We document the extent, nature, and consequences of survey errors in cash welfare and SNAP receipt in three major U.S. household surveys. We find high rates of misreporting, particularly failure to report receipt. The surveys inaccurately capture patterns of multiple program participation, even...

Measurement errors are often a large source of bias in survey data. Lack of knowledge of the determinants of such errors makes it difficult for data producers to reduce the extent of errors and for data users to assess the validity of analyses using the data. We study the determinants of...

Survey error is known to be pervasive and to bias even simple, but important estimates of means, rates, and totals, such as the poverty and the unemployment rate. To summarize and analyze the extent, sources, and consequences of survey error, we define empirical counterparts of key components of...

We describe methods of combining administrative and survey data to improve the measurement of income. We begin by decomposing the total survey error in the mean of survey reports of dollars received from a government transfer program. We decompose this error into three parts, generalized...

Accurately measuring government benefit receipt in household surveys is necessary when studying disadvantaged populations and the programs that serve them. The Food Stamp Program is especially important given its size and recent growth. To validate survey reports, we use administrative data on...

We examine the consequences of underreporting of transfer programs for prototypical analyses of low-income populations using the Current Population Survey (CPS), the source of official poverty and inequality statistics. We link administrative data for food stamps, TANF, General Assistance, and...

While measurement error in the dependent variable does not lead to bias in some well-known cases, with a binary dependent variable the bias can be pronounced. In binary choice, Hausman, Abrevaya and Scott-Morton (1998) show that the marginal effects in the observed data differ from the true ones...

Stigma of welfare participation is important for policy and survey design, because it deters program take-up and increases misreporting. Stigma is also relevant to the literature on social image concerns, yet empirical evidence is scant because stigma is difficult to empirically identify. We use...

Large literatures have analyzed racial and ethnic disparities in economic outcomes and access to the safety net. For such analyses that rely on survey data, it is crucial that survey accuracy does not vary by race and ethnicity. Otherwise, the observed disparities may be confounded by...