IDEAS home Printed from https://ideas.repec.org/p/fce/doctra/1201.html
   My bibliography  Save this paper

Fat-tail Distributions and Business-Cycle Models

Author

Listed:

Abstract

Recent empirical findings suggest that macroeconomic variables are seldom normally dis- tributed. For example, the distributions of aggregate output growth-rate time series of many OECD countries are well approximated by symmetric exponential-power (EP) den- sities, 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 sta- tistical 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.

Suggested Citation

  • Guido Ascari & Giorgio Fagiolo & Andrea Roventini, 2012. "Fat-tail Distributions and Business-Cycle Models," Documents de Travail de l'OFCE 2012-01, Observatoire Francais des Conjonctures Economiques (OFCE).
  • Handle: RePEc:fce:doctra:1201
    as

    Download full text from publisher

    File URL: http://www.ofce.sciences-po.fr/pdf/dtravail/WP2012-01.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2008. "Are output growth-rate distributions fat-tailed? some evidence from OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 639-669.
    2. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    3. Posch, Olaf, 2009. "Structural estimation of jump-diffusion processes in macroeconomics," Journal of Econometrics, Elsevier, vol. 153(2), pages 196-210, December.
    4. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, Oxford University Press, vol. 121(3), pages 823-866.
    5. Giulio Bottazzi & Angelo Secchi, 2006. "Maximum Likelihood Estimation of the Symmetric and Asymmetric Exponential Power Distribution," LEM Papers Series 2006/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Giorgio Fagiolo & Mauro Napoletano & Marco Piazza & Andrea Roventini, 2009. "Detrending and the Distributional Properties of U.S. Output Time Series," Economics Bulletin, AccessEcon, vol. 29(4), pages 3155-3161.
    7. Carolina Castaldi & Giovanni Dosi, 2009. "The patterns of output growth of firms and countries: Scale invariances and scale specificities," Empirical Economics, Springer, vol. 37(3), pages 475-495, December.
    8. Canning, D. & Amaral, L. A. N. & Lee, Y. & Meyer, M. & Stanley, H. E., 1998. "Scaling the volatility of GDP growth rates," Economics Letters, Elsevier, vol. 60(3), pages 335-341, September.
    9. Giulio Bottazzi & Angelo Secchi, 2003. "Sectoral Specifities in the Dynamics of U.S. Manufacturing Firms," LEM Papers Series 2003/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    10. Carolina Castaldi & Sandro Sapio, 2008. "Growing like mushrooms? Sectoral evidence from four large European economies," Journal of Evolutionary Economics, Springer, vol. 18(3), pages 509-527, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthias Duschl & Thomas Brenner, 2013. "Characteristics of regional industry-specific employment growth rates' distributions," Papers in Regional Science, Wiley Blackwell, vol. 92(2), pages 249-270, June.
    2. Giorgio Fagiolo & Mauro Napoletano & Marco Piazza & Andrea Roventini, 2009. "Detrending and the Distributional Properties of U.S. Output Time Series," Economics Bulletin, AccessEcon, vol. 29(4), pages 3155-3161.
    3. Giulio Bottazzi & Angelo Secchi, 2011. "A new class of asymmetric exponential power densities with applications to economics and finance," Industrial and Corporate Change, Oxford University Press, vol. 20(4), pages 991-1030, August.
    4. Dosi, Giovanni & Roventini, Andrea & Russo, Emanuele, 2019. "Endogenous growth and global divergence in a multi-country agent-based model," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 101-129.
    5. Giulio Bottazzi & Marco Duenas, 2012. "The Evolution of the Business Cycles and Growth Rates Distributions," LEM Papers Series 2012/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Matthias Duschl & Thomas Brenner, 2011. "Characteristics of Regional Industry-specific Employment Growth – Empirical Evidence for Germany," Working Papers on Innovation and Space 2011-07, Philipps University Marburg, Department of Geography.
    7. Campi, Mercedes & Dueñas, Marco, 2020. "Volatility and economic growth in the twentieth century," Structural Change and Economic Dynamics, Elsevier, vol. 53(C), pages 330-343.
    8. Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2008. "Are output growth-rate distributions fat-tailed? some evidence from OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 639-669.
    9. Mauro Napoletano & Jean-Luc Gaffard & Zakaria Babutsidze, 2012. "Agent Based Models: A New Tool for Economic and Policy Analysis," Sciences Po publications info:hdl:2441/121881fn7h9, Sciences Po.
    10. Carolina Castaldi & Giovanni Dosi, 2007. "The patterns of output growth of firms and countries: new evidence on scale invariances and scale specificities," LEM Papers Series 2007/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Williams, Michael A. & Baek, Grace & Li, Yiyang & Park, Leslie Y. & Zhao, Wei, 2017. "Global evidence on the distribution of GDP growth rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 750-758.
    12. Carolina Castaldi & Giovanni Dosi, 2009. "The patterns of output growth of firms and countries: Scale invariances and scale specificities," Empirical Economics, Springer, vol. 37(3), pages 475-495, December.
    13. Mauro Napoletano & Jean-Luc Gaffard & Zakaria Babutsidze, 2012. "Agent Based Models A New Tool for Economic and Policy Analysis: A New Tool for Economic and Policy Analysis," Sciences Po publications 3, Sciences Po.
    14. Miguel Carvalho & António Rua, 2014. "Extremal Dependence in International Output Growth: Tales from the Tails," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 605-620, August.
    15. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    16. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Tania Treibich, 2019. "Debunking the granular origins of aggregate fluctuations: from real business cycles back to Keynes," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 67-90, March.
    17. Posch, Olaf, 2009. "Structural estimation of jump-diffusion processes in macroeconomics," Journal of Econometrics, Elsevier, vol. 153(2), pages 196-210, December.
    18. Shana M. Sundstrom & Craig R. Allen & David G. Angeler, 2020. "Scaling and discontinuities in the global economy," Journal of Evolutionary Economics, Springer, vol. 30(2), pages 319-345, April.
    19. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
    20. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.

    More about this item

    Keywords

    Growth-Rate Distributions; Normality; Fat Tails; Time Series; Exponential- Power Distributions; Laplace Distributions; DSGE Models; RBC Models.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fce:doctra:1201. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Francesco Saraceno). General contact details of provider: http://edirc.repec.org/data/ofcspfr.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.