<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Policy Evaluation | CRiSS-LAB</title><link>https://criss-lab.com/tag/policy-evaluation/</link><atom:link href="https://criss-lab.com/tag/policy-evaluation/index.xml" rel="self" type="application/rss+xml"/><description>Policy Evaluation</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Fri, 01 Aug 2025 00:00:00 +0000</lastBuildDate><image><url>https://criss-lab.com/media/sharing.png</url><title>Policy Evaluation</title><link>https://criss-lab.com/tag/policy-evaluation/</link></image><item><title>Causal Inference for Data Science</title><link>https://criss-lab.com/teaching/causal-inference-data-science/</link><pubDate>Fri, 01 Aug 2025 00:00:00 +0000</pubDate><guid>https://criss-lab.com/teaching/causal-inference-data-science/</guid><description>&lt;p>This teaching line focuses on moving from predictive models to causal questions: what would happen under a different intervention, policy, design, or institutional decision?&lt;/p>
&lt;p>Topics include directed acyclic graphs, confounding, matching, fixed effects, difference-in-differences, regression discontinuity, instrumental variables, sensitivity analysis, and causal machine learning.&lt;/p></description></item></channel></rss>