Asymptotic Theory for Regressions with Smoothly Changing Parameters
We 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.
References listed on IDEAS
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.:
- Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," SSE/EFI Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
- 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.
- Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003. "Local-global neural networks: a new approach for nonlinear time series modelling," Textos para discussão 470, 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.
- 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 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.
- Waldyr Dutra Areosa & Michael McAleer & Marcelo Cunha Medeiros, 2010. "Moment-based estimation of smooth transition regression models with endogenous variables," Textos para discussão 571, Department of Economics PUC-Rio (Brazil).
- Marcelo C. Medeiros & Alvaro Veiga, 2003.
"Diagnostic Checking in a Flexible Nonlinear Time Series Model,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 24(4), pages 461-482, 07.
- Medeiros, Marcelo & Veiga, Alvaro, 2000. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 386, Stockholm School of Economics, revised 15 Jan 2001.
- Saikkonen, Pentti & Choi, In, 2004. "Cointegrating Smooth Transition Regressions," Econometric Theory, Cambridge University Press, vol. 20(02), pages 301-340, April.
- 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.
- 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.
- Shiqing Ling & Michael McAleer, 2001.
"Asymptotic Theory for a Vector ARMA-GARCH Model,"
ISER Discussion Paper
0549, Institute of Social and Economic Research, Osaka University.
When requesting a correction, please mention this item's handle: RePEc:aah:create:2012-31. See general information about how to correct material in RePEc.
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.