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Beyond Panel Unit Root Tests : Using Multiple Testing to Determine the Non-Stationarity Properties of Individual Series in a Panel

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  • MOON, H.R.
  • PERRON, Benoit

Abstract

Most panel unit root tests are designed to test the joint null hypothesis of a unit root for each individual series in a panel. After a rejection, it will often be of interest to identify which series can be deemed to be stationary and which series can be deemed nonstationary. Researchers will sometimes carry out this classification on the basis of n individual (univariate) unit root tests based on some ad hoc significance level. In this paper, we demonstrate how to use the false discovery rate (FDR) in evaluating I(1)=I(0) classifications based on individual unit root tests when the size of the cross section (n) and time series (T) dimensions are large. We report results from a simulation experiment and illustrate the methods on two data sets.

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Bibliographic Info

Paper provided by Centre interuniversitaire de recherche en économie quantitative, CIREQ in its series Cahiers de recherche with number 10-2010.

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Length: 43 pages
Date of creation: 2010
Date of revision:
Handle: RePEc:mtl:montec:10-2010

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Keywords: False discovery rate; Multiple testing; unit root tests; panel data;

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  1. Palm, Franz C. & Smeekes, Stephan & Urbain, Jean-Pierre, 2011. "Cross-sectional dependence robust block bootstrap panel unit root tests," Journal of Econometrics, Elsevier, vol. 163(1), pages 85-104, July.
  2. 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.
  3. Christoph Hanck, 2009. "For which countries did PPP hold? A multiple testing approach," Empirical Economics, Springer, vol. 37(1), pages 93-103, September.
  4. MOON, Hyungsik Roger & PERRON, Benoit., 2002. "Testing for a Unit Root in Panels with Dynamic Factors," Cahiers de recherche 2002-18, Universite de Montreal, Departement de sciences economiques.
  5. 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.
  6. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205.
  7. Lopez, Claude & Murray, Christian J & Papell, David H, 2005. "State of the Art Unit Root Tests and Purchasing Power Parity," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(2), pages 361-69, April.
  8. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May.
  9. Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
  10. Benoit Perron & Hyungsik Roger Moon, 2007. "An empirical analysis of nonstationarity in a panel of interest rates with factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 383-400.
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Cited by:
  1. Pesaran, M. Hashem, 2012. "On the interpretation of panel unit root tests," Economics Letters, Elsevier, vol. 116(3), pages 545-546.
  2. Smeekes Stephan, 2011. "Bootstrap Sequential Tests to Determine the Stationary Units in a Panel," Research Memorandum 003, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

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