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The effects of additive outliers on stationarity tests: a monte carlo study

  • Olivier Darné


    (LAMETA-CNRS, Faculty of Economics, University of Montpellier I)

Monte Carlo simulations are used to study the size and power properties of two stationarity tests developed by Kwiatkowski et al. (1992) [KPSS] and Leybourne and McCabe (1994) [LMC] when the data contain additive outliers. We show that the KPSS tests are very robust to additive outliers whereas the LMC test exhibits size distorsions and loss of power.

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Article provided by AccessEcon in its journal Economics Bulletin.

Volume (Year): 3 (2004)
Issue (Month): 16 ()
Pages: 1-8

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Handle: RePEc:ebl:ecbull:eb-04c10004
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  1. Kilian, L. & Caner, M., 1999. "Size Distortions of Tests of the Null Hypothesis of Stationarity: Evidence and Implications for the PPP Debate," Papers 99-05, Michigan - Center for Research on Economic & Social Theory.
  2. Shin, Dong Wan & Sarkar, Sahadeb & Lee, Jong Hyup, 1996. "Unit root tests for time series with outliers," Statistics & Probability Letters, Elsevier, vol. 30(3), pages 189-197, October.
  3. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  4. Leybourne, S J & McCabe, B P M, 1994. "A Consistent Test for a Unit Root," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 157-66, April.
  5. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
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