11 citations · 15 across the 7 of their papers we have counts for
5 papers · 1 filter
Robust Priors in Nonlinear Panel Models with Individual and Time Effects
Zizhong Yan, Zhengyu Zhang, Mingli Chen +2
We develop likelihood-based bias reduction for nonlinear panel models with additive individual and time effects. In two-way panels, integrated-likelihood corrections are attractive…
Comment on "Sequential validation of treatment heterogeneity" and "Comment on generic machine learning inference on heterogeneous treatment effects in randomized experiments"
Victor Chernozhukov, Mert Demirer, Esther Duflo +1
We warmly thank Kosuke Imai, Michael Lingzhi Li, and Stefan Wager for their gracious and insightful comments. We are particularly encouraged that both pieces recognize the importan…
Philip G. Wright, directed acyclic graphs, and instrumental variables
Jaap H. Abbring, Victor Chernozhukov, Iván Fernández-Val
Wright (1928) deals with demand and supply of oils and butter. In Appendix B of this book, Philip Wright made several fundamental contributions to causal inference. He introduced a…
Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
Victor Chernozhukov, Iván Fernández-Val, Sukjin Han +1
We propose an instrumental variable framework for identifying and estimating causal effects of discrete and continuous treatments with binary instruments. The basis of our approach…
Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models
Victor Chernozhukov, Iván Fernández-Val, Chen Huang +1
The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice. It can be severely biased when the time series dimension of the data, $T…