<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Michela Maria Tincani | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/michela-maria-tincani/</link><description>Michela Maria Tincani</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/michela-maria-tincani/index.xml" rel="self" type="application/rss+xml"/><item><title>Peer Effects and Rank Concerns in the Classroom</title><link>https://macropaperwarehouse.com/papers/peer-effects-and-rank-concerns-in-the-classroom/</link><guid>https://macropaperwarehouse.com/papers/peer-effects-and-rank-concerns-in-the-classroom/</guid><description>&lt;p&gt;This paper investigates the mechanisms behind peer effects in the classroom using exogenous variation in study disruptions generated by the 2010 Maule mega-earthquake in Chile (magnitude 8.8, the seventh-largest ever instrumentally recorded). The central research question is why classroom peers can shape academic achievement — specifically, whether beyond production complementarities and a desire to conform, a desire to compete for classroom rank can drive peer influence on learning.&lt;/p&gt;
&lt;p&gt;The author constructs a novel dataset linking administrative and survey data from Chile&amp;rsquo;s Ministry of Education (SIMCE test scores, GPA, curriculum coverage, and school expenditure records) for two cohorts of roughly 150,000 eighth-grade students — one measured in 2009 before the earthquake, one measured in 2011 roughly 20–22 months after — to newly constructed measures of housing damage. Damage to each student&amp;rsquo;s home is built in three steps: (1) ground-shaking intensity using an established attenuation formula for the 2010 earthquake; (2) seismic vulnerability of each student&amp;rsquo;s home inferred from a latent-class-analysis model trained on census data linking housing construction materials to vulnerability classes; and (3) a combined expected &amp;ldquo;damage ratio&amp;rdquo; (fraction of home that needs to be rebuilt). Identification uses a difference-in-differences strategy that exploits the differential correlation between pre-existing seismic vulnerability and outcomes across the pre- and post-earthquake cohorts, controlling for socioeconomic composition.&lt;/p&gt;</description></item></channel></rss>