Smooth transition autoregressive models are a flixible family of nonlinear time series models that have also been used for modelling economic data. This paper contributes to the evaluation stage of a proposed specification, estimation, and evaluation cycle of this models by introducing a...

This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive...

This paper studies a class of Markov models which consist of two components. Typically, one of the components is observable and the other is unobservable or 'hidden'. Conditions under which (a form of) geometric ergodicity of the unobservable component is inherited by the joint process formed of...

The asymmetric power ARCH model is a recent addition to time series models that may be used for predicting volatility. Its performance is compared with that of standard models of conditional heteroskedasticity such as GARCH. This has previously been done empirically. In this paper the same issue...

Starting from a linear error correction model the stability and linearity of a German M1 moneyt demand function are investigated, applying smooth transition regression techniques. Using seasonally unadjusted data from 1961 (1) to 1990 (2) it is found that the money demand equation is both linear...

The detection of structural change and determination of lag lengths are long-standing issues in time series analysis. This paper demonstrates how these can be successfully married in a Bayesian analysis. By taking account of the inherent uncertainty about the lag length when deciding on the...

This paper analyzes the net barter terms of trade measured by the primary commodity price index relative to the index of unit values of export of manufactures from industrial countries. The starting-point is that the series is stationary but possibly nonlinear. Statistical tests indicate that...

We consider a family of GARCH(1,1) processes introduced in He and Teräsvirta (1999a). This family contains various popular GARCH models as special cases. A necessary and sufficient condition for the existence of a strictly stationary solution is given.

This paper presents a new dynamic ARCH-related conditionally heteroscedastic stochastic frontier model specification where firm and time-specific technical inefficiency is represented by an autoregressive stochastic process in the error components. Monte Carlo results reveal that a one-sided...

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained in the general...