This paper proposes a new theory of business cycles based on the idea that financial uncertainty shocks change the nature of innovation. When investors become more risk tolerant, they fund riskier startups with greater growth potential. As these ambitious startups grow, the initial shock propagates and generates a boom in output and employment. I develop a heterogeneous firm industry model of the US business sector with countercyclical risk premia and innovation by startups and existing firms. The quantitative implementation of the model jointly matches time series properties of stock returns and macroeconomic aggregates, as well as micro evidence on firm cohort growth over the cycle.
Journal of Public Economics, 169, 160-171 (2019)
We study how the distribution of earnings growth evolves over the business cycle in Italy. We distinguish between two sources of annual earnings growth: changes in employment time (number of weeks of employment within a year) and changes in weekly earnings. Changes in employment time generate the tails of the earnings growth distribution, and account for the its procyclical skewness. In contrast, the distribution of weekly earnings growth is close to symmetric and stable over the cycle. This suggests that the employment margin should be carefully modeled to avoid erroneous conclusions on the nature of risks underlying the individual earnings. We show that the combination of simple employment and wage processes is enough to capture the complex features of the earnings growth distribution.