<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Yinchu Zhu | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/yinchu-zhu/</link><description>Yinchu Zhu</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/yinchu-zhu/index.xml" rel="self" type="application/rss+xml"/><item><title>Debiasing and T-Tests for Synthetic Control Inference on Average Causal Effects</title><link>https://macropaperwarehouse.com/papers/debiasing-and-t-tests-for-synthetic-control-inference-on-average-causal-effects/</link><guid>https://macropaperwarehouse.com/papers/debiasing-and-t-tests-for-synthetic-control-inference-on-average-causal-effects/</guid><description>&lt;p&gt;Chernozhukov, Wüthrich, and Zhu propose a debiased synthetic control (SC) estimator and an accompanying self-normalized t-test for making inferences on the average treatment effect on the treated (ATT) in aggregate panel data settings with one treated unit. The inferential target is the time-averaged treatment effect τ = (1/T1) Σ_{t=T0+1}^{T} (Y0t(1) − Y0t(0)), a one-number summary of the overall causal impact that admits standard-form confidence intervals, in contrast to per-period effects (which cannot be consistently estimated with one treated unit) and sharp null hypotheses (which do not inform effect magnitude).&lt;/p&gt;</description></item></channel></rss>