This paper provides a general methodology for testing for dependence in time series data, with particular emphasis given to non-Gaussian data. A dynamic model is postulated for a continuous latent variable and the dynamic structure transferred to the non-Gaussian, possibly discrete,...

Most of the literature on testing ARCH models focuses on the null hypothesis of no-ARCH effects. In this paper, we consider the general problem of testing any possible set of coefficient values in ARCH models, which may be non-stationary, with Gaussian and non-Gaussian errors, as well as with...

In this paper we propose a new test statistic that considers multiple structural breaks to analyse the non-stationarity of a panel data set. The methodology is based on the common factor analysis in an attempt to allow for some sort of dependence across the individuals. Thus allowing for...

This paper uses the approach of Im, Pesaran and Shin (2003) to propose seasonal unit root tests for dynamic heterogeneous panels based on the means of the individuals HEGY test statistics. The standardised t-bar and F-bar statistics are simply averages of the HEGY tests across groups. These...

This paper proposes bootstrap versions of the seasonal unit root tests of, inter alia, Hylleberg, Engle, Granger and Yoo (1990,Journal of Econometrics 55, 305-328)[HEGY]. We report a simulation study of the properties of both the conventional and bootstrapped seasonal unit root tests when...

Procedures are developed to compute the proportion of turning points located in the sample path of time series data. It is shown that the proportion of turning points can be directly related to the data generating process. Methods for estimating model parameters are developed using counts of...