How do output growth-rate distributions look like? Some cross-country, time-series evidence
AbstractThis paper investigates the statistical properties of within-country gross domestic product (GDP) and industrial production (IP) growth-rate distributions. Many empirical contributions have recently pointed out that cross-section growth rates of firms, industries and countries all follow Laplace distributions. In this work, we test whether also within-country, time-series GDP and IP growth rates can be approximated by tent-shaped distributions. We fit output growth rates with the exponential-power (Subbotin) family of densities, which includes as particular cases both Gaussian and Laplace distributions. We find that, for a large number of OECD (Organization for Economic Cooperation and Development) countries including the US, both GDP and IP growth rates are Laplace distributed. Moreover, we show that fat-tailed distributions robustly emerge even after controlling for outliers, autocorrelation and heteroscedasticity. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007
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Bibliographic InfoArticle provided by Springer in its journal The European Physical Journal B.
Volume (Year): 57 (2007)
Issue (Month): 2 (05)
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Web page: http://www.springer.com/economics/journal/10051
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- Corrado Di Guilmi & Mauro Gallegati & Edoardo Gaffeo, 2003. "Power Law Scaling in the World Income Distribution," Economics Bulletin, AccessEcon, vol. 15(6), pages 1-7.
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