<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T13:32:06Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/118047" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/118047</identifier><datestamp>2026-06-16T18:52:34Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Arnaud Costinot, David Atkin and Abhijit Banerjee.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Miyauchi, Yuhei</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Economics.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Economics</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-09-17T15:55:12Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2018-09-17T15:55:12Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/118047</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1051459429</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2018.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 167-175).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">This thesis consists of three chapters that analyze how the networks of firms, people, and locations shape socio-economic activities. The first chapter analyzes the role of supplier to buyer matching in the firm-to-firm trade as a source of geographic concentration of economic activities. Using a panel of firm-to-firm trade data covering over a million Japanese firms, I first provide evidence that the new supplier matching rate upon unexpected supplier bankruptcies increases in locations and industries when there are more alternative suppliers selling in the buyer's location, while this rate remains stable in the presence of other buyers looking for a match. I then estimate a new structural trade model that incorporates dynamic firm-to-firm matching across space in a standard Melitz model and concludes that this agglomeration mechanism drives a large part of spatial inequality of firm density and real wages in Japan. The second chapter (co-authored with Gabriel Kreindler) investigates how people's mobility patterns are associated with urban spatial economic activities. We use cell phone transaction data to extract commuting flows at a fine spatially and temporarily scale, and use a model to empirically associate commuting flows with spatial economic activity distributions in Bangladesh and Sri Lanka. We validate our predicted measures of economic activities with a government survey and show several applications to provide a proof of concept of our approach. The third chapter develops an econometric framework to estimate structural parameters underlying a network formation model. I show that the set of equilibria is a complete lattice under certain conditions, and extend this characterization to an econometric framework based on the moment inequality model. I then apply this method to a student friendship network formation in the U.S.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Yuhei Miyauchi.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">175 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Economics.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Essays on economic geography and networks</dim:field>
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   	&lt;Title>Essays on economic geography and networks&lt;/Title>
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   	&lt;PublicationDate>2018&lt;/PublicationDate>
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        	&lt;DisplayName>Miyauchi, Yuhei&lt;/DisplayName>
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    &lt;Keyword>Economics.&lt;/Keyword>
   	&lt;Abstract>This thesis consists of three chapters that analyze how the networks of firms, people, and locations shape socio-economic activities. The first chapter analyzes the role of supplier to buyer matching in the firm-to-firm trade as a source of geographic concentration of economic activities. Using a panel of firm-to-firm trade data covering over a million Japanese firms, I first provide evidence that the new supplier matching rate upon unexpected supplier bankruptcies increases in locations and industries when there are more alternative suppliers selling in the buyer&amp;apos;s location, while this rate remains stable in the presence of other buyers looking for a match. I then estimate a new structural trade model that incorporates dynamic firm-to-firm matching across space in a standard Melitz model and concludes that this agglomeration mechanism drives a large part of spatial inequality of firm density and real wages in Japan. The second chapter (co-authored with Gabriel Kreindler) investigates how people&amp;apos;s mobility patterns are associated with urban spatial economic activities. We use cell phone transaction data to extract commuting flows at a fine spatially and temporarily scale, and use a model to empirically associate commuting flows with spatial economic activity distributions in Bangladesh and Sri Lanka. We validate our predicted measures of economic activities with a government survey and show several applications to provide a proof of concept of our approach. The third chapter develops an econometric framework to estimate structural parameters underlying a network formation model. I show that the set of equilibria is a complete lattice under certain conditions, and extend this characterization to an econometric framework based on the moment inequality model. I then apply this method to a student friendship network formation in the U.S.&lt;/Abstract>
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