the cash value of Supplemental 

Nutrition Assistance Program (SNAP) benefits and the value of compensation in the form of 

meals and housing. After tax income is calculated using imputed federal and state income taxes 

based on TAXSIM. 

Public In-kind Benefits

Public in-kind benefits include those for rental assistance, Low Income Home Energy Assistance 

Program (LIHEAP), the National School Lunch Program (NSLP), and the Supplementary Nutrition 

Program for Women, Infants, and Children (WIC). SNAP benefits are not imputed to the 

consumption measure as they are assumed to be accounted for implicitly in reports of food 

expenditures; it is expected that consumer units use SNAP benefits before other sources of 

income or credit to pay for food. Public in-kind transfers of rental assistance are derived from 

regression models using CE Interview collected rental unit characteristics and rent paid. 

Included in consumption is the difference in imputed and reported rents for renters receiving 

19 This is in contrast to the approach taken by others who produce annual consumption measures (e.g., to study 

inequality or poverty) by restricting the data to consumer units with four complete interviews with population 

weights adjusted to reflect specific consumer unit characteristics (e.g., Fisher et al. 2015), multiplying each 

quarterly interview consumption values by four to approximate annual values (e.g., Meyer and Sullivan 2012), or 

adjusting the weights to reflect the number of quarterly interviews in which consumer units participated (e.g., 

Brouillette et al., 2021). 

20 Total 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. Periodic credit or installment 

payments on goods or services already acquired are also excluded. The full cost of each purchase is recorded, even 

though full payment may not have been made at the date of purchase. The order of the expenditures listed here 

follows the order of presentation in published CE tables. The major categories of expenditures include the 

following: food, housing, apparel and services, transportation, healthcare, entertainment, and other expenditures. 

Other expenditures include the following: personal care products and service; reading; education; tobacco products 

and smoking supplies; miscellaneous; cash contributions; life, endowment, annuities, and other personal insurance; 

retirement, pensions, and Social Security.
17

government assistance with rents, those living in public housing, and those living in rentcontrolled units. 

No information is collected in the Interview regarding LIHEAP, NSLP, or WIC. Data from the 

Current Population Annual Social and Economic Supplement (CPS-ASEC) were combined with CE 

data to impute LIHEAP benefits to consumer units and receipt of benefits from the NSLP and 

WIC. NSLP benefits from the USDA were assigned to consumer units by imputing NSLP receipt 

and using the same number of school days for all states for 2015 through 2019. Benefit levels 

for 2020 were assigned using a similar procedure, but the amount of the benefit varies based on 

the number of school days in session and assumptions regarding the number of days not in 

school, but with the possibility of receiving benefits via SNAP Electronic Benefit Transfers 

(EBT).21 WIC benefits from USDA were assigned to consumer units with imputed WIC receipt 

and varied by the number of infants, children, and mothers in the WIC sample. In addition to 

the average WIC food benefit being assigned to each member in a WIC consumer unit, benefits 

reflecting the value the infant formula rebates are also added. Over the last several years states 

have begun to distribute WIC benefits using EBTs. For those states having fully implemented

EBTs, only the infant formula rebates were assigned to WIC consumer units.22 As with SNAP EBT, 

food expenditures are assumed to implicitly account for WIC benefits distributed via EBT. 

Rental Equivalence of Owned Homes and Rent for Renters

The flow of services from owner occupied housing are based on respondents’ answers to the 

following question: If someone were to rent this “dwelling” how much do you think it would 

rent for monthly, unfurnished, and without utilities? This question is asked regarding one’s 

primary residence, as well as for vacation homes, and is based on when the interview takes 

place. In order to include a value of rent for renters that is most comparable to current owners’ 

rental equivalence, we used the last month of rent paid rather than the sum of the rents 

reported for the past three months (the reference period). The quarterly value of all rents paid 

are included in CE publications.

The rental equivalence of owners’ primary residences (where they live at the time of the 

interview), and the rental equivalence for vacation homes and time shares are available in the 

CE Interview data files. Included in the most comprehensive consumption measure are the 

rental equivalences for primary residences and vacation homes for own use as well as those 

available for rent to others for part of the year. Not included in consumption are the rental 

equivalence for time shares. 

21 See Shrider (2021). 22 See the following to link to the USDA WIC EBT Status Report (January 2022) https://www.fns.usda.gov/wic/wicebt-activities.
18

Vehicle Flow of Services: Depreciation and Opportunity Costs

The value of the flow of services from owned vehicles is a function of vehicle depreciation and 

the opportunity cost of owning their stock of vehicles versus another asset. Depreciation and 

opportunity costs depend on the current market value of the stock of vehicles owned. 

Depreciation rates are first estimated using vehicle characteristics (original purchase price, 

make, model and year, and whether used or new). Then current market values are also 

estimated. Service flows from the stock of vehicles owned are produced only for cars and trucks 

since the characteristic information for the other vehicles (e.g., motorcycles, RVs, private 

airplanes) is not sufficient to estimate the current market values. Pooled quarterly data from CE 

Interview periods 1996Q1 through 2021Q1 are used to estimate age specific vehicle 

depreciation rates and current market values. There are unique age specific depreciation rates 

across all interview years. The opportunity costs are estimated using the current market value 

and long-term security rates. The ones that we use are the “Treasury Long-Term Average (Over 

10 Years), Inflation-Indexed, Percent, Annual, Not Seasonally Adjusted.” The annual rates are 

derived from the monthly rates published on the FRED website: 

https://fred.stlouisfed.org/series/DLTIIT.

Relative Poverty Thresholds and Equivalence Scales

The relative poverty thresholds are derived based on the ranking of population weighted 

equivalized income, expenditures, and consumption. Consumer unit level values of income, 

expenditures, and consumption are converted to equivalized values by dividing by the number 

of equivalent adults in the consumer unit. The number of equivalent adults is based on 

applying the three-parameter scale to the adults and children in the consumer unit. The 

equivalence adjustment reflects that (1) on average, children need or consume less than adults; 

(2) as consumer unit size increases, expenditure and consumption needs do not increase at the 

same rate; and (3) the increase in need is larger for a first child of a single-parent family than 

the first child of a two-adult family. The three-parameter scale is calculated in the following 

way:

• One and two adults: scale = (number of adults)0.5

• Single parents: scale = (number of adults + 0.8*first child + 0.5*other children)0.7

• All other families: scale = (number of adults + 0.5*number of children)0.7

In the calculation used to convert consumer unit income, expenditures, and consumption for 

two adults, the scale is set to 1.41. The economy of scale factor is set at 0.70 for other family 

types, which is within the 0.65 to 0.75 range recommended by the NAS panel that released a 

report on a new approach to measuring poverty in the U.S. (NRC 1995).

Absolute Poverty Thresholds

The absolute poverty thresholds are either anchored in 2015 or the thresholds are those that 

result when the poverty rate is anchored to 2015. Absolute anchored thresholds are based on 
19

the anchor being the 2015 relative consumption_4 threshold. The Absolute thresholds based 

on anchoring the poverty rates are based on the poverty rate for the 2015 relative 

consumption_4 threshold. Both absolute thresholds are updated to 2016 through 2020 using 

the Chained CPI-U.23

Appendix B References

Brouillette, Jean-Felix, Charles I. Jones, and Peter J. Klenow. 2021. “Race and Economic WellBeing in the United States.” NBER Working Paper 29539.

Bureau of Labor Statistics (BLS). 2021. “Handbook of Methods: Consumer Expenditures and 

Income.” https://stats.bls.gov/opub/hom/cex/pdf/cex.pdf. Accessed 2022-01-11.

Erhard, Laura. 2021. Email communication from Brett Creech to Thesia Garner, December 22, 

2021, 3:11 p.m.

Fisher, Jonathan, David S. Johnson, and Timothy M. Smeeding. 2015. “Inequality of income and 

consumption in the U.S.: Measuring the trends in inequality from 1984 to 2011 for the 

same individuals.” Review of Income and Wealth, 61(4), 630-650.

Interagency Technical Working Group (ITWG). 2021. “Final Report of the of the Interagency 

Technical Working Group on Evaluating Alternative Measures of Poverty.” 

https://www.bls.gov/evaluation/final-report-of-the-interagency-technical-workinggroup-on-evaluating-alternative-measures-of-poverty.pdf. Accessed on 2022-01-11. 

Meyer, Bruce D., and James X. Sullivan. 2012. “Winning the War: Poverty from the Great 

Society to the Great Recession.” Brookings Papers on Economic Activity, Fall, 133-183.

National Research Council (NRC). 1995. Measuring Poverty: A New Approach. Washington, DC: 

The National Academies Press.

Shrider, Emily. 2021. “Alternative School Lunch Valuation in the CPS ASEC During COVID-19.” 

Census Bureau SEHSD Working Paper #2021-20. 

https://www.census.gov/content/dam/Census/library/publications/2021/demo/p60-

275.pdf. Accessed on 22-01-11. 

23 The C-CPI-U employs a formula that reflects the effect of substitution that consumers make across item 

categories in response to changes in relative prices. The C-CPI-U designed to account for consumer substitution 

between item categories, any remaining substitution bias (as compared to the CPI-U) would be quite small. See 

https://www.bls.gov/cpi/additional-resources/chained-cpi.htm