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 …

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 paper notes a simple connection between synthetic control and online learning.
Specifically, we recognize synthetic control as an instance of Follow‐The‐Leader (FTL) …

This paper studies inference on treatment effects in panel data settings with unobserved
confounding. We model outcome variables through a factor model with random factors and …

We study the estimation of treatment effects of a binary policy in environments with a
staggered treatment rollout. We propose a new estimator--Sequential Synthetic Difference in …

Despite the importance of denoising in modern machine learning and ample empirical work
on supervised denoising, its theoretical understanding is still relatively scarce. One concern …

We develop an estimator for applications where the variable of interest is endogenous and
researchers have access to aggregate instruments. Our method addresses the critical …

We present a method of parameter estimation for large class of nonlinear systems, namely
those in which the state consists of output derivatives and the flow is linear in the parameter …

We propose a synthetic difference-in-difference estimator that incorporates time-varying
covariates. We incorporate covariates into a high-dimensional least squares with correlated …

Untitled Page 1 Page 2 Essays in Econometrics A dissertation presented by Jiafeng Chen to
The Department of Economics in partial fulfillment of the requirements for the degree of …