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For Which Countries did PPP hold? A Multiple Testing Approach

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  • Hanck, Christoph
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    Abstract

    We use recent advances in multiple testing to identify the countries for which Purchasing Power Parity (PPP) held over the last century. The approach controls the multiplicity problem inherent in simultaneously testing for PPP on several time series, thereby avoiding spurious rejections. It has higher power than traditional multiple testing techniques by exploiting the dependence structure between the countries with a bootstrap approach. We use a sieve bootstrap approach to account for nonstationarity under the null hypothesis. Our empirical results show that, plausibly, controlling for multiplicity in this way leads to a number of rejections of the null of no PPP that is intermediate between that of traditional multiple testing techniques and that which results if one tests the null on each single time series at some level. --

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    Bibliographic Info

    Paper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 2006,47.

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    Date of creation: 2006
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    Handle: RePEc:zbw:sfb475:200647

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    Related research

    Keywords: Multiple Testing; Bootstrap; PPP; Panel Data;

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    1. Nelson C. Mark & Masao Ogaki & Donggyu Sul, 2005. "Dynamic Seemingly Unrelated Cointegrating Regressions," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 797-820.
    2. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    3. Yoosoon Chang & Joon Y. Park, 2003. "A Sieve Bootstrap For The Test Of A Unit Root," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 379-400, 07.
    4. Breuer, Janice Boucher & McNown, Robert & Wallace, Myles S, 2001. "Misleading Inferences from Panel Unit-Root Tests with an Illustration from Purchasing Power Parity," Review of International Economics, Wiley Blackwell, vol. 9(3), pages 482-93, August.
    5. Hanck, Christoph, 2006. "Cross-Sectional Correlation Robust Tests for Panel Cointegration," Technical Reports 2006,44, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    6. Phillips, Peter C B & Xiao, Zhijie, 1998. " A Primer on Unit Root Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 423-69, December.
    7. Jaroslava Hlouskova & Martin Wagner, 2005. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Diskussionsschriften dp0503, Universitaet Bern, Departement Volkswirtschaft.
    8. Karlsson, Sune & Lothgren, Mickael, 2000. "On the power and interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 66(3), pages 249-255, March.
    9. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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