A simple test of changes in mean in the possible presence of long‐range dependence

We propose a simple testing procedure to test for a change point in the mean of a possibly long‐range dependent time series. Under the null hypothesis, the series is stationary with long‐range dependence and our test statistic converges to a non‐degenerate distribution, whereas under the alternative, the series has a change point in the mean and the test statistic diverges to infinity. We demonstrate the good size and power properties of our test via simulations and illustrate its usefulness by analysing two real data sets.

[1]  Laura Mayoral Testing for Fractional Integration Versus Short Memory with Structural Breaks* , 2012 .

[2]  R. Bass,et al.  Review: P. Billingsley, Convergence of probability measures , 1971 .

[3]  X. Shao,et al.  A self‐normalized approach to confidence interval construction in time series , 2010, 1005.2137.

[4]  Laura Mayoral Testing for Fractional integration versus short memory with trends and structural breaks , 2010 .

[5]  Zhongjun Qu,et al.  A Test Against Spurious Long Memory , 2009 .

[6]  A. Aue,et al.  ON DISTINGUISHING BETWEEN RANDOM WALK AND CHANGE IN THE MEAN ALTERNATIVES , 2009, Econometric Theory.

[7]  X. Shao,et al.  Confidence intervals for spectral mean and ratio statistics , 2009 .

[8]  M. D. Martínez-Miranda,et al.  Computational Statistics and Data Analysis , 2009 .

[9]  Lihong Wang Change-in-mean problem for long memory time series models with applications , 2008 .

[10]  Jeffrey R. Russell,et al.  True or Spurious Long Memory? A New Test , 2008 .

[11]  Lihong Wang Gradual changes in long memory processes with applications , 2007 .

[12]  Wei Biao Wu,et al.  Inference of trends in time series , 2007 .

[13]  Wei Biao Wu,et al.  LOCAL WHITTLE ESTIMATION OF FRACTIONAL INTEGRATION FOR NONLINEAR PROCESSES , 2007, Econometric Theory.

[14]  Katsumi Shimotsu,et al.  Simple (but effective) tests of long memory versus structural breaks , 2006 .

[15]  Pierre Perron,et al.  An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts , 2006 .

[16]  A. Philippe,et al.  A TEST FOR STATIONARITY VERSUS TRENDS AND UNIT ROOTS FOR A WIDE CLASS OF DEPENDENT ERRORS , 2006, Econometric Theory.

[17]  X. Shao,et al.  Invariance principles for fractionally integrated nonlinear processes , 2006, math/0608223.

[18]  Gilles Teyssière,et al.  Long Memory in Economics , 2006 .

[19]  Q. Shao,et al.  On discriminating between long-range dependence and changes in mean , 2006, math/0607803.

[20]  A. Banerjee,et al.  Modelling structural breaks, long memory and stock market volatility: an overview , 2005 .

[21]  J. Dolado,et al.  What is What?: A Simple Time-Domain Test of Long-Memory vs. Structural Breaks , 2005 .

[22]  Pierre Perron,et al.  Dealing with Structural Breaks , 2005 .

[23]  Stepana Lazarova,et al.  Testing for structural change in regression with long memory processes , 2004 .

[24]  T. Mikosch,et al.  Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects , 2004, Review of Economics and Statistics.

[25]  C. Granger,et al.  Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns , 2004 .

[26]  Wang Lihong Limit theorems in change-point problems with multivariate long-range dependent observations , 2003 .

[27]  Qiying Wang,et al.  ASYMPTOTICS FOR GENERAL FRACTIONALLY INTEGRATED PROCESSES WITH APPLICATIONS TO UNIT ROOT TESTS , 2003, Econometric Theory.

[28]  P. Robinson Time Series with Long Memory , 2003 .

[29]  Murad S. Taqqu,et al.  Theory and applications of long-range dependence , 2003 .

[30]  P. Sibbertsen,et al.  Distinguishing between Long-Range Dependence and Deterministic Trends , 2003 .

[31]  B. Ray,et al.  Bayesian methods for change‐point detection in long‐range dependent processes , 2002 .

[32]  Jan Beran,et al.  SEMIFAR models|a semiparametric approach to modelling trends , 2002 .

[33]  Ignacio N. Lobato Testing That a Dependent Process Is Uncorrelated , 2001 .

[34]  Marc Henry,et al.  Robust Automatic Bandwidth for Long Memory , 2001 .

[35]  Ignacio N. Lobato,et al.  A NONPARAMETRIC TEST FOR I(0) , 1998 .

[36]  Rohit S. Deo,et al.  Linear Trend with Fractionally Integrated Errors , 1998 .

[37]  Jonathan H. Wright Testing for a Structural Break at Unknown Date with Long‐memory Disturbances , 1998 .

[38]  Marcus J. Chambers,et al.  Long Memory and Aggregation in Macroeconomic Time Series , 1998 .

[39]  L. Horváth,et al.  The effect of long-range dependence on change-point estimators , 1997 .

[40]  Murad S. Taqqu,et al.  Testing for long‐range dependence in the presence of shifting means or a slowly declining trend, using a variance‐type estimator , 1997 .

[41]  Ignacio N. Lobato,et al.  Real and Spurious Long-Memory Properties of Stock-Market Data , 1996 .

[42]  Javier Hidalgo,et al.  Testing for structural change in a long-memory environment☆ , 1996 .

[43]  Marc Henry,et al.  Bandwidth Choice in Gaussian Semiparametric Estimation of Long Range Dependence , 1996 .

[44]  P. Robinson Gaussian Semiparametric Estimation of Long Range Dependence , 1995 .

[45]  D. Andrews Tests for Parameter Instability and Structural Change with Unknown Change Point , 1993 .

[46]  R. Smith Long-range dependence and global warming , 1992 .

[47]  Venkata K. Jandhyala,et al.  A search for the source of the nile's change-points , 1991 .

[48]  R. Davies,et al.  Tests for Hurst effect , 1987 .

[49]  H. R. Kuensch Statistical Aspects of Self-Similar Processes , 1986 .

[50]  D. Pollard Convergence of stochastic processes , 1984 .

[51]  J. Geweke,et al.  THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS , 1983 .

[52]  G. Cobb The problem of the Nile: Conditional solution to a changepoint problem , 1978 .

[53]  Yu. A. Davydov,et al.  The Invariance Principle for Stationary Processes , 1970 .