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Further Evidence on the Statistical Properties of Real GNP

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  • Laura Mayoral

Abstract

The well-known lack of power of unit-root tests has often been attributed to the short length of macroeconomic variables and also to data-generating processes (DGPs) departing from the "I"(1)-"I"(0) models. This paper shows that by using long spans of annual real gross national product (GNP) and GNP per capita (133 years), high power can be achieved, leading to the rejection of both the unit-root and the trend-stationary hypothesis. More flexible representations are then considered, namely, processes containing structural breaks (SB) and fractional orders of integration (FI). Economic justification for the presence of these features in GNP is provided. It is shown that both FI and SB formulations are in general preferred to the autoregressive integrated moving average (ARIMA) ["I"(1) or "I"(0)] formulations. As a novelty in this literature, new techniques are applied to discriminate between FI and SB. It turns out that the FI specification is preferred, implying that GNP and GNP per capita are non-stationary, highly persistent but mean-reverting series. Finally, it is shown that the results are robust when breaks in the deterministic component are allowed for in the FI model. Some macroeconomic implications of these findings are also discussed. Copyright 2006 Blackwell Publishing Ltd.

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.

Volume (Year): 68 (2006)
Issue (Month): s1 (December)
Pages: 901-920

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Handle: RePEc:bla:obuest:v:68:y:2006:i:s1:p:901-920

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Cited by:
  1. Gilles Dufrénot & Valérie Mignon & Théo Naccache, . "The slow convergence of per capita income between the developing countries: “growth resistance” and sometimes “growth tragedy”," Discussion Papers 09/03, University of Nottingham, CREDIT.
  2. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," CESifo Working Paper Series 2671, CESifo Group Munich.
  3. Guglielmo Maria Caporale & Marinko Skare, 2014. "Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis," Discussion Papers of DIW Berlin 1395, DIW Berlin, German Institute for Economic Research.
  4. Gianluca, MORETTI & Giulio, NICOLETTI, 2008. "Estimating DGSE models with long memory dynamics," Discussion Papers (ECON - Département des Sciences Economiques) 2008037, Université catholique de Louvain, Département des Sciences Economiques.
  5. Ivan Kitov, 2012. "Why price inflation in developed countries is systematically underestimated," Papers 1206.0450, arXiv.org.
  6. Marco Barassi & Matthew Cole & Robert Elliott, 2011. "The Stochastic Convergence of CO 2 Emissions: A Long Memory Approach," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 49(3), pages 367-385, July.

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