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

  • Hyungsik Roger Moon
  • Benoit Perron

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 classi.cation on the basis of n individual (univariate) unit root tests based on some ad hoc significance level. In this paper, we suggest and demonstrate how to use the false discovery rate (FDR) in evaluating I (1) = I (0) classifications

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Paper provided by CIRANO in its series CIRANO Working Papers with number 2011s-17.

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Length: 22 pages
Date of creation: 01 Feb 2011
Date of revision:
Handle: RePEc:cir:cirwor:2011s-17
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  1. Joseph Romano & Azeem Shaikh & Michael Wolf, 2008. "Rejoinder on: Control of the false discovery rate under dependence using the bootstrap and subsampling," TEST- An Official Journal of the Spanish Society of Statistics and Operations Research, Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 461-471, November.
  2. Olivier Scaillet & Laurent Barras & Russell R. Wermers, 2005. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Working Papers CEB 05-014.RS, ULB -- Universite Libre de Bruxelles.
  3. Chortareas, Georgios & Kapetanios, George, 2009. "Getting PPP right: Identifying mean-reverting real exchange rates in panels," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 390-404, February.
  4. 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.
  5. 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.
  6. 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.
  7. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
  8. 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.
  9. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
  10. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
  11. Christoph Hanck, 2009. "For which countries did PPP hold? A multiple testing approach," Empirical Economics, Springer, vol. 37(1), pages 93-103, September.
  12. 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.
  13. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
  14. Joseph Romano & Azeem Shaikh & Michael Wolf, 2008. "Control of the false discovery rate under dependence using the bootstrap and subsampling," TEST- An Official Journal of the Spanish Society of Statistics and Operations Research, Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 417-442, November.
  15. Ng, Serena, 2008. "A Simple Test for Nonstationarity in Mixed Panels," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 113-127, January.
  16. 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.
  17. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May.
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