Asymptotic Theory for Regressions with Smoothly Changing Parameters
AbstractWe derive asymptotic properties of the quasi maximum likelihood estimator of smooth transition regressions when time is the transition variable. The consistency of the estimator and its asymptotic distribution are examined. It is shown that the estimator converges at the usual square-root-of-T rate and has an asymptotically normal distribution. Finite sample properties of the estimator are explored in simulations. We illustrate with an application to US inflation and output data.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2012-31.
Date of creation: 12 Jun 2012
Date of revision:
Contact details of provider:
Web page: http://www.econ.au.dk/afn/
Regime switching; smooth transition regression; asymptotic theory.;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-07-14 (All new papers)
- NEP-ECM-2012-07-14 (Econometrics)
- NEP-ETS-2012-07-14 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Areosa, Waldyr Dutra & McAleer, Michael & Medeiros, Marcelo C., 2011.
"Moment-based estimation of smooth transition regression models with endogenous variables,"
Journal of Econometrics,
Elsevier, vol. 165(1), pages 100-111.
- Waldyr Dutra Areosa & Michael McAleer & Marcelo Cunha Medeiros, 2010. "Moment-based estimation of smooth transition regression models with endogenous variables," Textos para discussÃ£o 571, Department of Economics PUC-Rio (Brazil).
- Areosa, W.D. & McAleer, M.J. & Medeiros, M.C., 2008. "Moment-bases estimation of smooth transition regression models with endogenous variables," Econometric Institute Research Papers EI 2008-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Waldyr Dutra Areosa & Michael McAleer & Marcelo C. Medeiros, 2009. "Moment-Based Estimation of Smooth Transition Regression Models with Endogenous Variables," CIRJE F-Series CIRJE-F-671, CIRJE, Faculty of Economics, University of Tokyo.
- Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003.
"Local-global neural networks: a new approach for nonlinear time series modelling,"
Textos para discussÃ£o
470, Department of Economics PUC-Rio (Brazil).
- Mayte Suarez -Farinas & Carlos E. Pedreira & Marcelo C. Medeiros, 2004. "Local Global Neural Networks: A New Approach for Nonlinear Time Series Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1092-1107, December.
- Li, W K & Ling, Shiqing & McAleer, Michael, 2002. " Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-69, July.
- Ling, Shiqing & McAleer, Michael, 2003.
"Asymptotic Theory For A Vector Arma-Garch Model,"
Cambridge University Press, vol. 19(02), pages 280-310, April.
- Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
- Andrews, Donald W.K., 1992.
"Generic Uniform Convergence,"
Cambridge University Press, vol. 8(02), pages 241-257, June.
- Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
- Saikkonen, Pentti & Choi, In, 2004. "Cointegrating Smooth Transition Regressions," Econometric Theory, Cambridge University Press, vol. 20(02), pages 301-340, April.
- Line Elvstrøm Ekner & Emil Nejstgaard, 2013. "Parameter Identification in the Logistic STAR Model," Discussion Papers 13-07, University of Copenhagen. Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.