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Report
Nonlinear Firm Dynamics
This paper presents empirical evidence on the nature of idiosyncratic shocks to firms and discusses its role for firm behavior and aggregate fluctuations. We document that firm-level sales and productivity are hit by heavy-tailed shocks and follow a nonlinear stochastic process, thus departing from the canonical linear. We estimate a state-of-the-art model to flexibly capture the rich dynamics uncovered in the data and characterize the drivers of nonlinear persistence and non-Gaussian shocks. We show that these features are crucial to get empirically plausible volatility and persistence of ...
Report
What Do Data on Millions of U.S. Workers Reveal about Life-Cycle Earnings Dynamics?
We study individual earnings dynamics over the life cycle using panel data on millions of U.S. workers. Using nonparametric methods, we first show that the distribution of earnings changes exhibits substantial deviations from lognormality, such as negative skewness and very high kurtosis. Further, the extent of these nonnormalities varies significantly with age and earnings level, peaking around age 50 and between the 70th and 90th percentiles of the earnings distribution. Second, we estimate nonparametric impulse response functions and find important asymmetries: positive changes for ...
Working Paper
Consumption Dynamics and Welfare Under Non-Gaussian Earnings Risk
CORRECT ORDER OF AUTHORS: Fatih Guvenen, Serdar Ozkan, and Rocio Madera. The order of coauthors has been assigned randomly using AEA’s Author Randomization Tool. Recent empirical studies document that the distribution of earnings changes displays substantial deviations from lognormality: in particular, earnings changes are negatively skewed with extremely high kurtosis (long and thick tails), and these non-Gaussian features vary substantially both over the life cycle and with the earnings level of individuals. Furthermore, earnings changes display nonlinear (asymmetric) mean reversion. In ...
Working Paper
Consumption Dynamics and Welfare Under Non-Gaussian Earnings Risk
CORRECT ORDER OF AUTHORS: Fatih Guvenen, Serdar Ozkan, and Rocio Madera. The order of coauthors has been assigned randomly using AEA’s Author Randomization Tool. Recent empirical studies document that the distribution of earnings changes displays substantial deviations from lognormality: in particular, earnings changes are negatively skewed with extremely high kurtosis (long and thick tails), and these non-Gaussian features vary substantially both over the life cycle and with the earnings level of individuals. Furthermore, earnings changes display nonlinear (asymmetric) mean reversion. In ...