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Panel Data Tests of PPP. A Critical Overview

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  • Caporale, Guglielmo Maria

    (London South Bank University)

  • Cerrato, Mario

    (London Metropolitan University)

Abstract

This paper reviews 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. We offer some empirical guidelines to deal with these problems, but conclude that panel methods are unlikely to solve the PPP puzzle.

Suggested Citation

  • Caporale, Guglielmo Maria & Cerrato, Mario, 2004. "Panel Data Tests of PPP. A Critical Overview," Economics Series 159, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:159
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    File URL: https://irihs.ihs.ac.at/id/eprint/1579
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    2. Herzer, Dierk, 2014. "Unions and income inequality: a heterogenous cointegration and causality analysis," Working Paper 146/2014, Helmut Schmidt University, Hamburg.
    3. Guglielmo Maria Caporale & Christoph Hanck, 2010. "Are PPP tests erratically behaved? Some panel evidence," International Review of Applied Economics, Taylor & Francis Journals, vol. 24(2), pages 203-221.
    4. Luis Alberiko Gil-Alaña & Guiglielmo Maria Caporale, 2012. "Testing the PPP Hypothesis in the Sub-Saharan Countries," NCID Working Papers 10/2012, Navarra Center for International Development, University of Navarra.
    5. Guglielmo Maria Caporale & Christoph Hanck, 2009. "Cointegration tests of PPP: do they also exhibit erratic behaviour?," Applied Economics Letters, Taylor & Francis Journals, vol. 16(1), pages 9-15.
    6. Guglielmo Maria Caporale & Andros Gregoriou, 2009. "Non-normality, heteroscedasticity and recursive unit root tests of PPP: solving the PPP puzzle?," Applied Economics Letters, Taylor & Francis Journals, vol. 16(3), pages 223-226.
    7. 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.
    8. Martin Wagner, 2008. "On PPP, unit roots and panels," Empirical Economics, Springer, vol. 35(2), pages 229-249, September.
    9. Dierk Herzer & Julian Donaubauer, 2018. "The long-run effect of foreign direct investment on total factor productivity in developing countries: a panel cointegration analysis," Empirical Economics, Springer, vol. 54(2), pages 309-342, March.
    10. Miles, William, 2020. "House price convergence in the euro zone: A pairwise approach," Economic Systems, Elsevier, vol. 44(3).
    11. Julián Ramajo Hernández(1) & Montserrat Ferré Carracedo(2), "undated". "Testing For Long-Run Purchasing Power Parity In The Post Bretton Woods Era: Evidence From Old And New Tests," Working Papers 24-05 Classification-JEL , Instituto de Estudios Fiscales.
    12. 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.
    13. Dierk Herzer & Holger Strulik, 2017. "Religiosity and income: a panel cointegration and causality analysis," Applied Economics, Taylor & Francis Journals, vol. 49(30), pages 2922-2938, June.
    14. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    15. Norkutė, Milda & Westerlund, Joakim, 2021. "The factor analytical approach in near unit root interactive effects panels," Journal of Econometrics, Elsevier, vol. 221(2), pages 569-590.
    16. Dierk Herzer, 2017. "The Long-run Relationship Between Trade and Population Health: Evidence from Five Decades," The World Economy, Wiley Blackwell, vol. 40(2), pages 462-487, February.
    17. Luke Lin & Chun I. Lee, 2016. "Central Bank Intervention, Exchange Rate Regime and the Purchasing Power Parity," The World Economy, Wiley Blackwell, vol. 39(8), pages 1256-1274, August.
    18. Paweł Baranowski, 2005. "Wpływ inflacji na inwestycje w kapitał rzeczowy w krajach Unii Europejskiej," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 11-12, pages 19-30.
    19. 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.
    20. Luzzati, Tommaso & Orsini, Marco & Gucciardi, Gianluca, 2018. "A multiscale reassessment of the Environmental Kuznets Curve for energy and CO2 emissions," Energy Policy, Elsevier, vol. 122(C), pages 612-621.
    21. 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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    More about this item

    Keywords

    Purchasing Power Parity (PPP); Panel unit root and cointegration tests; Cross-sectional dependence;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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