April 2023 MLR -- Developing a consumption measure, with examples of use for poverty and inequality analysis: a new research product from BLS
Abstract: This study provides an update on the work being done by the U.S. Bureau of Labor Statistics (BLS) to produce a research-based consumption measure and explores its potential use in poverty and inequality analysis. For this study, and for most U.S.-based studies in the literature, the Consumer Expenditure Surveys serve as the base to develop the measure. The consumption measure presented in this study accounts for the flow of services from homeownership and owned vehicles, in-kind transfers from government and private entities, and for the full value of health insurance; very few researchers have accounted for all of these. The main contribution is to provide the literature with an update on BLS activities, which include a plan to include home production in the consumption measure and information regarding an upcoming BLS research series. Using the measures produced in this study, we find that consumption without health insurance is 16 percent lower, on average, than total expenditures. Using a consumption measure, with or without health insurance, results in lower poverty rates than when using measures based on total expenditures or pretax income, and consumption for all the measures is more equal than the distributions of total expenditures or income. Using an absolute poverty measure, we find a noticeable decrease in the poverty rate from 2019 to 2021, when measured by consumption without health insurance.
Much of the economic well-being research focused on understanding the effects of behavior and policies on utility relies on the relationship between utility and household consumption or utility and household income. That research primarily uses income data from surveys. In the United States and other countries with more advanced economies, income data are more readily available from surveys and thus are more commonly used as a proxy for well-being than consumption. Additionally, researchers might prefer income as a measure of well-being because it reflects access to resources that could be used for consumption, whereas well-being measured by consumption could be artificially low because of preferences. However, income is more sensitive to short-run fluctuations, whereas consumption better reflects long-term resources and is more likely to capture disparities that result from differences across households in access to credit or the accumulation of assets. There is also evidence that components of consumption that are particularly important for poor people are well captured in household surveys, while many components of income important to poor people may not be as well captured in such surveys. Furthermore, some researchers have suggested that consumption is more strongly correlated with other indicators of economic well-being than is income. However, rather than promoting one measure over another, other research efforts support multidimensional measures of economic well-being, thereby noting that unidimensional measures are not sufficient.
Although consumption may be a better measure of economic well-being than income, determining the actual consumption level for an individual or a group of individuals—a person or family that forms a consumer unit (CU), for example—is difficult because it depends on the individual’s or group’s particular circumstances, choices, use of purchases, and time usage. In addition, data limitations make the problem of valuing consumption even more difficult. For example, combining expenditures data with time-use data has been particularly challenging. As a result, many researchers have used expenditures as a proxy for consumption. The U.S. Bureau of Labor Statistics (BLS) Consumer Expenditure Surveys (CE) have been the primary source of expenditures data at the CU level for researchers and government agencies since the late 19th century. And, as such, the CE is the oldest BLS product that collects household or consumer expenditures as a measure of living conditions for the United States.
BLS has long been interested in the creation of a measure of consumption with CE data as the base, as have other researchers. For example, Fisher, Johnson, and Smeeding (2015) produced a measure of consumption to study inequality, and Meyer and Sullivan (2012, 2013) produced a consumption measure to study poverty and inequality. However, recent experiences with the COVID-19 pandemic have highlighted the need for a more comprehensive consumption measure than has previously been produced. Throughout the pandemic, family and household members have played an increasingly important role in the well-being of other members of their households through the provision of services such as childcare, eldercare, more home-cooked meals, and education, all of which are nonmarket transactions and not captured with expenditures alone. For these transactions, a comprehensive consumption measure needs to account for the time household members spend in home production for their own consumption. These shortcomings of expenditures as an economic measure of well-being have motivated researchers at BLS to develop a more comprehensive consumption measure that accounts for a broader set of in-kind benefits than accounted for in previous measures and for the value of home production for own consumption.
Our first attempt at BLS to produce a consumption measure was published in the May 2022 edition of AEA Papers and Proceedings as “Building a consumption poverty measure: initial results following recommendations of a federal interagency working group.” In this article, we build upon our earlier work by expanding what is included in consumption and refining our methods to produce the measure. The primary difference between the earlier consumption measure and the one presented in this article is that we introduce a value of health insurance; this makes our most recent consumption measure more like the ones produced by Meyer and Sullivan (2012, 2013). This enables us to produce three consumption measures: one that excludes health insurance, one that includes health insurance capped as a percentage of consumption, and one that includes health insurance not capped. The measure based on capping health insurance expenditures for poverty measurement is based on a recommendation made by the Interagency Technical Working Group on Evaluating Alternative Measures of Poverty (ITWG). As illustrations of how the measures can be used, we produce simple means for the consumption measures and components and inequality statistics for 2019, 2020, and 2021. The consumption-based poverty and inequality statistics are compared with statistics based on pretax income and CE-defined total expenditures.
In our analysis, we find that the value of CU consumption without health insurance averaged about 16 percent less than CE total expenditures over the 3-year period, and that the values of CU consumption with health insurance (capped and uncapped) was about 14 percent more than CE total expenditures in 2019 and 2020, and about 12 percent more in 2021. For all consumption measures, compared with total expenditures and pretax income, poverty rates are lower when based on a relative concept. The absolute concept that we used for this study sets all poverty rates the same in 2019; such an approach allows us to see how poverty rates changed over the period while holding the base poverty rate the same. Our results show a noticeable decrease in the poverty rate from 2019 to 2021 when it is measured by consumption without health insurance. For all 3 years, consumption distributions are more equal than distributions of total expenditures and pretax income. Relative to 2019, we find that consumption poverty fell in 2020, with the onset of the pandemic, and that distributions of consumption became more equal. Compared with 2020, for all the consumption measures, poverty rose in 2021 when we used a relative measure, and inequality rose but not to the same levels as in 2019.
The consumption measures presented in this article represent work in progress. Next steps in the development of the BLS research consumption measure include the addition of the value of time for home production. During the 2021–23 period, BLS sponsored research to impute values of select home-production activities using the BLS American Time Use Survey and other data in combination with the CE. Once the value of home production is included, the goal of BLS to produce a more comprehensive measure of consumption can be realized. In addition, BLS plans to publish a consumption-measure research series based on internal CE data and imputation; this series will be available to the public through published tables of means. The series will not be an official BLS production series, but it can be referred to as an official research series. Depending upon available resources, BLS plans to release an auxiliary public-use data file that includes research-based consumption values. . . .
Thesia I. Garner email@example.com
Thesia I. Garner is the chief research economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics.
Brett Matsumoto firstname.lastname@example.org
Brett Matsumoto is a research economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics.
Jake Schild email@example.com
Jake Schild is a research economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics.
Scott Curtin firstname.lastname@example.org
Scott Curtin is a branch chief in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics.
Adam Safir email@example.com
Adam Safir is a division chief in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics.