Working Paper: CEPR ID: DP17400
Authors: Ralph de Haas; Vincent Sterk; Neeltje van Horen
Abstract: We construct a new and comprehensive data set on 1.3 million European startups. A cluster analysis identifies five distinct startup types that are consistently present across countries, industries, and cohorts. The initial differences between these startup typesare persistent and each type displays a characteristic life cycle in terms of productivity, employment, and survival. An agnostic firm dynamics model helps quantify how much structural policy could improve macroeconomic performance by shifting the compositionof startup cohorts. We show that policies benefiting high-performance startups, while discouraging the entry of underperforming firms, can yield substantial gains in aggregate employment and productivity.
Keywords: startups; entrepreneurship; firm entry; productivity; corporate tax; cluster analysis
JEL Codes: D22; D24; G32; L11; L25; L26; O47
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| structural policies aimed at improving the composition of startup cohorts (L26) | substantial macroeconomic gains (E65) |
| policies benefiting high-performance startups (M13) | overall economic performance (P47) |
| discouraging underperforming firms (L10) | overall economic performance (P47) |
| budget-neutral tax reforms differentiated by startup type (H32) | increase aggregate productivity (O49) |
| budget-neutral tax reforms differentiated by startup type (H32) | increase employment (J68) |
| higher entry rates of productive startups (L26) | improved economic outcomes (O49) |
| adjustment of firm entry rates in response to policy changes (H32) | elasticity of entry varies across startup types (L26) |
| persistent differences in performance across startup types (D29) | key driver of economic outcomes (O49) |