An important issue in the analysis of cross-sectional dependence which has received renewed interest in the past few years is the need for a better understanding of the extent and nature of such cross dependencies. In this paper we focus on measures of cross-sectional dependence and how such...

We consider an alternative use of simulation in the context of using the Likelihood-Ratio statistic to test non-nested models. To date simulation has been used to estimate the Kullback-Leibler measure of closeness between two densities, which in turn ‘mean adjusts’ the Likelihood-Ratio...

This paper considers information criteria as model evaluation tools for nonlinear threshold models. Results concerning the consistency of information criteria in selecting the lag order of linear autoregressive models are extended to nonlinear autoregressive threshold models. Extensive Monte...

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross section dependence. A popular method for modelling such dependence uses a factor error structure. Such models raise new problems for estimation and inference. This paper compares...

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recent work by Pesaran (2006) suggests a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error...

This paper presents the theoretical development of new threshold autoregressive models based on trended time series. The theoretical arguments underlying the models are outlined and a nonlinear economic model is used to derive the specification of the empirical econometric models. Estimation and...