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...

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...

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...

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...

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...

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 cause bias are often invoked to make computation...

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...

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...