This paper investigates the robustness of recent findings on the effect of parental background on child health. We are particularly concerned with the extent to which their finding that income effects on child health are the result of spurious correlation rather than some causal mechanism. A...

Whether interested in the differential impact of a particular factor in various institutional settings or in the heterogeneous effect of policy or random experiment, the empirical researcher confronts a problem if the factor of interest is correlated with an omitted variable. This paper...

Working as a volunteer is a widespread phenomenon that has both individual and societal benefits. In this paper, we identify the wage returns to working for free by exploiting exogenous variation in rainfall across local area districts in England, Scotland and Wales. Instrumental variables...

This paper combines the approach by Guimarães and Portugal (2010) with the methodology of Gelbach (2015) to investigate the determinants of the least squares bias of the wage return to education. We find that disregarding individual fixed effects is highly problematic, accounting for 95% of the...

Previous studies have shown that both height and weight are associated with wages. However, by focusing on interpreting the partial effects of either height or weight on wages while holding all else constant, some gaps in our understanding of the complex relationship between body size and wages...

We show that the OLS and fixed‐effects (FE) estimators of the popular difference-in-differences model may deviate when there is time varying panel non-response. If such non-response does not affect the common-trend assumption, then OLS and FE are consistent, but OLS is more precise. However,...

It is standard practice in applied work to rely on linear least squares regression to estimate the effect of a binary variable ("treatment") on some outcome of interest. In this paper I study the interpretation of the regression estimand when treatment effects are in fact heterogeneous. I show...

A growing literature on inference in difference-in-differences (DiD) designs with grouped errors has been pessimistic about obtaining hypothesis tests of the correct size, particularly with few groups. We provide Monte Carlo evidence for three points: (i) it is possible to obtain tests of the...

Applied work often studies the effect of a binary variable ("treatment") using linear models with additive effects. I study the interpretation of the OLS estimands in such models when treatment effects are heterogeneous. I show that the treatment coefficient is a convex combination of two...

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...