关键词:
Business Cycles
Entrepreneurship
Skewness
Skill Bias Technical Change
Uncertainty
摘要:
This dissertation consists of three chapters. In the first essay of my thesis, I document a marked declined in the share of entrepreneurial households in the United States and I propose and quantify a mechanism to account for such decline. Using individual-level data, I provide evidence on the decline in the population share of entrepreneurs and in the entry rate into entrepreneurship. I also show that the decline is most concentrated among college graduates. Then, using an otherwise standard entrepreneurial choice model with two skill groups of individuals, I show that the decline in entrepreneurship is the equilibrium outcome of two forces that have increased the returns to high skill labor: the skill-biased technical change and the decrease in the cost of capital goods. I find that these two technological forces jointly account for three-quarters of the decline in the share of entrepreneurs observed in the United States over the last 30 years. In the second essay of this thesis, Nicholas Bloom, Fatih Guvenen, and I study the cyclicality the distribution of firm-leve outcomes over the business cycle. Using firm-level panel data from the US Census and for more than forty other countries, we show that the skewness of the growth rate of employment and sales is procyclical. In particular, during recessions, they display a large left tail of negative growth rates (and during booms, a large right tail of positive growth rates). These results are robust to different selection criteria, across countries, industries, and measures. We find similar results at the industry level: industries with falling growth rates see more left-skewed growth rates of firm sales. We then build a heterogeneous agents model in which entrepreneurs face shocks with time-varying skewness that matches the firm-level distributions we document for the United States. Our quantitative results show that a negative shock to the skewness of firms’ productivity growth (keeping the mean and variance consta