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Scott Stern. Wu, Jane Yajie Massachusetts Institute of Technology Sloan School of Management. Sloan School of Management 2018-09-17T15:53:12Z 2018-09-17T15:53:12Z 2018 2018 http://hdl.handle.net/1721.1/117998 1051300111 Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-34). Venture capitalists have been shown to be more likely to invest in entrepreneurs of the same ethnicity. At the same time, this result rests on assumptions about how shared ethnicity is defined both theoretically and empirically. Current measurement of ethnic ties is problematic due to mis-classifications, mixed heritage individuals, and variation in accuracy by ethnicity. This paper overcomes these limitations by taking advantage of a novel source of data -- face photographs -- and by applying advanced machine learning techniques to compute the facial similarity between investors and entrepreneurs in a large scale dataset of realized and potential investments. Results suggest that previous work has vastly underestimated the relationship between ethnic ties and investment. Moreover, this relationship is more nuanced than previously documented, varies with the stage of investment and the type of investors involved, and is associated with a lower likelihood of securing follow-on funding or achieving an exit. by Jane Y. Wu. S.M. in Management Research 70 pages eng Massachusetts Institute of Technology 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. http://dspace.mit.edu/handle/1721.1/7582 Sloan School of Management. Face distance : unpacking the role of ethnic ties in venture capital investment Unpacking the role of ethnic ties in venture capital investment Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="f963f5be-856c-4021-aa65-5bd5985ce3e6"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Face distance : unpacking the role of ethnic ties in venture capital investment</Title> <Subtitle>Unpacking the role of ethnic ties in venture capital investment</Subtitle> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <Authors> <Author> <DisplayName>Wu, Jane Yajie Massachusetts Institute of Technology</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Sloan School of Management.</Keyword> <Abstract>Venture capitalists have been shown to be more likely to invest in entrepreneurs of the same ethnicity. At the same time, this result rests on assumptions about how shared ethnicity is defined both theoretically and empirically. Current measurement of ethnic ties is problematic due to mis-classifications, mixed heritage individuals, and variation in accuracy by ethnicity. This paper overcomes these limitations by taking advantage of a novel source of data -- face photographs -- and by applying advanced machine learning techniques to compute the facial similarity between investors and entrepreneurs in a large scale dataset of realized and potential investments. Results suggest that previous work has vastly underestimated the relationship between ethnic ties and investment. Moreover, this relationship is more nuanced than previously documented, varies with the stage of investment and the type of investors involved, and is associated with a lower likelihood of securing follow-on funding or achieving an exit.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>