For testing lack of correlation against spatial autoregressive alternatives, Lagrange multiplier tests enjoy their usual computational advantages, but the (χ2) first-order asymptotic approximation to critical values can be poor in small samples. We develop refined tests for lack of spatial...

Individual and household based aggregate measures of worklessness can, and do, offer conflicting signals about labour market performance. We outline a means of quantifying the extent of any disparity, (polarisation), in the signals stemming from individual and household-based measures of...

The 2004 Presidential Election in Mozambique was marred by allegations of fraud. We assess the validity of these allegations by testing whether or not qualitative descriptions of the methods and locations of misconduct are consistent with a series of simple quantitative tests. Most studies of...

Economic evaluation of climate policy traditionally treats uncertainty by appealing to expected utility theory. Yet our knowledge of the impacts of climate policy may not be of sufficient quality to justify probabilistic beliefs. In such circumstances, it has been argued that the axioms of...

We introduce a notion of median uncorrelation that is a natural extension of mean (linear) uncorrelation. A scalar random variable Y is median uncorrelated with a kdimensional random vector X if and only if the slope from an LAD regression of Y on X is zero. Using this simple definition, we...

The Story of the Hats is a puzzle in social epistemology. It describes a situation in which a group of rational agents with common priors and common goals seems vulnerable to a Dutch book if they are exposed to different information and make decisions independently. Situations in which this...

In this paper, we obtain the density function of the single barrier one-sided Parisian stopping time. The problem reduces to that of solving a Volterra integral equation of the first kind, where a recursive solution is consequently obtained. The advantage of this new method as compared to that...

We propose to model multivariate volatility processes on the basis of the newly defined conditionally uncorrelated components (CUCs). This model represents a parsimonious representation for matrix-valued processes. It is flexible in the sense that each CUC may be fitted separately with any...

We suggest two improved methods for conditional density estimation. The rst is based on locally tting a log-linear model, and is in the spirit of recent work on locally parametric techniques in density estimation. The second method is a constrained local polynomial estimator. Both methods always...

Typically, in many studies in ecology, epidemiology, biomedicine and others, we are confronted with panels of short time–series of which we are interested in obtaining a biologically meaningful grouping. Here, we propose a bootstrap approach to test whether the regression functions or the...