This paper reviews the empirical methods used in the accounting literature to draw causal
inferences. Recent years have seen a burgeoning growth in the use of methods that seek to …

This article reviews recent advances in fixed effects estimation of panel data models for long
panels, where the number of time periods is relatively large. We focus on semiparametric …

We study the incidental parameter problem for the “three-way” Poisson Pseudo-Maximum
Likelihood (“PPML”) estimator recently recommended for identifying the effects of trade …

In this survey we discuss the recent causal panel data literature. This recent literature has
focused on credibly estimating causal effects of binary interventions in settings with …

This paper introduces time‐varying grouped patterns of heterogeneity in linear panel data
models. A distinctive feature of our approach is that group membership is left unrestricted …

I introduce a model of undirected dyadic link formation which allows for assortative matching
on observed agent characteristics (homophily) as well as unrestricted agent‐level …

We study discrete panel data methods where unobserved heterogeneity is revealed in a first
step, in environments where population heterogeneity is not discrete. We focus on two‐step …

We derive fixed effects estimators of parameters and average partial effects in (possibly
dynamic) nonlinear panel data models with individual and time effects. They cover logit …

This paper studies a quantile regression dynamic panel model with fixed effects. Panel data
fixed effects estimators are typically biased in the presence of lagged dependent variables …

Maximum-likelihood estimation of nonlinear models with fixed effects is subject to the
incidental-parameter problem. This typically implies that point estimates suffer from large …