Working Paper: NBER ID: w21639
Authors: Christopher Goetz; Henry Hyatt; Erika McEntarfer; Kristin Sandusky
Abstract: In this paper, we highlight the potential for linked employer-employee data to be used in entrepreneurship research, describing new data on business start-ups, their founders and early employees, and providing examples of how they can be used in entrepreneurship research. Linked employer-employee data provides a unique perspective on new business creation by combining information on the business, workforce, and individual. By combining data on both workers and firms, linked data can investigate many questions that owner-level or firm-level data cannot easily answer alone - such as composition of the workforce at start-ups and their role in explaining business dynamics, the flow of workers across new and established firms, and the employment paths of the business owners themselves.
Keywords: entrepreneurship; linked employer-employee data; business startups; workforce dynamics
JEL Codes: J21; L26
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| workforce composition (J21) | startup success (M13) |
| labor market agglomeration (J49) | entrepreneurship (M13) |
| flow of workers from established firms (J63) | startups (M13) |
| prior employment history (J63) | startup outcomes (L26) |
| human capital (J24) | startup outcomes (L26) |
| workforce demographics (J21) | entrepreneurial activity (L26) |