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Change in persistence tests for panels: An update and some new results

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Author Info
Cerqueti, Roy ()
Costantini, Mauro ()
Gutierrez, Luciano ()

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Abstract

In this paper we propose a set of new panel tests to detect changes in persistence. The test statistics are used to test the null hypothesis of stationarity against the alternative of a change in persistence from I(0) to I(1), from I(1) to I(0) and in an unknown direction. The limiting distributions of the panel tests are derived, and small sample properties are investigated by Monte Carlo experiments under the hypothesis that the individual series are independently cross-section distributed. These tests have a good size and power properties. Cross-sectional dependence is also considered. A procedure of de-factorizing, proposed by Stock and Watson (2002), is applied. The defactored panel tests have good size and power. The empirical results obtained from applying these tests to a panel covering 21 OECD countries observed between 1970 and 2007 suggest that inflation rate changes from I(1) to I(0) when cross-correlation is considered.

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Paper provided by University of Molise, Dept. SEGeS in its series Economics & Statistics Discussion Papers with number esdp08043.

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Length: 35 pages
Date of creation: 31 Mar 2008
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Handle: RePEc:mol:ecsdps:esdp08043

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Related research
Keywords: Persistence; Stationarity; Panel data;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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  1. Mankiw, N Gregory & Miron, Jeffrey A & Weil, David N, 1987. "The Adjustment of Expectations to a Change in Regime: A Study of the Founding of the Federal Reserve," American Economic Review, American Economic Association, vol. 77(3), pages 358-74, June. [Downloadable!] (restricted)
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  2. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November. [Downloadable!] (restricted)
  3. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January. [Downloadable!] (restricted)
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  4. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March. [Downloadable!] (restricted)
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  5. Timothy Cogley & Thomas Sargent, . "Evolving Post-World War II U.S. Inflation Dynamics," Working Papers 2132872, Department of Economics, W. P. Carey School of Business, Arizona State University. [Downloadable!]
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  6. A. M. Robert Taylor, 2005. "On the use of Sub-sample Unit Root Tests to Detect Changes in Persistence," Journal of Time Series Analysis, Blackwell Publishing, vol. 26(5), pages 759-778, 09. [Downloadable!] (restricted)
  7. Stephen Leybourne & Tae-Hwan Kim & Vanessa Smith & Paul Newbold, 2003. "Tests for a change in persistence against the null of difference-stationarity," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 291-311, December. [Downloadable!] (restricted)
  8. Kim, Jae-Young, 2000. "Detection of change in persistence of a linear time series," Journal of Econometrics, Elsevier, vol. 95(1), pages 97-116, March. [Downloadable!] (restricted)
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