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Bootstrapping long memory tests: Some Monte Carlo results

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  • Murphy, A.
  • Izzeldin, M.

Abstract

The bootstrapped size and power properties of six long memory tests-the modified R/S, KPSS, V/S, GPH, Robinson's and the recently proposed tests-are investigated. Even in samples of size 100, the moving block bootstrap controls the empirical size of the tests in the DGPs examined. The test appears to be the most powerful. Moreover, compared with asymptotic tests, the bootstrap tests suffer little loss of power against fractionally integrated processes in samples with 250 or more observations. This is true both for distributions with heavy tails and with stochastic volatility.

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Bibliographic Info

Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 53 (2009)
Issue (Month): 6 (April)
Pages: 2325-2334

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Handle: RePEc:eee:csdana:v:53:y:2009:i:6:p:2325-2334

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  1. 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.
  2. JAMES G. MacKINNON, 2006. "Bootstrap Methods in Econometrics," The Economic Record, The Economic Society of Australia, vol. 82(s1), pages S2-S18, 09.
  3. Russell Davidson & James G. MacKinnon, 2004. "The Power of Bootstrap and Asymptotic Tests," Working Papers 1035, Queen's University, Department of Economics.
  4. Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus & Teyssiere, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," Journal of Econometrics, Elsevier, vol. 112(2), pages 265-294, February.
  5. Harris, David & McCabe, Brendan & Leybourne, Stephen, 2008. "Testing For Long Memory," Econometric Theory, Cambridge University Press, vol. 24(01), pages 143-175, February.
  6. Hiemstra, Craig & Jones, Jonathan D., 1997. "Another look at long memory in common stock returns," Journal of Empirical Finance, Elsevier, vol. 4(4), pages 373-401, December.
  7. Marwan Izzeldin & Anthony Murphy, 2000. "Bootstrapping the Small Sample Critical Values of the Rescaled Range Statistic," The Economic and Social Review, Economic and Social Studies, vol. 31(4), pages 351-359.
  8. Lee, Dongin & Schmidt, Peter, 1996. "On the power of the KPSS test of stationarity against fractionally-integrated alternatives," Journal of Econometrics, Elsevier, vol. 73(1), pages 285-302, July.
  9. Hauser, Michael A, 1997. "Semiparametric and Nonparametric Testing for Long Memory: A Monte Carlo Study," Empirical Economics, Springer, vol. 22(2), pages 247-71.
  10. Pilar Grau-Carles, 2005. "Tests of Long Memory: A Bootstrap Approach," Computational Economics, Society for Computational Economics, vol. 25(1), pages 103-113, February.
  11. Robinson, P.M. & Henry, M., 1999. "Long And Short Memory Conditional Heteroskedasticity In Estimating The Memory Parameter Of Levels," Econometric Theory, Cambridge University Press, vol. 15(03), pages 299-336, June.
  12. Andrew W. Lo, 1989. "Long-term Memory in Stock Market Prices," NBER Working Papers 2984, National Bureau of Economic Research, Inc.
  13. Lobato, Ignacio N & Robinson, Peter M, 1998. "A Nonparametric Test for I(0)," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 475-95, July.
  14. Silva, E.M. & Franco, G.C. & Reisen, V.A. & Cruz, F.R.B., 2006. "Local bootstrap approaches for fractional differential parameter estimation in ARFIMA models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1002-1011, November.
  15. Robinson, P. M., 1991. "Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression," Journal of Econometrics, Elsevier, vol. 47(1), pages 67-84, January.
  16. Javier Hidalgo, 2003. "An Alternative Bootstrap to Moving Blocks for Time Series Regression Models," STICERD - Econometrics Paper Series /2003/452, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  17. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
  18. Christian de Peretti, 2003. "Bilateral Bootstrap Tests for Long Memory: An Application to the Silver Market," Computational Economics, Society for Computational Economics, vol. 22(2), pages 187-212, October.
  19. Andersson, Michael K. & Gredenhoff, Mikael P., 1998. "Robust Testing for Fractional Integration Using the Bootstrap," Working Paper Series in Economics and Finance 218, Stockholm School of Economics.
  20. Franco, Glaura C. & Reisen, Valderio A., 2007. "Bootstrap approaches and confidence intervals for stationary and non-stationary long-range dependence processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 546-562.
  21. Tanaka, Katsuto, 1999. "The Nonstationary Fractional Unit Root," Econometric Theory, Cambridge University Press, vol. 15(04), pages 549-582, August.
  22. Hidalgo, Javier, 2003. "An alternative bootstrap to moving blocks for time series regression models," Journal of Econometrics, Elsevier, vol. 117(2), pages 369-399, December.
  23. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 35(4), pages 615-645, November.
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