Fat-Tail Distributions and Business-Cycle Models

Guido Ascari, Giorgio Fagiolo () and Andrea Roventini

No 02/2012, Working Papers from University of Verona, Department of Economics

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 Model (search for similar items in EconPapers)
JEL-codes: C1 E3 (search for similar items in EconPapers)
Pages: 14
Date: 2012-01
New Economics Papers: this item is included in nep-bec, nep-dge and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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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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