Test of Multiple Breaks in Long Memory Process: An Unknown Mean Breaks Case

Article Preview

Abstract:

This paper extends Bai and Perron (1998) multi-unknown breaks method to long memory process, analyzes the finite sample property of the method (mean, variance, the test performance of Sup-F statistics) and the relation with the fractional integration parameter, size and location of break point. One and two unknown mean break and various long memory situations are considered. It found that expect for the condition that fractional integrated parameter d approaches to 0.5, BP method is fairly exact to estimate the break point, the bias is relatively small and the power and size of the Sup-F test is acceptable. Especially when d is negative, this method shows outstanding statistical property, small bias and standard deviation, and perfect test power and size.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

410-412

Citation:

Online since:

September 2013

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Bai J. and Perron P., Estiamting and testing linear models with multiple structural changes . Econometrica, 1998, Vol. 66, 47-78.

DOI: 10.2307/2998540

Google Scholar

[2] Bai J and Perron P., Computation and analysis of multiples structural change models , Journal of Applied Econometrics, 2003, Vol. 18, 1-22.

Google Scholar

[3] Bos C S, Franses Ph H B F and Ooms M., Long memory and level shifts: Re-analyzing inflation rates , Empirical Economics , Vol. 24, No. 3, 427-449.

DOI: 10.1007/s001810050065

Google Scholar

[4] Caporate G M and Gil-Alana L A. Long memory and structural breaks in hyperinflation countries, Journal of Economics and Finance, 2003, Vol. 27, 136-152.

DOI: 10.1007/bf02827215

Google Scholar

[5] Hidalgo J. and Robinson P. M., Testing for structural change in a long-memory environment , Journal of Econometrics, 1996, Vol. 70, 159-174.

DOI: 10.1016/0304-4076(94)01687-9

Google Scholar

[6] Horvath L and Kokoszka P. The effect of long-range dependence on change-point estimators, Journal of Statistical Planning and Inference, 1997, Vol. 64, 57-81.

DOI: 10.1016/s0378-3758(96)00208-x

Google Scholar

[7] Kramer W and Sibbertsen P., Testing for structural change in the presence of long memory, International Journal of Business and Economics, 2003, Vol. 1, 235-242.

Google Scholar

[8] Robinson P. M., Semiparametric analysis of long-memory time series , The Annals of Statistics, 1994, Vol. 22, 515-539.

Google Scholar

[9] Wright J. H., Testing for a structural break at unknown date with long-memory disturbances , Journal of Times Series Analysis, 1996, Vol. 19, 369-376.

DOI: 10.1111/1467-9892.00097

Google Scholar