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 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 …

We present a new perspective on the Synthetic Control (SC) method as a weighted least
squares regression estimator with time fixed effects and unit weights. This perspective …

This article provides a selective overview of the recent developments in factor models and
their applications in econometric learning. We focus on the perspective of the low-rank …

Data snooping is a major concern in empirical asset pricing. We develop a new framework
to rigorously perform multiple hypothesis testing in linear asset pricing models, while limiting …

We propose a new latent factor conditional asset pricing model. Like Kelly, Pruitt, and Su
(KPS, 2019), our model allows for latent factors and factor exposures that depend on …

This paper studies panel data models with interactive fixed effects where the regressors are
allowed to be correlated with the idiosyncratic error terms. We propose a two-step profile …

This paper develops two instrumental variable (IV) estimators for dynamic panel data
models with exogenous covariates and a multifactor error structure when both the cross …

This paper analyses the instrumental variables (IV) approach put forward by Norkute et al.,
in the context of static linear panel data models with interactive effects present in the error …

The global financial crisis and Covid‐19 recession have renewed discussion concerning
trend‐cycle discovery in macroeconomic data, and boosting has recently upgraded the …