High-Tech Entrepreneurship

Schumpeterian entrepreneurship is particularly prominent in high-tech industries where new ideas generated from advanced knowledge are of great importance. But case studies notwithstanding, the data used to analyze entrepreneurship have been dominated by startups in low-growth, low-tech industries. In this paper, we use a novel data set on scientists and engineers and a novel strategy in which we pare down the sample to those whose jobs are related to their education to better identify potential high-tech startups. We develop a simple model in which entry into and rewards from entrepreneurship are determined by the interaction of ability, the quality of the entrepreneurial idea, and experience in employment. The model yields distinctive implications about how labor market experience and earnings at work influence the probability of a high-tech worker becoming an entrepreneur, earnings as an entrepreneur, and persistence in entrepreneurship. Consistent with the model, we find that younger entrepreneurs are more likely to come from the upper tail of the paid wage distribution and that more pre-entry labor market experience is associated with better chances of continuing as an entrepreneur but also with lower earnings in entrepreneurship