Fat-Tail Distributions and Business-Cycle Models

Guido Ascari, Giorgio Fagiolo () and Andrea Roventini

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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.

Keywords: Growth-Rate Distributions; Normality; Fat Tails; Time Series; Exponential-Power Distributions; Laplace Distributions; DSGE Models; RBC Models (search for similar items in EconPapers)
Date: 2012
Note: View the original document on HAL open archive server: https://hal.science/hal-04141131
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Related works:
Journal Article: FAT-TAIL DISTRIBUTIONS AND BUSINESS-CYCLE MODELS (2015)
Working Paper: Fat-Tail Distributions and Business-Cycle Models (2012)
Working Paper: Fat-tail Distributions and Business-Cycle Models (2012)
Working Paper: Fat-Tail Distributions and Business-Cycle Models (2012)
Working Paper: Fat-Tail Distributions and Business-Cycle Models (2012)
Working Paper: Fat-Tail Distributions and Business-Cycle Models (2012)
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