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 present a new estimator for causal effects with panel data that builds on insights behind
the widely used difference-in-differences and synthetic control methods. Relative to these …

In this article, we study methods for estimating causal effects in settings with panel data,
where some units are exposed to a treatment during some periods and the goal is …

Large factor models use a few latent factors to characterize the co-movement of economic
variables in a high-dimensional data set. High dimensionality brings challenges as well as …

This paper introduces a simple framework of counterfactual estimation for causal inference
with time‐series cross‐sectional data, in which we estimate the average treatment effect on …

Difference-in-differences (DID) is commonly used for causal inference in time-series cross-
sectional data. It requires the assumption that the average outcomes of treated and control …

This paper studies the relationship between public debt expansion and economic growth
and investigates whether the debt-growth relation varies with the level of indebtedness. We …

This paper extends the Common Correlated Effects (CCE) approach developed by Pesaran
(2006) to heterogeneous panel data models with lagged dependent variables and/or weakly …

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

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the
estimation of long-run effects in large dynamic heterogeneous panel data models with cross …