Record number :
2128842
Title of article :
Moment-based estimation of smooth transition regression models with endogenous variables
Author/Authors :
Areosa، نويسنده , , Waldyr Dutra and McAleer، نويسنده , , Michael and Medeiros، نويسنده , , Marcelo C.، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2011
Pages :
12
From page :
100
To page :
111
Abstract :
Nonlinear 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.
Keywords :
Smooth transition , nonlinear models , Inflation targeting , endogeneity , Generalized Method of Moments , Nonlinear instrumental variables
Journal title :
Journal of Econometrics
Serial Year :
2011
Link To Document :
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