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Panel data tests of PPP: a critical overview

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  • Guglielmo Maria Caporale
  • Mario Cerrato

Abstract

This study reviews recent developments in the analysis of non-stationary panels, focusing on empirical applications of panel unit root and cointegration tests in the context of PPP. It highlights various drawbacks of existing methods. First, unit root tests suffer from severe size distortions in the presence of negative moving average errors. Second, the common demeaning procedure to correct for the bias resulting from homogeneous cross-sectional dependence is not effective; more worryingly, it introduces cross-correlation when it is not already present. Third, standard corrections for the case of heterogeneous cross-sectional dependence do not generally produce consistent estimators. Fourth, if there is between-group correlation in the innovations, the SURE estimator is affected by similar problems to FGLS methods, and does not necessarily outperform OLS. Finally, cointegration between different groups in the panel could also be a source of size distortions. Some empirical guidelines are offered to deal with these problems, but the study concludes that panel methods are unlikely to solve the PPP puzzle.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

Volume (Year): 16 (2006)
Issue (Month): 1-2 ()
Pages: 73-91

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Handle: RePEc:taf:apfiec:v:16:y:2006:i:1-2:p:73-91

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Citations

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Cited by:
  1. Wagner, Martin, 2005. "On PPP, Unit Roots and Panels," Economics Series 176, Institute for Advanced Studies.
  2. Bahram Adrangi & Mary E. Allender & Kambiz Raffiee, 2011. "Exchange Rates and Inflation Rates: Exploring Nonlinear Relationships," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 1-16, April.
  3. Edward Bernard Bastiaan de Rivera y Rivera & Diógenes Manoel Leiva Martin & Emerson Fernandes Marçal & Leonardo Fernando Cruz Basso, 2012. "Present value model between prices and dividends with constant and time-varying expected returns: enterprise-level Brazilian stock market evidence from non-stationary panels," Brazilian Business Review, Fucape Business School, vol. 9(4), pages 51-86, October.
  4. Caporale, Guglielmo Maria & Hanck, Christoph, 2006. "Are PPP Tests Erratically Behaved? Some Panel Evidence," Technical Reports 2006,43, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  5. Woo, Kai-Yin & Lee, Shu-Kam, 2009. "Detecting intra-national PPP model in China: A median-unbiased estimation approach," Economic Modelling, Elsevier, vol. 26(5), pages 1029-1032, September.
  6. Herzer, Dierk & Strulik, Holger, 2013. "Religiosity and income: A panel cointegration and causality analysis," Center for European, Governance and Economic Development Research Discussion Papers 168, University of Goettingen, Department of Economics.
  7. Cerrato, Mario & Sarantis, Nicholas, 2007. "A bootstrap panel unit root test under cross-sectional dependence, with an application to PPP," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 4028-4037, May.

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