A central concern for economic policymakers around the world is the standard of living enjoyed by their country’s population. Living standards depend on many factors, including workers’ wages and hours, the availability of jobs, living costs, and the adequacy of social insurance programs and the social safety net. Living standards for those at the bottom of the income distribution are a particular concern.

While many studies focus on cross-country differences in living standards, nominal incomes often vary significantly across geographic areas within countries. Whether geographic differences in nominal income translate into geographic differences in living standards, however, depends on the variation across areas in living costs and local amenities. Over the past two years, the COVID-19 pandemic has raised new concerns about living standards, particularly for less skilled workers and workers in the developing world.

The 5^th IZA workshop on labor statistics, organized by Katharine Abraham and Susan Houseman, featured 11 papers and a keynote address delivered by Bruce Meyer of the University of Chicago that explored a variety of questions related to the measurement of incomes, living costs and standards of living. Findings from several of the papers are highlighted below; the full set of papers is listed on the workshop program.

Poverty measurement

One important fact about poverty is that poor households often experience substantial within-year income and consumption volatility. In their paper titled “Poverty at High Frequency,” Joshua Merfeld and Jonathan Morduch show that a substantial fraction of the population in rural South Indian villages whose annual consumption expenditures place them above the poverty line experience months during the year with consumption expenditures below that level. Headcount poverty based on the share of months villagers spend in poverty is 26% higher than implied by conventional annual measures.

This finding has important implications regarding both the value of high-frequency data collection and the targeting of anti-poverty resources, which the authors argue could have greater impact if allocated disproportionately during months when consumption and income are relatively low rather than evenly throughout the year.

In most countries, poverty measurement relies on data collected through household surveys. In their paper titled “Errors in Reporting and Imputation of Government Benefits and Their Implications,” Pablo Celhay, Bruce Meyer and Nikolas Mittag document that household survey respondents in the United States significantly underreport receipt of welfare and food stamp benefits.

Their analysis makes use of data from three large Census Bureau surveys—the Current Population Survey, the American Community Survey and the Survey of Income and Program Participation—linked to administrative data for the state of New York. Imputed values for the benefit receipt variables are even more likely to be wrong than self-reported values. Because reporting and imputation errors are not random, they lead to distortions not only in the level but also in the pattern of benefit receipt.

The paper makes clear the need for improvements in the collection of data on participation in public assistance programs, whether through improvements to the questions on household surveys or expanded access to administrative data.

Geography of living standards

In his keynote address, based on a paper titled “Does Geographically Adjusting Poverty Thresholds Improve Poverty Measurement and Program Targeting?” co-authored with Derek Wu and Brian Curran, Bruce Meyer considered whether poverty thresholds should be adjusted to take account of differences in prices across geographic areas. He argued against make such adjustments based on evidence that those classified as poor only when a geographic price adjustment is applied may be less disadvantaged than those classified as poor only when a uniform poverty threshold is applied.

His assessment of relative disadvantage rested on measures of material hardship, appliances owned, home quality issues, food security, public services, health, education, assets, permanent income and mortality. In nine out of these ten domains, he argued, geographic price adjustments led to counting relatively less disadvantaged people as poor. Meyer’s presentation led to a lively discussion, with discussant David Johnson noting several reasons to be cautious about accepting Meyer’s conclusions at face value.

COVID and living standards

The COVID pandemic clearly has had an impact on living standards around the world. The final paper on the workshop program, “Households in Transit: COVID-19 and the Changing Measurement of Welfare,” by Laura Caron and Erwin Tiongson, raises an interesting measurement question related to the definition of household consumption.

During the early pandemic period, households that were able to shift from in-person work to working from home saved on commuting costs. Using data for the country of Georgia, the study shows that higher income households benefited disproportionately from this shift. Conventional consumption statistics, however, would have treated their drop in commuting costs as a reduction in consumption.

The authors argue that, accounting correctly for changes in commuting costs, high-income households fared relatively better during the pandemic—and low-income households relatively less well—than implied by standard expenditure-based measures.