"Economics brings a large set of versatile and powerful theories and methods to the study of entrepreneurship. They are usually but not always quantitative, are often based on models of optimizing behavior under uncertainty, and utilize empirical approaches founded on the econometric analysis of large and representative data samples" (pp. 2-3). Also, "it seems fair to acknowledge that the economics approach focuses on a few aspects of entrepreneurship rather than the totality of this complex phenomenon" (p. 4).
There are many building blocks for thinking the research questions that have been raised by economics of entrepreneurship:
(1) occupational choice under uncertainty, (2) credit rationing that have shaped the understanding of small business lending as well as the potential role of governments to intervene in credit markets to assist entrepreneurial start-ups, (3) innovation.
In innovation, there are two theoretical models have been particularly influential (p. 12). One is that entrepreneurs learn from a series of stochastic draws that come in from the market. Based on constantly arriving new information, entrepreneurs adjust their beliefs and their market strategies (Jovanovis, 1982). Second, it is the product life cycle and the evolution of industries in which different types of innovation are performed at different stages of firm maturity (Klepper, 1996).
Following Schumpeter's insights on innovation and entrepreneurship, literature on "patent races" has emerged that pits established firms against each other in the drive to discover new innovations that yield monopoly profits. Also, growth is enhanced through individual entrepreneurs exploiting knowledge by creating new ventures even though they are not contributing to the production of knowledge (p. 13).
The above argument provided the theoretical models, whereas in the following the canonical empirical models would be summarized.
Economics distrust individuals' declared intentions and forces them to undertake the harder but more objective task of inferring their preferences from their actual behavior. Or, economics often apply advanced and innovative statistical techniques to overcome thorny empirical problems., like sample selection bias, unobserved heterogeneity, endogeneity, and non-stationarity.
In particular, there are models: (1) discrete choice models to analyze people's participation and survival in entrepreneurship, (2) sample selection models to analyze entrepreneur's profit, (3) hazard models to analyze how long people will remain in entrepreneurship and survive in the market, (4) cointegration estimators for time series entrepreneurship data to analyze how multiple aggregate variables covary over time, (5) decomposition techniques to analyze how entrepreneurial outcomes differed between socio-economic groups, and (6) earnings functions to analyze how schooling and other human capitals influence the earnings of entrepreneurs.
No comments:
Post a Comment