It is standard practice in applied work to study the effect of a binary variable ("treatment") on an outcome of interest using linear models with additive effects. In this paper I study the interpretation of the ordinary and two-stage least squares estimands in such models when treatment effects...

Since identification, instrumental variables and variables exclusion, core concepts in econometrics, are entwined, several questions arise: How is identification related to the existence of IVs? How are identification criteria related to omitted variables? Is omission/inclusion of variables from...

The authors model COVID infections and COVID deaths, both reported and implied, for the 50 U.S. states as well as the District of Columbia, and separately for a sample of 33 countries, as a function of pre-existing circumstances that citizens have no ability to control over the short term. These...

This article provides empirical researchers with an introduction and guide to research designs based on variation in judge and examiner tendencies to administer treatments or other interventions. We review the basic theory behind the research design, outline the assumptions under which the...

In this paper we study semiparametric efficiency for the estimation of a finite-dimensional parameter defined by generalized moment conditions under the local instrumental variable assumptions. These parameters identify treatment effects on the set of compliers under the monotonicity assumption....

We study the estimation of causal treatment effects on demand when treatment is randomly assigned but prices adjust in response to treatment. We show that regressions of demand on treatment or on treatment and price lead to biased estimates of the direct treatment effect. The bias in both cases...

We examine the relationship between child quantity and quality. Motivated by the theoretical ambiguity regarding the sign of the marginal effects of additional siblings on children’s outcomes, our empirical model allows for an unrestricted relationship between family size and child outcomes....

We develop an “omitted variable bias” framework for sensitivity analysis of instrumental variable (IV) estimates that is immune to “weak instruments,” naturally handles multiple “side-effects” (violations of the exclusion restriction assumption) and “confounders” (violations of...

This paper studies panel data models with interactive fixed effects where the regressors are allowed to be correlated with the idiosyncratic error terms. We propose a two-step profile GMM estimation procedure to estimate the parameters of interest. In the first step we obtain a preliminary...

Instrumental variables (IV) are often used to provide exogenous variation in the impulse response analysis but the heterogeneous effects the IV may identify are rarely discussed. In microeconometrics, on the other hand, it is well understood that an IV identifies the local average treatment...