We use de-identified tax returns to characterize entrepreneurship across the American population since the late 1990s. Our longitudinal data permit an analysis of which new firms end up being highly successful, allowing us to distinguish startups that are destined to remain as small businesses from star job creators. We develop a novel measure of the returns to founding owners using a high-dimensional matching strategy, which tracks total income in the decade following entrepreneurial entry relative to that for a similar matched worker.
In the first part of the paper, we document new facts on the lifecycle of star entrepreneurs, including their family backgrounds, where they grew up, and their labor market trajectories prior to entry. Star entrepreneurs are disproportionately white, male, and drawn from high-income families. Entrepreneurship pays at the median and mean for those who choose to enter, though under-represented groups (URGs) consistently earn lower returns than their over-represented counterparts. Higher variance in entrepreneurial returns comes primarily through the outside option in the right tail of the earnings distribution.
In the second part of the paper, we develop three research designs to evaluate the role of alternative mechanisms that might account for different entry rates and returns for URGs. First, using a sample of early employees at highly successful startups, we estimate a substantial causal effect of liquid wealth on subsequent entry. However, liquidity appears insufficient to close entry gaps. Second, using local shocks to labor demand early in a person’s career, we estimate the causal effect of experience in entrepreneurial industries on subsequent entry. Finally, using a movers research design, we find that children exposed to more entrepreneurs while they are growing up are more likely to start businesses themselves.
We use these multiple research designs to decompose the reduced form effects. For example, the effect of labor market experience can be separated into a direct effect and an effect operating through accumulated savings. Our results support the class of explanations that highlight “pipeline” factors as the key supply-side constraints on the number of star URG entrepreneurs. Such factors limit the number of potential entrepreneurs who might be responsive to later-stage interventions. For example, policies that target the point of entry, such as liquidity support or tax incentives, are unlikely to close entry gaps and narrow return differences.
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