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Found 7 papers, 4 papers with code
Double-Robust Two-Way-Fixed-Effects Regression For Panel Data
We propose a new estimator for the average causal effects of a binary treatment with panel data in settings with general treatment patterns.
Doubly Robust Identification for Causal Panel Data Models
We focus on a different, complementary approach to identification where assumptions are made about the connection between the treatment assignment and the unobserved confounders.
Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics
In this essay I discuss potential outcome and graphical approaches to causality, and their relevance for empirical work in economics.
Methodology
Synthetic Difference in Differences
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.
Methodology
Sampling-based vs. Design-based Uncertainty in Regression Analysis
We derive standard errors that account for design-based uncertainty instead of, or in addition to, sampling-based uncertainty.
Statistics Theory Econometrics Statistics Theory
Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis
In a seminal paper Abadie, Diamond, and Hainmueller [2010] (ADH), see also Abadie and Gardeazabal [2003], Abadie et al. [2014], develop the synthetic control procedure for estimating the effect of a treatment, in the presence of a single treated unit and a number of control units, with pre-treatment outcomes observed for all units.
Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions
There are many settings where researchers are interested in estimating average treatment effects and are willing to rely on the unconfoundedness assumption, which requires that the treatment assignment be as good as random conditional on pre-treatment variables.
Methodology Econometrics Statistics Theory Statistics Theory
