This survey discusses the recent causal panel data literature. This recent literature has focused on credibly estimating causal effects of binary interventions in settings with longitudinal data, with an emphasis on practical advice for empirical researchers. It pays particular attention to...

We evaluate the 2017 Tax Cuts and Jobs Act. Combining reduced-form estimates from tax data with a global investment model, we estimate responses, identify parameters, and conduct counterfactuals. Domestic investment of firms with the mean tax change increases 20% versus a no-change baseline. Due...

We construct a dynamic general equilibrium model of foreign direct investment (FDI) and foreign technology adoption, incorporating adoption barriers, international technology spillover, and relative price advantages. A higher FDI conversion efficacy, a lower adoption barrier, or a stronger...

During the recovery from the COVID-19 pandemic, international shipping and logistics capacity was strained, limiting the quantity of imports. We investigate the impact of an import constraint on inflation, following an increase in domestic demand. Whether the binding import constraint raises...

We build a general equilibrium production-based asset pricing model with heterogeneous firms that jointly accounts for firm-level and aggregate facts emphasized by the recent macroeconomic literature, and for important asset pricing moments. Using administrative firm-level data, we establish...

Motivated by a recent literature on the double-descent phenomenon in machine learning, we consider highly over-parameterized models in causal inference, including synthetic control with many control units. In such models, there may be so many free parameters that the model fits the training data...

This paper analyzes difference-in-differences designs with a continuous treatment. We show that treatment effect on the treated-type parameters can be identified under a generalized parallel trends assumption that is similar to the binary treatment setup. However, interpreting differences in...

This paper introduces the concept of a "trimmed aggregate ATT," which is a weighted average of a set of group-time average treatment effect on the treated (ATT) parameters identified in a staggered adoption difference-in-differences (DID) design. The set of identified group-time ATTs that...

We develop an optimal policy assignment rule that integrates two distinctive approaches commonly used in economics--targeting by observables and targeting through self-selection. Our method can be used with experimental or quasi-experimental data to identify who should be treated, be untreated,...

We study identification and estimation of causal effects in settings with panel data. Traditionally researchers follow model-based identification strategies relying on assumptions governing the relation between the potential outcomes and the unobserved confounders. We focus on a novel,...