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Who Hires Whom? Entrepreneurial Backgrounds and Labor Market Opportunities

July 2026

Written by: Josh Feng, Xavier Jaravel

Working Paper Number:

CES-26-45

Abstract

What are the implications of unequal access to entrepreneurial careers for labor markets? Using data from the U.S. Census and LinkedIn profiles, we document that entrepreneurs are significantly more likely to hire workers from similar social backgrounds (gender, race, age, education, etc.). These effects are quantitatively large across several demographic dimensions. For example, female employee share at female-founded startups is 36.4pp higher after controlling for industry-by-metro area-by-cohort fixed effects, with corresponding estimates of 51.2pp for Blacks, 37.3pp for Hispanics, and 11.3pp for non-college individuals. Large effects are present in high-growth startups, across industries and occupations, and remain stable across new firm cohorts. In addition, we find that these differences persist out to at least 20 years. We use wage data and an AKM research design to untangle whether the relative differences are driven by labor demand or labor supply effects. We find that demand drives the differences: group-specific wage decompositions show that new firms pay higher relative wages to individuals from similar backgrounds to the entrepreneur. Using these estimates, we calibrate a model of entrepreneurship with heterogeneous ability and production functions, and assess the impacts on relative wage from reducing access barriers to entrepreneurship.

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employ, entrepreneurial, black, entrepreneur, entrepreneurship, minority, labor, hispanic, proprietor, employment growth, heterogeneity, hiring, hire, socioeconomic, earner

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:
Metropolitan Statistical Area, Bureau of Labor Statistics, Center for Economic Studies, Decennial Census, Economic Census, North American Industry Classification System, Patent and Trademark Office, Alfred P Sloan Foundation, Longitudinal Employer Household Dynamics, AKM, NBER Summer Institute, Census Bureau Disclosure Review Board, Disclosure Review Board, Federal Statistical Research Data Center

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