In this paper we propose a method for determining the number of regimes in threshold autoregressive models using smooth transition autoregression as a tool. As the smooth transition model is just an approximation to the threshold autoregressive one, no asymptotic properties are claimed for the proposed method. Tests available for testing the adequacy of a smooth transition autoregressive model ...

In this paper we examine the forecast accuracy of four univariate time series models for 47 macroeconomic variables of the G7 economies. The models considered are the linear autoregressive model, the smooth transition autoregressive model, and two neural network models. The two neural network models are different because they are specified using two different techniques. Forecast accuracy is as...

This paper considers a linear model with time varying parameters controlled by a neural network to analyze and forecast nonlinear time series.We show that this formulation, called neural coefficient smooth transition autoregressive (NCSTAR) model, is in close relation to the threshold autoregressive (TAR) model and the smooth transition autoregressive (STAR) model with the advantage of naturall...

T his paper proposes a new unit root test against the alternative of symmetric or asymmetric exponential smooth transition autoregressive (AESTAR) nonlinearity that accounts for multiple smooth breaks. We provide small sample properties which indicate the test statistics have good empirical size and power. Also, we compared small sample properties of the test statistics with Christop...

This paper proposes an alternative representation of the original version of the Logistic Smooth Transition Auto-Regressive (LSTAR) model. The Logistic Smooth Transition Auto-Regressive (LSTAR) and Exponential Smooth Transition Auto-Regressive (FSTAR) models are frequently used in empirical research. The LSTAR model describes asymmetrical nonlinear adjustment process, while the ESTAR model desc...

the price of oil plays an important role in the global economy and is an important factor influencing the government and commercial sectors. because of increasing importance of oil in financial markets, oil price predictions have always been an important subject for the researchers in economics, and other economic agents. this paper tries to study the behavior of crude oil prices based on smoot...

In this thesis, we study a smooth-transition type of nonlinear cointegration among a dynamic system. Base on the Logistic Smooth Transition Autoregressive (LSTAR) models, the definition of cointegration which is extended form Engle and Granger (1987)’s definition of linear cointegration is introduced. Then statistical test for linear cointegration against nonlinear cointegration is derived. The...

In this paper we propose the Gaussian Dynamic Bayesian Smooth Transition Autoregressive (DBSTAR) models for nonlinear autoregressive time series processes as alternative to both the classical Smooth Transition Autoregressive (STAR) models of Chan and Tong (1986) and the computational Bayesian STAR (CBSTAR) models of Lopes and Salazar (2005). The DBSTAR models are autoregressive formulations of ...