137
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

Autoregressive Order Identification for VAR Models with Non Constant Variance

Pages 2059-2078 | Received 01 Jun 2012, Accepted 28 Jan 2013, Published online: 01 Jun 2015

References

  • Ahmed, S., Levin, A., Wilson, B.A. (2002). Recent US macroeconomic stability: good luck, good policies, or good practices? International Finance Discussion Papers, The board of governors of the federal reserve system, 2002–730.
  • Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In: Petrov, B.N., Csaki, F., eds. 2nd International Symposium on Information Theory (pp 267–281). Budapest: Akademia Kiado.
  • Ansley, C.F., Newbold, P. (1979). Multivariate partial autocorrelations. ASA Proc. Business Econ. Stat. Sec.349–353.
  • Aue, A., Hörmann, S., Horvàth, L., Reimherr, M. (2009). Break detection in the covariance structure of multivariate time series models. Ann. Stat. 37:4046–4087.
  • Bai, J. (2000). Vector autoregressive models with structural changes in regression coefficients and in variance-covariance matrices. Ann. Econ. Finance 1:303–339.
  • Boubacar Mainassara, Y. (2012). Selection of weak VARMA models by Akaike’s information criteria. J. Time Ser. Anal. 33:121–130.
  • Brockwell, P.J., Davis, R.A. (1991). Time Series: Theory and Methods. New York: Springer.
  • Cavanaugh, J.E. (1997). Unifying the derivations for the Akaike and corrected Akaike information criteria. Stat. Probab. Lett. 33:201–208.
  • Dahlhaus, R. (1997). Fitting time series models to non stationary processes. Ann. Stat. 25:1–37.
  • Dahlhaus, R., Subba Rao, S. (2006). Statistical inference for time-varying ARCH processes. Ann. Stat. 34:1075–1114.
  • Davis, S.J., Kahn, J.A. (2008). Interpreting the great moderation: changes in the volatility of economic activity at the macro and micro levels. J. Econ. Perspectives 22:155–180.
  • Engle, R.F., Rangel, J.G. (2008). The spline GARCH model for low-frequency volatility and its global macroeconomic causes. Rev. Financial Studies 21:1187–1222.
  • Francq, C., Gautier, A. (2004). Large sample properties of parameter least squares estimates for time-varying ARMA models. J. Time Ser. Anal. 25:765–783.
  • Galeano, P., Pena, D. (2007). Covariance changes detection in multivariate time series. J. Stat. Plan. Inf. 137:194–211.
  • Hannan, E.J., Quinn, B.G. (1979). The determination of the order of an autoregression. J. Royal Stat. Soc. B 41:190–195.
  • Herrera, A.M., Pesavento, E. (2005). The decline in the US output volatility: structural changes and inventory investment. J. Business Econ. Stat. 23:462–472.
  • Horvàth, L., Kokoszka, P., Zhang, A. (2006). Monitoring constancy of variance in conditionally heteroskedastic time series. Econ. Theor. 22:373–402.
  • Horvàth, L., Steinebach, J. (2000). Testing for changes in the mean or variance of a stochastic process under weak invariance. J. Stat. Plan. Inf. 91:365–376.
  • Hurvich, C.M., Tsai, C.-L. (1989). Regression and time series model selection in small samples. Biometrika 76:297–307.
  • Kim, C.S., Park, J.Y. (2010). Cointegrating regressions with time heterogeneity. Econ. Rev. 29:397–438.
  • Kim, C.J., Nelson, C.R. (1999). Has the U.S. economy become more stable? A Bayesian approach based on a Markov-switching model of the business cycle. Rev. Econ. Stat. 81:608–616.
  • Kokoszka, P., Leipus, R. (2000). Change-point estimation in ARCH models. Bernoulli 6:513–539.
  • Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Berlin: Springer.
  • McConnell, M.M., Perez-Quiros, G. (1999). A decomposition of the increased stability of GDP growth. Current Issues in Economics and Finance, Federal Reserve Bank of New York.
  • Mikosch, T., Stărică, C. (2004). Nonstationarities in financial time series, the long- range dependence, and the IGARCH effects. Rev. Econ. Stat. 86:378–390.
  • Patilea, V., Raïssi, H. (2012). Adaptive estimation of vector autoregressive models with time-varying variance: application to testing linear causality in mean. J. Stat. Plan. Inf. 142:2891–2912.
  • Patilea, V., Raïssi, H. (2011). Corrected portmanteau tests for VAR models with time-varying variance. Working paper, Université européenne de Bretagne IRMAR-INSA.
  • Paulsen, J. (1984). Order determination of multivariate autoregressive time series with unit roots. J. Time Ser. Anal. 5:115–127.
  • Qu, Z., Perron, P. (2007). Estimating and testing structural changes in multivariate regressions. Econometrica 75:459–502.
  • Reinsel, G.C. (1993). Elements of Multivariate Time Series Analysis. New York: Springer.
  • Sanso, A., Aragó, V., Carrion, J.L. (2004). Testing for changes in the unconditional variance of financial time series. Revista de Economia Financiera 4:32–53.
  • Stărică, C. (2003). Is GARCH(1,1) as good a model as the Nobel prize accolades would imply? Working paper, Available at: http://129.3.20.41/eps/em/papers/0411/0411015.pdf.
  • Stock, J.H., Watson, M.W. (2002). Has the business cycle changed and why? In: Gertler, M., Rogoff, K., eds. NBER Macroannual 2002. Cambridge, MA: MIT Press.
  • Tiao, G.C., Box, G.E.P. (1981). Modeling multiple times series with applications. J. Am. Stat. Assoc. 76:802–816.
  • Xu, K.L., Phillips, P.C.B. (2008). Adaptive estimation of autoregressive models with time-varying variances. J. Econ. 142:265–280.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.