Normality is often mechanically and without sufficient reason assumed in econometric models. In this paper three important and significantly heteroscedastic GDP series are studied. Heteroscedasticity is removed and the distributions of the filtered series are then compared to a Normal, a...

In this paper we propose a new nonparametric kernel based estimator for a density function $f$ which achieves bias reduction relative to the classical Rosenblatt-Parzen estimator. Contrary to some existing estimators that provide for bias reduction, our estimator has a full asymptotic...

This paper demonstrates an evaluation of 71 developed and under-developed countries’ biodiversity performance using a methodological framework based to the new advances of Data Envelopment Analysis (DEA). By using conditional DEA, bootstrapping and kernel density estimations, efficiency levels...

This paper examines the current state of price convergence amongst the eleven initial EMU member states. Special attention is given to possible changes in the convergence process during the euro cash changeover. We apply the convergence approach using both panel estimates of changes in the...

This paper shows that recent published mortality projections with unobserved exposure can be understood as structured density estimation. The structured density is only observed on a sub-sample corresponding to historical calendar times. The mortality forecast is obtained by extrapolating the...

Lindsay (1994) provided a general set up in discrete models for minimum disparity estimation. Such a set up eludes us in continuous models. We provide such a general result and hence fill up a major gap in the literature.