<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Causal Inference | Junyao He | Academic Portfolio</title><link>https://junyaohe001.github.io/tags/causal-inference/</link><atom:link href="https://junyaohe001.github.io/tags/causal-inference/index.xml" rel="self" type="application/rss+xml"/><description>Causal Inference</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><image><url>https://junyaohe001.github.io/media/icon_hu14599980757415029838.png</url><title>Causal Inference</title><link>https://junyaohe001.github.io/tags/causal-inference/</link></image><item><title>Teleworkability and the Evolution of Job-Home Networks after the COVID-19 Shock: Causal Evidence from the Netherlands</title><link>https://junyaohe001.github.io/working-papers/teleworkability-job-home-networks/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://junyaohe001.github.io/working-papers/teleworkability-job-home-networks/</guid><description>&lt;p>&lt;strong>Status:&lt;/strong> Under review&lt;/p>
&lt;p>This article examines how actual remote-work patterns reshaped Dutch municipal job-home networks after the COVID-19 shock. It uses spatial difference-in-differences models and Bartik shift-share designs to estimate direct and spillover effects on commuting relations, employment-residence linkages, and urban-regional network structure.&lt;/p></description></item></channel></rss>