I am a PhD candidate in the Department of Economics at NYU.
I am currently on the job market.
Fields: macroeconomics, entrepreneurship and international trade.
Recent research shows that entrepreneurial activity has been declining in the US in recent decades. Given the role of entrepreneurship in theories of growth, job creation and economic mobility this has generated considerable concern. This paper investigates why entrepreneurship has declined. It documents that (1) the decline in entrepreneurship has been more pronounced for higher education levels, implying that at least part of the force driving the changes is not skill-neutral, and (2) the size distribution of entrepreneur businesses has been quite stable. Together with a decline in the entrepreneurship rate the second fact implies a shift of economic activity towards non-entrepreneur firms. Guided by this evidence I evaluate explanations for the decline in entrepreneurship based on skill-biased technical change, increases in the fixed costs of businesses which could be due to technological change or increases in regulations, and changes in technology that have benefited large non-entrepreneur firms. I do this using a general equilibrium model of occupational choice calibrated with a rich set of moments on occupations, income distributions and firm size distributions. I find that an increase in fixed costs explains most of the decline in the aggregate entrepreneurship rate and that skill-biased technical change can fully account for the larger decrease in entrepreneurship for more educated people when combined with the other forces.
One of the primary innovations in modern business cycle research is the idea that uncertainty shocks drive aggregate fluctuations. But changes in stock prices (VIX), disagreement among macro forecasters, and the cross-sectional dispersion in firms' earnings, while all used to measure uncertainty, are not the same, either conceptually or statistically. Are these really measuring the same phenomenon and not just a collection of counter-cyclical second moments? If so, what is this shock that has such diverse impacts on the economy? Statistically, there is some rationale for naming all uncertainty shocks. There exists a subset of commonly-used uncertainty measures that comove significantly, above and beyond what the cycle alone could explain. Therefore, we explore a mechanism that generates micro dispersion (cross-sectional variance of firm-level outcomes), higher-order uncertainty (disagreement) and macro uncertainty (uncertainty about macro outcomes) from a change in macro volatility. The mechanism succeeds quantitatively, causing uncertainty measures to covary, just as they do in the data. If we want to continue the practice of naming these changes all ''uncertainty shocks,'' these results provide guidance about what such a shock might actually entail.