We study the interpretation of regressions with multiple treatments and flexible controls. Such regressions are often used to analyze stratified randomized control trials with multiple intervention arms, to estimate value-added (for, e.g., teachers) with observational data, and to leverage the...

We provide a method to measure welfare, in money-metric terms, taking into account expectations about the future. Our two key assumptions are that (1) the expenditure function is separable between the present and the future, and (2) there are some households that do not face idiosyncratic...

A central question in applied research is to estimate the effect of an exogenous intervention or shock on an outcome. The intervention can affect the outcome and controls on impact and over time. Moreover, there can be subsequent feedback between outcomes, controls and the intervention. Many of...

This study uses the Youth Risk Behavior Survey (YRBS) and the National Comorbidity Survey (NCS) to explore the causal relationship between alcohol abuse (binge drinking and clinically defined alcohol use disorders) and suicide attempts among youth. We use an empirical approach that allows one to...

We explore the interrelationships between various measures of cultural distance. We first discuss measures of genetic distance, used in the recent economics literature to capture the degree of relatedness between countries. We next describe several classes of measures of linguistic, religious,...

We derive general, yet simple, sharp bounds on the size of the omitted variable bias for a broad class of causal parameters that can be identified as linear functionals of the conditional expectation function of the outcome. Such functionals encompass many of the traditional targets of...

Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We...

This paper analyzes difference-in-differences designs with a continuous treatment. We show that treatment effect on the treated-type parameters can be identified under a generalized parallel trends assumption that is similar to the binary treatment setup. However, interpreting differences in...

We develop a method to identify the individual latent propensity to select into treatment and marginal treatment effects. Identification is achieved with survey data on individuals' subjective expectations of their treatment propensity and of their treatment-contingent outcomes. We use the...