t his paper investigates the asymmetric behavior of inflation. we use logistic smooth transition autoregressive (lstar) model to characterize the regime-switching behavior of iran’s monthly inflation during the period may 1990 to december 2013. we find that there is a triple relationship between the inflation level, its fluctuations and persistence. the findings imply that the behavior of infla...

A smooth transition autoregressive model is estimated for the Southern Oscillation Index, an index commonly used as a measure of El Niño events. Using standard measures there is no indication of nonstationarity in the index. A logistic smooth transition autoregressive model describes the most turbulent periods in the data (these correspond to El Niño events) better than a linear autoregressive ...

This paper features an analysis of major currency exchange rate movements in relation to the US dollar, as constituted in US dollar terms. Euro, British pound, Chinese yuan, and Japanese yen are modelled using a variety of non-linear models, including smooth transition regression models, logistic smooth transition regressions models, threshold autoregressive models, nonlinear autoregressive mod...

A new class of Smooth Transition Autoregressive models, based on cubic spline type transition functions, has been introduced and subjected to comparison with models based on the traditional logistic transition functions. A very high degree of similarity between the two model classes has been demonstrated. The new class of models can be slightly preferable because of its more simple formal and g...

In this paper, we consider a flexible smooth transition autoregressive (STAR) model with multiple regimes and multiple transition variables. This formulation can be interpreted as a time varying linear model where the coefficients are the outputs of a single hidden layer feedforward neural network. This proposal has the major advantage of nesting several nonlinear models, such as, the Self-Exci...

This paper introduces new LM specification procedures to choose between Logistic and Exponential Smooth Transition Autoregressive (ST AR) models and to improve testing for nonlinearities. The selection procedures introduced here are simpler and have better consistency and power properties than those previously available in the literature. These improvements result from analyzing the properties ...

Logistic smooth transition and Markov switching autoregressive models of a logistic transform of the monthly US unemployment rate are estimated by Markov chain Monte Carlo methods. The Markov switching model is identified by constraining the first autoregression coefficient to differ across regimes. The transition variable in the LSTAR model is the lagged seasonal difference of the unemployment...