Recent empirical findings suggest that macroeconomic variables are seldom normally distributed. For example, the distributions of aggregate output growth-rate time series of many OECD countries are well approximated by symmetric exponential-power (EP) densities with Laplace fat tails. In this work, we assess whether real business cycle (RBC) and standard medium-scale New Keynesian (NK) models are able to replicate this statistical regularity. We simulate both models, drawing Gaussian- vs Laplace-distributed shocks, and we explore the statistical properties of simulated time series. Our results cast doubts on whether RBC and NK models are able to provide a satisfactory representation of the transmission mechanisms linking exogenous shocks to macroeconomic dynamics.
Fat-tail distributions and business-cycle models
ROVENTINI, Andrea
2013-01-01
Abstract
Recent empirical findings suggest that macroeconomic variables are seldom normally distributed. For example, the distributions of aggregate output growth-rate time series of many OECD countries are well approximated by symmetric exponential-power (EP) densities with Laplace fat tails. In this work, we assess whether real business cycle (RBC) and standard medium-scale New Keynesian (NK) models are able to replicate this statistical regularity. We simulate both models, drawing Gaussian- vs Laplace-distributed shocks, and we explore the statistical properties of simulated time series. Our results cast doubts on whether RBC and NK models are able to provide a satisfactory representation of the transmission mechanisms linking exogenous shocks to macroeconomic dynamics.
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