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Massachusetts Institute of Technology

Three essays on entrepreneurial quality

Abstract

dc:description.abstract

This dissertation introduces a new method to measure entrepreneurial quality and applies it to three questions of theoretical interest in entrepreneurship. The dissertation is presented in five chapters. Chapter 1 is an introductory chapter. It overviews the entrepreneurial quality approach, indicates the key choices made in this dissertation, and explains how researchers can build on this approach for their own applications. Chapters 2 through 4 are specific research applications. Chapter 2 uses this approach to measure the "state of American entrepreneurship" once quality is included. Chapter 3 studies differences in the quality of entrepreneurship by gender and the gender gap in VC financing conditional on quality. Chapter 4 looks at entrepreneurial migration and the quantity and quality of migrants in high growth entrepreneurship across regions. Chapter 5 provides a short conclusion. Extended abstracts are provided at the beginning of each chapter.

Degree

thesis:*
Department dc:contributor.department
Sloan School of Management.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Guzmán, Jorge (Jorge Arturo)
Advisor dc:contributor.advisor
  • Scott Stern.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/109662
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/109662

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Guzmán, Jorge (Jorge Arturo). Three essays on entrepreneurial quality. Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/109662