<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fan Wu | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/fan-wu/</link><description>Fan Wu</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/fan-wu/index.xml" rel="self" type="application/rss+xml"/><item><title>Competing under Information Heterogeneity: Evidence from Auto Insurance</title><link>https://macropaperwarehouse.com/papers/competing-under-information-heterogeneity-evidence-from-auto-insurance/</link><guid>https://macropaperwarehouse.com/papers/competing-under-information-heterogeneity-evidence-from-auto-insurance/</guid><description>&lt;p&gt;This paper studies imperfect competition in selection markets where competing firms have heterogeneous information about consumers — a layer of asymmetry distinct from the classic buyer-seller information gap. The central questions are: how do inter-firm information asymmetries shape equilibrium pricing, consumer sorting, and market efficiency; and whether a centralized bureau that aggregates and equalizes firms&amp;rsquo; risk information can promote competition and improve welfare.&lt;/p&gt;
&lt;p&gt;The empirical setting is the Italian mandatory motor vehicle liability insurance market (Responsabilità Civile Auto). The authors use the IPER dataset from IVASS, a nationally representative panel of matched insurer-insuree contracts covering 124,428 liability insurance contracts for new customers in the province of Rome from 2013 to 2021. The panel tracks consumers across insurer switches, enabling construction of individual-specific risk estimates from ex-post claim records using Poisson regressions for claim frequency and log-normal regressions for claim severity. The analysis focuses on the top 10 largest firms plus a composite fringe firm.&lt;/p&gt;</description></item></channel></rss>