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Industry Choices and Social Interactions of Entrepreneurs: Identification by Residential Addresses


  • Rocco Huang

    (University of Amsterdam)


This paper shows that industry choices of entrepreneurs are determined by their social networks. The separation of residential and business addresses helps us establish the causality, because we can safely argue that residential addresses determine social networks but do not directly affect industry choices. In a large cross-section of London neighborhoods (average area: one squared-mile), we show that new generation of entrepreneurs are more likely to enter industries overrepresented by their residential neighbors. We further show that industry composition of a neighborhood is more persistent when social interactions are more intensive and of higher quality, as proxied by higher ethnic homogeneity, more sociable housing structures, or higher entrepreneurial population density. The effect is also stronger in industries that require more informational interactions, as proxied by greater geographic agglomeration of entrepreneurs. The median home- business distances in our sample is nearly six kilometers, thus the persistence of a neighborhood’s industry specialization is unlikely to be driven by unobservable common product market conditions. We also control for industry specialization at borough level (each borough contains around 20 neighborhoods), to further remove the effects of unobservable factors. Finally, we also use various sub-groups of entrepreneurs to test for a series of alternative hypotheses, and we do not find support for them. We do not find failure rates to be significantly different for entrepreneurs who follow their neighbors’ popular choices. Overall, the results suggest that entry of new entrepreneurs tend to reinforce agglomeration, while exits do not reverse it. These evidences (weakly) lend support to the existence of agglomeration economies.

Suggested Citation

  • Rocco Huang, 2005. "Industry Choices and Social Interactions of Entrepreneurs: Identification by Residential Addresses," Labor and Demography 0507010, University Library of Munich, Germany, revised 14 Sep 2005.
  • Handle: RePEc:wpa:wuwpla:0507010
    Note: Type of Document - pdf; pages: 48

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    References listed on IDEAS

    1. Brock, William A. & Durlauf, Steven N., 2001. "Interactions-based models," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 54, pages 3297-3380 Elsevier.
    2. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    3. Lei Feng & Mark S. Seasholes, 2004. "Correlated Trading and Location," Journal of Finance, American Finance Association, vol. 59(5), pages 2117-2144, October.
    4. Cole, Harold L & Mailath, George J & Postlewaite, Andrew, 1992. "Social Norms, Savings Behavior, and Growth," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1092-1125, December.
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    JEL classification:

    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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