Abstract:

There is a consensus among economists that a formal analysis of entrepreneurship has not yet been adequately incorporated into economics. In this dissertation study we take a small step towards developing new insights and analytical tools that would contribute to this goal.

In the first essay we pose the question of what entrepreneurs do to create economic value by focusing on occupations where entrepreneurial activities involve learning, adopting and implementing advanced technical knowledge. We construct a model where entrepreneurs possessing sufficiently high skills in and knowledge about advanced technology earn a positive premium, while those who locate far away from their set of skills in the technology space earn negative returns.

The second essay examines the roles of comparative advantage, learning and human capital in workers' mobility between entrepreneurial and non-entrepreneurial sectors as well as the implications of these for the evolution of the entrepreneurship premium over a life-cycle. The model demonstrates that highly-talented young individuals are drawn into entrepreneurship when intensive use of specialized technical knowledge is required to perform their jobs.

The implications of each model in the two essays are empirically examined by using the NSF database of Science and Engineering Statistical Data System (SESTAT).

Past empirical studies of entrepreneurship have documented (i)?negative pecuniary returns to entrepreneurship and (ii)?the sorting pattern according to which less talented individuals become entrepreneurs. In most of these studies, the heterogeneity of self-employed with respect to their human capital and skills has not been considered to any meaningful degree. In the theory of this dissertation study, returns to entrepreneurship and the pattern of sorting depend crucially on whether entrepreneurs' human capital is high enough or not to employ advanced technical knowledge in their jobs. The empirical part of this dissertation study uses SESTAT to actually distinguish between these two types of entrepreneurs in the data. Empirical results based on this strategy reveal that highly-talented individuals are drawn into the self-employment sector and earn positive pecuniary returns only if they intensively use advanced technical knowledge.