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PPP May not Hold After all: A Further Investigation

  • Serena Ng
  • Pierre Perron

In a recent paper Engel (1999b) presents monte-carlo evidence to suggest that unit root tests can not detect a non-stationary component in the real exchange rate even when this component accounts for almost half of its long-horizon forecast error variance This hidden non-stationary component led to the conclusion that long run purchasing power parity might not hold after all In this note we first point out some conceptual difficulties with the statistic being used to measure the size of the non-stationary component and then argue that it bears no systematic relationship with rejection rates in unit root tests The problems stem from near observational equivalence of the simulated model in not one but two dimensions We then discuss the steps a practitioner can take to minimize Type I error in cases when the non-stationary component is hard to detect Real exchange rate data for 19 countries are examined and estimates are obtained for the duration of the real exchange rate shocks

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Paper provided by The Johns Hopkins University,Department of Economics in its series Economics Working Paper Archive with number 466.

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Date of creation: Feb 2001
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Handle: RePEc:jhu:papers:466
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  1. Perron, Pierre, 1991. "Test Consistency with Varying Sampling Frequency," Econometric Theory, Cambridge University Press, vol. 7(03), pages 341-368, September.
  2. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  3. Douglas Staiger & James H. Stock & Mark W. Watson, 1997. "The NAIRU, Unemployment and Monetary Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 33-49, Winter.
  4. Paul R. Bergin & Robert C. Feenstra, 1999. "Pricing to Market, Staggered Contracts, and Real Exchange Rate Persistence," NBER Working Papers 7026, National Bureau of Economic Research, Inc.
  5. Perron, P. & Ng, S., 1994. "Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties," Cahiers de recherche 9427, Universite de Montreal, Departement de sciences economiques.
  6. Gordon, Robert J, 1996. "The Time-varying NAIRU and its Implications for Economic Policy," CEPR Discussion Papers 1492, C.E.P.R. Discussion Papers.
  7. Engel, C., 1996. "Accounting for U.S. Real Exchange Rate Changes," Working Papers 96-02, University of Washington, Department of Economics.
  8. Serena Ng & Pierre Perron, 1997. "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Boston College Working Papers in Economics 369, Boston College Department of Economics, revised 01 Sep 2000.
  9. Campbell, J.Y. & Perron, P., 1991. "Pitfalls and Opportunities: What Macroeconomics should know about unit roots," Papers 360, Princeton, Department of Economics - Econometric Research Program.
  10. Shiller, Robert J. & Perron, Pierre, 1985. "Testing the random walk hypothesis : Power versus frequency of observation," Economics Letters, Elsevier, vol. 18(4), pages 381-386.
  11. John B. Taylor, 1999. "A Historical Analysis of Monetary Policy Rules," NBER Chapters, in: Monetary Policy Rules, pages 319-348 National Bureau of Economic Research, Inc.
  12. Douglas Staiger & James H. Stock & Mark W. Watson, 1996. "How Precise are Estimates of the Natural Rate of Unemployment?," NBER Working Papers 5477, National Bureau of Economic Research, Inc.
  13. Robert R Tchaidze, 2001. "Estimating Taylor Rules in a Real Time Setting," Economics Working Paper Archive 457, The Johns Hopkins University,Department of Economics.
  14. Perron, Pierre & Ng, Serena, 1998. "An Autoregressive Spectral Density Estimator At Frequency Zero For Nonstationarity Tests," Econometric Theory, Cambridge University Press, vol. 14(05), pages 560-603, October.
  15. Perron, P., 1994. "The Adequacy of Asymptotic Approximations in the Near-Integrated Autoregressive Model with Dependent Errors," Cahiers de recherche 9424, Universite de Montreal, Departement de sciences economiques.
  16. Nabeya, S. & Perron, P., 1991. "Local Asymtotic Distributions Related to the AR(1) MOdel with Dependent Errors," Papers 362, Princeton, Department of Economics - Econometric Research Program.
  17. Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April.
  18. Faust, Jon, 1996. "Near Observational Equivalence and Theoretical size Problems with Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 12(04), pages 724-731, October.
  19. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July.
  20. Laurence Ball & Robert Moffitt, 2001. "Productivity Growth and the Phillips Curve," Economics Working Paper Archive 450, The Johns Hopkins University,Department of Economics.
  21. Ng, S. & Perron, P., 1995. "Estimation and Inference in Nearly Unbalanced, Nearly Cointegrated Systems," Cahiers de recherche 9534, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  22. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
  23. Hamori, Shigeyuki & Tokihisa, Akira, 1997. "Testing for a unit root in the presence of a variance shift1," Economics Letters, Elsevier, vol. 57(3), pages 245-253, December.
  24. Robert J. Gordon, 1998. "Foundations of the Goldilocks Economy: Supply Shocks and the Time-Varying NAIRU," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 29(2), pages 297-346.
  25. Clark, Peter K., 1988. "Nearly redundant parameters and measures of persistence in economic time series," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 447-461.
  26. Schwert, G William, 1989. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(2), pages 147-59, April.
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