Emin Dinlersoz, Timothy Dunne, John Haltiwanger, and Veronika Penciakova
Working Paper 2023-9
What locations generate more business ideas, and where are ideas more likely to turn into businesses? Using comprehensive administrative data on business applications, we analyze the spatial disparity in the creation of business ideas and the formation of new employer startups from these ideas. Startups per capita exhibit enormous variation across granular units of geography. We decompose this variation into variation in ideas per capita and in their rate of transition to startups, and we find that both components matter. Observable local demographic, economic, financial, and business conditions account for a significant fraction of the variation in startups per capita—and more so for the variation in ideas per capita than in transition rate. Income, education, age, and foreign-born share are generally strong positive correlates of both idea generation and transition. Overall, the relationship of local conditions with ideas differs from that with transition rate in magnitude and, sometimes, in sign: certain conditions (notably, the African American share of the population) are positively associated with ideas but negatively with transition rates. We also find a close correspondence between the actual rank of locations in terms of startups per capita and the predicted rank based only on observable local conditions—a result useful for characterizing locations with high startup activity.
JEL classification: L26, R12, R23
Key words: entrepreneurship, firm entry, business formation, business dynamism, economic geography
All results have been reviewed to ensure that no confidential information is disclosed (CBDRB-FY22-022 and CBDRB-FY23-055). The authors thank Richard Beem, Shawn Klimek, and participants at the 2021 and 2022 Southern Economic Association conference and the University of North Carolina Kenan-Flagler Business School finance seminar for helpful comments. John Haltiwanger was also a Schedule A employee of the US Census Bureau at the time of the writing of this paper. The authors also thank the Templeton Foundation for financial support. The views expressed here are those of the authors and not necessarily those of the US Census Bureau, the Federal Reserve Bank of Atlanta, or the Federal Reserve System. Any remaining errors are the authors' responsibility.
Please address questions regarding content to Emin Dinlersoz, US Census Bureau; Timothy Dunne, University of Notre Dame; John Haltiwanger, University of Maryland; or Veronika Penciakova, Federal Reserve Bank of Atlanta.
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