<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Counterfactual Analysis |</title><link>https://www.khaichiong.com/tags/counterfactual-analysis/</link><atom:link href="https://www.khaichiong.com/tags/counterfactual-analysis/index.xml" rel="self" type="application/rss+xml"/><description>Counterfactual Analysis</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 01 Jan 2021 00:00:00 +0000</lastBuildDate><image><url>https://www.khaichiong.com/media/icon_hu_da05098ef60dc2e7.png</url><title>Counterfactual Analysis</title><link>https://www.khaichiong.com/tags/counterfactual-analysis/</link></image><item><title>Counterfactual Estimation in Semiparametric Discrete‑Choice Models</title><link>https://www.khaichiong.com/publications/counterfactual-estimation-semiparametric-discrete-choice/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://www.khaichiong.com/publications/counterfactual-estimation-semiparametric-discrete-choice/</guid><description>&lt;p&gt;In this book chapter, Chiong, Hsieh, and Shum examine counterfactual estimation
techniques for semiparametric discrete‑choice models. They show how to obtain
policy‑relevant counterfactuals when only partial information about
preferences is available, illustrating the methods with examples from
industrial organization.&lt;/p&gt;</description></item></channel></rss>