In the analysis of time series, it is frequent to classify perturbations as Additive Outliers (AO), Innovative Outliers (IO), Level Shift (LS) outliers or Transitory Change (TC) outliers. In this paper, a new outlier type, the Seasonal Level Shift (SLS), is introduced in order to complete the...

In the analysis of time series, it is frequent to classify perturbations as Additive Outliers (AO), Innovative Outliers (IO), Level Shift (LS) outliers or Transitory Change (TC) outliers. In this paper, a new outlier type, the Seasonal Level Shift (SLS), is introduced in order to complete the...

This paper is concerned with the subject of how the three main approaches to model aggregate fluctuations are related. That is, we are interested in the relation between real business cycle models, endogenous business cycle models and sunspot equilibria models. It is shown that there exists an...

In this paper, the authors provide some asymptotic results for the J-type test on non-nested hypotheses proposed by Davidson and MacKinnon (1981), in the context of I(1) time series.

This paper proposes a new kind of asymmetric GARCh where the conditional variance obeys two different regimes with a smooth transition function. In one formulation variance reacts differently to negative and positive shocks while a second formulation, small and big shocks have separate effects.

This paper considers the Bayesian analysis of threshold regression models. It shows that this analysis can be conducted with simple deterministic numerical integration in one or two dimensions. The shape of the posterior density is greatly determined by the type of threshold and of transition...

In order to obtain exact distributional results without imposing restrictive parametric assumptions, various rank counterparts of the Dickey-Fuller statistic are considered. In particular, a rank counterpart of the score statistic is suggested which appears to have attractive theoretical...

In this paper we address the issue of the efficient estimation of the cointegrating vector in linear regression models with variables that follow general (higher order and fractionally) integrated processes.

The paper deals with estimation of missing observations in possibly nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analysed. Using the inverse or dual autocorrelation function it is seen how estimation of a missing observation is...

We propose a new method, the "Auto-SLEX" method, for analyzing bivariate non-stationary processes. The Auto-SLEX method is a procedure that automatically segments the time series into approximatively stationary blocks and automatically estimates the time-varying spectra and coherence.