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Earnings Measurement Error, Nonresponse and Administrative Mismatch in the CPS
July 2025
Working Paper Number:
CES-25-48
Using the Current Population Survey Annual Social and Economic Supplement matched to Social Security Administration Detailed Earnings Records, we link observations across consecutive years to investigate a relationship between item nonresponse and measurement error in the earnings questions. Linking individuals across consecutive years allows us to observe switching from response to nonresponse and vice versa. We estimate OLS, IV, and finite mixture models that allow for various assumptions separately for men and women. We find that those who respond in both years of the survey exhibit less measurement error than those who respond in one year. Our findings suggest a trade-off between survey response and data quality that should be considered by survey designers, data collectors, and data users.
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Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation
April 2011
Working Paper Number:
CES-11-14
Benefit receipt in major household surveys is often underreported. This misreporting leads to biased estimates of the economic circumstances of disadvantaged populations, program takeup, and the distributional effects of government programs, and other program effects. We use administrative data on Food Stamp Program (FSP) participation matched to American Community Survey (ACS) and Current Population Survey (CPS) household data. We show that nearly thirty-five percent of true recipient households do not report receipt in the ACS and fifty percent do not report receipt in the CPS. Misreporting, both false negatives and false positives, varies with individual characteristics, leading to complicated biases in FSP analyses. We then directly examine the determinants of program receipt using our combined administrative and survey data. The combined data allow us to examine accurate participation using individual characteristics missing in administrative data. Our results differ from conventional estimates using only survey data, as such estimates understate participation by single parents, non-whites, low income households, and other groups. To evaluate the use of Census Bureau imputed ACS and CPS data, we also examine whether our estimates using survey data alone are closer to those using the accurate combined data when imputed survey observations are excluded. Interestingly, excluding the imputed observations leads to worse ACS estimates, but has less effect on the CPS estimates.
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Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net
October 2015
Working Paper Number:
CES-15-35
We examine the consequences of underreporting of transfer programs in household survey data for several prototypical analyses of low-income populations. We focus on the Current Population Survey (CPS), the source of official poverty and inequality statistics, but provide evidence that our qualitative conclusions are likely to apply to other surveys. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the CPS at the individual level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, 40 percent of food stamp recipients and 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients, particularly for TANF, General Assistance and housing assistance. We find that the survey data sharply understate the income of poor households, as conjectured in past work by one of the authors. Underreporting in the survey data also greatly understates the effects of anti-poverty programs and changes our understanding of program targeting, often making it seem that welfare programs are less targeted to both the very poorest and middle income households than they are. Using the combined data rather than survey data alone, the poverty reducing effect of all programs together is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, specifically the share of people without work or program receipt. Using the administrative measures of program receipt rather than the survey ones often reduces the share of single mothers falling through the safety net by one-half or more.
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Long-Run Earnings Volatility and Health Insurance Coverage: Evidence from the SIPP Gold Standard File
October 2011
Working Paper Number:
CES-11-35
Despite the notable increase in earnings volatility and the attention paid to the growing ranks of the uninsured, the relationship between career earnings and short- and mediumrun health insurance status has been ignored due to a lack of data. I use a new dataset, the SIPP Gold Standard File, that merges health insurance status and demographics from the Survey of Income and Program Participation with career earnings records from the Social Security Administration (SSA) and the Internal Revenue Service (IRS) to examine the relationship between long-run family earnings volatility and health insurance coverage. I find that more volatile career earnings are associated with an increased probability of experiencing an uninsured episode, with larger effects for men, young workers, and the unmarried. These findings are consistent with the 'scarring' literature, and suggest the importance of safety-net measures for job losses and health insurance coverage.
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Costs, Demand, and Imperfect Competition as Determinants of Plant_level Output Prices
June 1992
Working Paper Number:
CES-92-05
The empirical modeling of imperfectly competitive markets has been constrained by the difficulty of obtaining micro data on individual producer prices, outputs, and costs. In this paper we utilize micro data collected from the 1977 Census of Manufactures to study the determinants of plant-level output prices among U.S. bread producers. A theoretical model of short-run price competition among plants producing differentiated products is used to specify reduced-form equations for each plant's price and output. Estimates of the reduced-form equations indicate that the main determinants of both the plant's output level and output price are the plant's own cost variables, particularly its capital stock and the prices of material inputs. The number of rival producers faced by the plant, the production costs of these rivals, and the demand conditions faced by the plant play no role in price or output determination. The results are not consistent with either oligopolistic competition or monopoly behavior, but rather are consistent with price-taking behavior by individual producers combined with output quality differentials across producers.
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Potential Bias When Using Administrative Data to Measure the Family Income of School-Aged Children
January 2025
Working Paper Number:
CES-25-03
Researchers and practitioners increasingly rely on administrative data sources to measure family income. However, administrative data sources are often incomplete in their coverage of the population, giving rise to potential bias in family income measures, particularly if coverage deficiencies are not well understood. We focus on the school-aged child population, due to its particular import to research and policy, and because of the unique challenges of linking children to family income information. We find that two of the most significant administrative sources of family income information that permit linking of children and parents'IRS Form 1040 and SNAP participation records'usefully complement each other, potentially reducing coverage bias when used together. In a case study considering how best to measure economic disadvantage rates in the public school student population, we demonstrate the sensitivity of family income statistics to assumptions about individuals who do not appear in administrative data sources.
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Within and Across County Variation in SNAP Misreporting: Evidence from Linked ACS and Administrative Records
July 2014
Working Paper Number:
carra-2014-05
This paper examines sub-state spatial and temporal variation in misreporting of participation in the Supplemental Nutrition Assistance Program (SNAP) using several years of the American Community Survey linked to SNAP administrative records from New York (2008-2010) and Texas (2006-2009). I calculate county false-negative (FN) and false-positive (FP) rates for each year of observation and find that, within a given state and year, there is substantial heterogeneity in FN rates across counties. In addition, I find evidence that FN rates (but not FP rates) persist over time within counties. This persistence in FN rates is strongest among more populous counties, suggesting that when noise from sampling variation is not an issue, some counties have consistently high FN rates while others have consistently low FN rates. This finding is important for understanding how misreporting might bias estimates of sub-state SNAP participation rates, changes in those participation rates, and effects of program participation. This presentation was given at the CARRA Seminar, June 27, 2013
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Using Internal Current Population Survey Data to Reevaluate Trends in Labor Earnings Gaps by Gender, Race, and Education Level
July 2008
Working Paper Number:
CES-08-18
Most empirical studies of trends in labor earnings gaps by gender, race or education level are based on data from the public use March Current Population Survey (CPS). Using the internal March CPS, we show that inconsistent topcoding in the public use data will understate these gaps and inaccurately capture their trends. We create a cell mean series beginning in 1975 that provides the mean of all values above the topcode for each income source in the public use March CPS and better approximate earnings gaps found in the internal March CPS than was previously possible using publically available data.
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Female Executives and the Motherhood Penalty
January 2021
Working Paper Number:
CES-21-03
Childbirth and subsequent breaks from the labor market are a primary reason why the average earnings of women is lower than that of men. This paper uses linked survey and administrative data from the United States to investigate whether the sex composition of executives at the firm, defined as the top earners, affects the earnings and employment outcomes of new mothers. We begin by documenting that (i) the male-female earnings gap is smaller in industries in which a larger share of executives are women, and (ii) the male-female earnings gap has declined more in industries that have experienced larger increases in the share of executives who are female. Despite these cross-sectional and longitudinal correlations, we find no evidence that the sex composition of the executives at the firm has a causal effect on the childbirth and motherhood penalties that impact women's earnings and employment.
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Considering the Use of Stock and Flow Outcomes in Empirical Analyses: An Examination of Marriage Data
January 2017
Working Paper Number:
CES-17-64
This paper fills an important void assessing how the use of stock outcomes as compared to flow outcomes may yield disparate results in empirical analyses, despite often being used interchangeably. We compare analyses using a stock outcome, marital status, to those using a flow
outcome, entry into marriage, from the same dataset, the American Community Survey. This paper considers two different questions and econometric approaches using these alternative measures: the effect of the Affordable Care Act young adult provision on marriage using a difference-indifferences
approach and the relationship between aggregate unemployment rates and marriage rates using a simpler ordinary least squares regression approach. Results from both analyses show stock and flow data yield divergent results in terms of sign and significance. Additional analyses suggest prior-period temporary shocks and migration may contribute to this discrepancy. These results suggest using caution when conducting analyses using stock data as they may produce false negative results or spurious false positive results, which could in turn give rise to misleading policy implications.
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