Information Frictions and Employee Sorting between Startups

45 Pages Posted: 12 Sep 2022 Last revised: 22 Jul 2023

See all articles by Kevin Bryan

Kevin Bryan

University of Toronto - Strategic Management

Mitchell Hoffman

University of Toronto - Rotman School of Management; National Bureau of Economic Research (NBER)

Amir Sariri

Purdue University

Date Written: September 2022

Abstract

Would workers apply to better firms if they were more informed about firm quality? Collaborating with 26 science-based startups, we create a custom job board and invite business school alumni to apply. The job board randomizes across applicants to show coarse expert ratings of all startups’ science and/or business model quality. Making ratings visible strongly reallocates applications toward higher-rated firms. This reallocation holds restricting to high-quality workers. Treatments operate in part by shifting worker beliefs about firms’ right-tail outcomes. Despite these benefits, workers make post-treatment bets indicating highly overoptimistic beliefs about startup success, suggesting a problem of broader informational deficits.

Suggested Citation

Bryan, Kevin and Hoffman, Mitchell and Sariri, Amir, Information Frictions and Employee Sorting between Startups (September 2022). NBER Working Paper No. w30449, Available at SSRN: https://ssrn.com/abstract=4216234

Kevin Bryan (Contact Author)

University of Toronto - Strategic Management ( email )

Canada

Mitchell Hoffman

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S1S4
Canada
6503802822 (Phone)
M5S2J6 (Fax)

HOME PAGE: http://https://sites.google.com/site/mhoffman2

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Amir Sariri

Purdue University ( email )

610 Purdue Mall
West Lafayette, IN 47907
United States

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