School systems regularly use student assessments for accountability purposes. But, as highlighted by our conceptual model, different configurations of assessment usage generate performance-conducive incentives of different strengths for different stakeholders in different school environments. We...

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,...

We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data,...

Using American panel data from the National Educational Longitudinal Study of 1988 (NELS:88) this paper investigates the effect of working during grade 12 on attainment. We exploit the longitudinal nature of the NELS by employing, for the first time in the related literature, a semiparametric...

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...

Macroeconomists have long been concerned with the causal effects of monetary policy. When the identification of causal effects is based on a selection-on-observables assumption, non-causality amounts to the conditional independence of outcomes and policy changes. This paper develops a...

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...

We use unique data from journal submissions to identify and unpack publication bias and p-hacking. We find that initial submissions display significant bunching, suggesting the distribution among published statistics cannot be fully attributed to a publication bias in peer review. Desk-rejected...

In a randomized control trial, the precision of an average treatment effect estimator can be improved either by collecting data on additional individuals, or by collecting additional covariates that predict the outcome variable. We propose the use of pre-experimental data such as a census, or a...

Exogenous shocks often impact a local labor market more than at the national level. This study improves upon the standard Difference in Difference (DD) approach by examining exogenous shocks using a Generalized Difference in Difference (GDD) econometric approach that identifies the effects of...