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...

Recent studies linking household surveys to administrative records reveal high rates of misreporting of program receipt. We use the FoodAPS survey to examine whether the findings of these studies of general household surveys using one or two states generalize to a survey with a narrow focus and...

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. We link administrative data for food...

Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develops methods to evaluate such issues by examining...

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...

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

Recent validation studies show that survey misreporting is pervasive and biases common analyses. Addressing this problem is further complicated, because validation data are usually convenience samples and access is restricted, making them more suitable to document than to solve the problem. I...

Models with high dimensional sets of fixed effects are frequently used to examine, among others, linked employer-employee data, student outcomes and migration. Estimating these models is computationally difficult, so simplifying assumptions that are likely to cause bias are often invoked to make...

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...

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...