Abstract
This paper considers the issue of seasonal cointegrating rank selection by information criteria as the extension of Cheng and Phillips (The Econometrics Journal (2009), Vol. 12, pp. S83–S104). The method does not require the specification of lag length in vector autoregression, is convenient in empirical work, and is in a semiparametric context because it allows for a general short memory error component in the model with only lags related to error correction terms. Some limit properties of usual information criteria are given for the rank selection and small Monte Carlo simulations are conducted to evaluate the performances of the criteria.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
AHN, S. K., CHO, S., and SEONG, B. C. (2004): Inference of seasonal cointegration: Gaussian reduced rank estimation and tests for various types of cointegration. Oxford Bulletin of Economics and Statistics 66, 261–284.
AHN, S. K., and REINSEL, G. C. (1994): Estimation of partially nonstationary vector autoregressive models with seasonal behavior. Journal of Econometrics 62, 317–350.
AKAIKE, H. (1973): Information theory and an extension of the maximum likelihood principle. In B. N. Petrov and F. Csaki (Eds.): Second International Symposium on Information Theory. Budapest: Akademiai Kiado.
CHENG, X. and PHILLIPS, P. C. B. (2008): Cointegrating rank selection in models with time-varying variance. Cowles Foundation Discussion Paper No. 1688.
CHENG, X. and PHILLIPS, P. C. B. (2009): Semiparametric cointegrating rank selection. The Econometrics Journal 12, S83–S104.
CUBADDA, G. (2001): Complex reduced rank models for seasonally cointegrated time series. Oxford Bulletin of Economics and Statistics 63, 497–511.
HANNAN, E. J. and QUINN, B. G. (1979): The determination of the order of an autoregression. Journal of the Royal Statistical Society, Series B, 41, 190–195.
JOHANSEN, S. (1996): Likelihood-based inference in cointegrated vector autoregressive models, 2nd ed.. Oxford University Press, Oxford.
JOHANSEN, S., and SCHAUMBURG, E. (1999): Likelihood analysis of seasonal cointegration. Journal of Econometrics 88, 301–339.
PHILLIPS, P. C. B. (2008): Unit root model selection. Journal of the Japan Statistical Society 38, 65–74.
SCHWARZ, G. (1978): Estimating the dimension of a model. Annals of Statistics 6, 461–464.
SEONG, B. (2009): Bonferroni Correction for Seasonal Cointegrating Ranks. Economics Letters 103, 42–44.
SEONG, B., CHO, S., and AHN, S. K. (2006): Maximum eigenvalue test for seasonal cointegrating ranks. Oxford Bulletin of Economics and Statistics 68, 497–514.
SEONG, B., and YI, Y. J. (2008): Joint Test for Seasonal Cointegrating Ranks. Communications of the Korean Statistical Society 15, 719–726.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Seong, B., Ahn, S.K., Cho, S. (2010). Semiparametric Seasonal Cointegrating Rank Selection. In: Lechevallier, Y., Saporta, G. (eds) Proceedings of COMPSTAT'2010. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2604-3_27
Download citation
DOI: https://doi.org/10.1007/978-3-7908-2604-3_27
Published:
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2603-6
Online ISBN: 978-3-7908-2604-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)