Moment-based estimation of smooth transition regression models with endogenous variables
AbstractNonlinear regression models have been widely used in practice for a variety of time series and cross-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 capturing asymmetric behavior. Most STR models have been applied to univariate processes, and have made a variety of assumptions, including stationary or cointegrated processes, uncorrelated, homoskedastic or conditionally heteroskedastic 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 relax the assumption of weakly exogenous regressors and to discuss moment based methods for estimating STR models. The paper analyzes the properties of the STR model with endogenous variables by providing a diagnostic test of linearity of the underlying process under endogeneity, developing an estimation procedure and a misspecification test for the STR model, presenting the results of Monte Carlo simulations to show the usefulness of the model and estimation method, and providing an empirical application for inflation rate targeting in Brazil. We show that STR models with endogenous variables can be specified and estimated by a straightforward application of existing results in the literature.
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Smooth transition; nonlinear models; nonlinear instrumental variables; generalized method of moments; endogeneity; inflation targeting.;
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.
- 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.
- NEP-ALL-2010-06-11 (All new papers)
- NEP-ECM-2010-06-11 (Econometrics)
- NEP-ETS-2010-06-11 (Econometric Time Series)
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