TD n. 571 2010

Michael McAller, Waldyr Dutra Areosa, Marcelo Medeiros.

http://dx.doi.org/10.1016/j.jeconom.2011.05.009

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, the 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 process, and have assumed a variety of assumptions, including stationary or cointegrated processes, uncorrelated and 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 instrumental variable 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 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 straightforward application of current results in the literature.

 

Publicado em  Journal of Econometrics, 165, 100-111, 2011