Risk attitude and perception is reflected in brain reactions during RPID experiments. Given the fMRI data, an important research question is how to detect risk related regions and to investigate the relation between risk preferences and brain activity. Conventional methods are often insensitive...

This discussion paper led to an article in <I>Applied Geography</I> (2014). Volume 49(SI), pages 24-36.<P> The strong world-wide urbanisation trend calls for a repositioning of cities, especially the large cities with a global impact. These cities tend to become economic, logistic and political...</p></i>

The vast majority of spatial econometric research relies on the assumption that the spatial network structure is known a priori. This study considers a two-step estimation strategy for estimating the <em>n(n-1)</em> interaction effects in a spatial autoregressive panel model where the spatial dimension...

The purpose of this paper is to identify and study the main determinants of international tourism demand with special reference to Tunisia over the period 1994–2012. The empirical study is based on estimations of GMM dynamic panel data model. Using a sample of 47 generating countries,...

The classical Chow test for structural instability requires strictly exogenousregressors and a break-point specified in advance. In this paper, we consider twogeneralisations, the one-step recursive Chow test (based on the sequence of studentisedrecursive residuals) and its supremum counterpart,...

After the crisis of 2008, and the important losses and shortfall in capital that it revealed, regulators conducted massive stress testing exercises in order to test the resilience of financial institutions in times of stress conditions. In this context, and considering the impact of these...

Several methods have been proposed in the last few years for evaluating uncertainty in forecasts produced by nonlinear econometric models. Some methods resort to Monte Carlo, while others resort to different simulation techniques. This work aims at comparing these methods by means of experiments...

When econometric models are used as forecasting tools, forecast errors can be decomposed into several components, one of which is due to estimation errors, while another one is due to the stochastic nature of the variables to be predicted. Conditional on model's specification and on the...

Most of the methods proposed in the literature for evaluating forecast uncertainty in econometric models need an estimate of the structural coefficiencs covariance matrix among input data. When estimation is performed with full information maximum likelihood, alternative estimators of such a...