This study investigates how to use regression adjustment to reduce variance in experimental data. We show that the estimators recommended in the literature satisfy an orthogonality property with respect to the parameters of the adjustment. This observation greatly simplifies the derivation of...

Loss aversion is one of the most widely used concepts in behavioral economics. We conduct a large-scale interdisciplinary meta-analysis, to systematically accumulate knowledge from numerous empirical estimates of the loss aversion coefficient reported during the past couple of decades. We...

Interference between units may pose a threat to unbiased causal inference in randomized controlled experiments. Although the assumption of no interference is essential for causal inference, few options are available for testing this assumption. This paper presents the first reliable ex post...

We assess selection bias in estimated returns to workplace training by exploiting a field experiment with random assignment of workers to a one-week training program. We compare experimental estimates of this program with non-experimental estimates that are estimated by using a sample of agents...

We assess selection bias in estimated returns to workplace training by exploiting a field experiment with random assignment of workers to a one-week training program. We compare experimental estimates of this program with non-experimental estimates that are estimated by using a sample of agents...

Session-specific features of a laboratory experiment, if those exist, do not disappear by clustering standard errors at the session level. Randomly ordering sessions, which is crucial to deal with sampling issues, cannot justify clustering the standard errors at the session level. The...

We examine the generalizability of internally valid estimates of causal effects in a fixed population over time when that population is subject to aggregate shocks. This temporal external validity is shown to depend upon the distribution of the aggregate shocks and the interaction between these...

We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment...

We present a semiparametric method to estimate group-level dispersion, which is particularly effective in the presence of censored data. We apply this procedure to obtain measures of occupation-specific wage dispersion using top-coded administrative wage data from the German IAB Employment...