Moment-bases estimation of smooth transition regression models with endogenous variables
AbstractNonlinear regression models have been widely used in practice for a variety of time series andcross-section datasets. For purposes of analyzing univariate and multivariate time series data, in particular,Smooth Transition Regression (STR) models have been shown to be very useful for representing and capturingasymmetric behavior. Most STR models have been applied to univariate processes, and have made avariety of assumptions, including stationary or cointegrated processes, uncorrelated, homoskedastic or conditionallyheteroskedastic errors, and weakly exogenous regressors. Under the assumption of exogeneity,the standard method of estimation is nonlinear least squares. The primary purpose of this paper is to relaxthe assumption of weakly exogenous regressors and to discuss moment based methods for estimating STRmodels. The paper analyzes the properties of the STR model with endogenous variables by providing a diagnostictest of linearity of the underlying process under endogeneity, developing an estimation procedureand a misspecification test for the STR model, presenting the results of Monte Carlo simulations to showthe usefulness of the model and estimation method, and providing an empirical application for inflation ratetargeting in Brazil. We show that STR models with endogenous variables can be specified and estimatedby a straightforward application of existing results in the literature.
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Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2008-36.
Date of creation: 16 Dec 2008
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endogeneity; smooth transition; generalized method of moments; inflation targeting; nonlinear instrumental variables; nonlinear models;
Other versions of this item:
- 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 discussÃ£o 571, Department of Economics PUC-Rio (Brazil).
- NEP-ALL-2009-03-28 (All new papers)
- NEP-ECM-2009-03-28 (Econometrics)
- NEP-ETS-2009-03-28 (Econometric Time Series)
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- Amemiya, Takeshi, 1975. "The nonlinear limited-information maximum- likelihood estimator and the modified nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 3(4), pages 375-386, November.
- 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 discussÃ£o 470, Department of Economics PUC-Rio (Brazil).
- Eric Hillebrand & Marcelo C. Medeiros & Junyue Xu, 2012. "Asymptotic Theory for Regressions with Smoothly Changing Parameters," CREATES Research Papers 2012-31, School of Economics and Management, University of Aarhus.
- Donald W.K. Andrews & Xu Cheng, 2011.
"GMM Estimation and Uniform Subvector Inference with Possible Identification Failure,"
Cowles Foundation Discussion Papers
1828, Cowles Foundation for Research in Economics, Yale University.
- Donald W.K. Andrews & Xu Cheng, 2011. "GMM Estimation and Uniform Subvector Inference with Possible Identification Failure," Cowles Foundation Discussion Papers 1828, Cowles Foundation for Research in Economics, Yale University, revised Jan 2013.
- Massacci, Daniele, 2012. "A simple test for linearity against exponential smooth transition models with endogenous variables," Economics Letters, Elsevier, vol. 117(3), pages 851-856.
- Line Elvstrøm Ekner & Emil Nejstgaard, 2013. "Parameter Identification in the Logistic STAR Model," Discussion Papers 13-07, University of Copenhagen. Department of Economics.
- Olivier Damette, 2013. "Mixture distribution hypothesis and the impact of a Tobin tax on exhange rate volatility : a reassessment," Working Papers of BETA 2013-07, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
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