Earnings nonresponse in household surveys is widespread, yet there is limited evidence on whether and how nonresponse bias affects measured earnings. This paper examines the patterns and consequences of nonresponse using internal Current Population Survey individual records linked to administrative Social Security Administrative data on earnings for calendar years 2005-2010. Our findings confirm the conjecture by Lillard, Smith, and Welch (1986) that nonresponse across the earnings distribution is U-shaped. Left-tail “strugglers” and right-tail “stars” are least likely to report earnings.
The Current Population Survey Annual Social and Economic Supplement (ASEC) serves as the data source for official income, poverty, and inequality statistics in the United States. There is a concern that the rise in nonresponse to earnings questions could deteriorate data quality and distort estimates of these important metrics. We use a dataset of internal ASEC records matched to Social Security Detailed Earnings Records (DER) to study the impact of earnings nonresponse on estimates of poverty from 1997-2008.
To measure poverty, incomes must be made equivalent across households with different structures. In this paper, we use a very flexible ordered response model to analyze the relationship between income, demographic structure, and subjective assessments of financial wellbeing drawn from the 1991-2008 British Household Panel Survey. Our results suggest the existence of large-scale economies within marital/cohabiting couples, but substantial diseconomies from the addition of children or further adults.
Earnings nonresponse in the Current Population Survey is roughly 30% in the monthly surveys and 20% in the March survey. If nonresponse is ignorable, unbiased estimates can be achieved by omitting nonrespondents. Little is known about whether CPS nonresponse is ignorable. Using sample frame measures to identify selection, we find clear-cut evidence among men but limited evidence among women for negative selection into response.
We offer new evidence on earnings volatility of men and women in the United States over the past four decades by using matched data from the March Current Population Survey. We construct a measure of total volatility that encompasses both permanent and transitory instability, and that admits employment transitions and losses from self employment. We also present a detailed decomposition of earnings volatility to account for changing shares in employment probabilities, conditional variances of continuous workers, and conditional mean variances from labor-force entry and exit.
Despite evidence that skilled labor is increasingly concentrated in cities, whether regional wage inequality is predominantly due to differences in skill levels or returns is unknown. We compare Appalachia, with its wide mix of urban and rural areas, to other parts of the U.S., and find that gaps in both skill levels and returns account for the lack of high wage male workers. For women, skill shortages are important across the distribution. Because rural wage gaps are insignificant, our results suggest that widening wage inequality between Appalachia and the rest of the U.S.
We document the demographic and economic forces underlying changes in income inequality among single mother families over the past three decades in the United States. Using decomposable measures of after-tax income-to-needs inequality, we examine within- and between-group inequality based on education attainment, age, past marital status, race, and employment status. We also conduct income factor decompositions to quantify the relative contributions of earnings, transfers, other income, and taxes to inequality.
Refugees are typically poorer than other immigrants and native born, although the average difference is smal, with changes in the unemployment rate explaining most of the difference in poverty rates. In times of recession, or in areas with particularly high unemployment rates, refugees will fare worse, perhaps due to concentrations of refugees in industries with higher cyclical variation in unemployment. We also find that refugees’ poverty rates start higher but fall more rapidly with time, suggesting that refugees assimilate more rapidly than other immigrants.
We estimate a model of food stamp program participation allowing for differences between refugees and immigrants. The model examines pre and post reform participation. It further isolates the effect of local labor markets. Using auxiliary information from the INS’ Statistical Yearbooks we are able to identify the impact refugee status has on participation. We demonstrate that regressions using ad hoc variables are subject to severe measurement error bias. We also correct for measurement error in the report of food stamp participation.
As labor markets tightened in the last half of the nineties, economic development and community leaders sought to identify more locally available workers than were indicated by published statistics. Using results from commissioned surveys, they pointed to large numbers of part-time workers who desired full-time work, and to full-time workers who were qualified for better jobs. These statistics were often used to negate low official unemployment rates that deterred firms, concerned by the ostensible shortage of workers, from locating in their counties.
