This article uses Data Envelopment Analysis (DEA) in order to determine the performance levels of 16 departments of a public owned university. Particularly, the constant returns to scale (CRS) and variable returns to scale (VRS) models have been applied alongside with bootstrap techniques in...

In this paper, we have proposed a general approach to obtain a projection of the nearest targets and minimum distance for a given unit. The method takes undesirable output into account. The idea behind it is that nearest targets and minimum distance lead to less variation in inputs and outputs...

This paper discusses a universal approach to the construction of confidence regions for level sets {h(x)≥0}⊂Rq of a function h of interest. The proposed construction is based on a plug-in estimate of the level sets using an appropriate estimate ĥn of h. The approach provides finite sample...

We propose a new method to estimate the empirical pricing kernel based on option data. We estimate the pricing kernel nonparametrically by using the ratio of the risk-neutral density estimator and the subjective density estimator. The risk-neutral density is approximated by a weighted kernel...

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.

The commonly used survey technique of clustering introduces dependence into sample data. Such data is frequently used in economic analysis, though the dependence induced by the sample structure of the data is often ignored. In this paper, the effect of clustering on the non-parametric, kernel...

This paper presents an analysis of changes in the distribution of gross household income and income inequality over the period 1983–1998. The analysis applies a semiparametric approach to study the effects of changes in the distribution of household types, and changes in National...

We propose a simulated maximum likelihood estimator for dynamic models based on non-parametric kernel methods. Our method is designed for models without latent dynamics from which one can simulate observations but cannot obtain a closed-form representation of the likelihood function. Using the...

We propose new tools for visualizing large numbers of functional data in the form of smooth curves or surfaces. The proposed tools include functional versions of the bagplot and boxplot, and make use of the first two robust principal component scores, Tukey's data depth and highest density...