Fernando Vidal

Accounting for slacks to measure and decompose revenue efficiency in the Spanish Designation of Origin wines with DEA

In this paper, we show how Data Envelopment Analysis (DEA) may be used to measure and decompose revenue inefficiency, taking into account all sources of technical waste in the context of an application to assess the Spanish quality wine sector, in particular Designation of Origin (DO) wines. We try to go beyond the standard approaches, which use Shephard distance functions or directional distance functions, to provide decomposition that incorporates slacks as a source of technical inefficiency. To accomplish this, we will base our analysis on a recent approach introduced in Cooper et al. (2011a). In particular, we show how an output-oriented version of the Weighted Additive model can be used to properly identify revenue, technical, and allocative inefficiencies in Spanish DOs. In the application, we conclude that the main source of revenue inefficiency in this sector is technical waste, and that Cava can be highlighted as the DO that performs as a benchmark for more numbers of units.

The weighted additive distance function

Distance functions in production theory are mathematical structures that characterize the belonging to the reference technology through a numerical value, behave as technical efficiency measures when the focus is analyzing an observed input–output vector within its production possibility set and present a dual relationship with some support function (profit, revenue, cost function). In this paper, we endow the well-known weighted additive models in Data Envelopment Analysis with a distance function structure, introducing the Weighted Additive Distance Function and showing its main properties.

Research Note: Efficiency in Attracting Tourists via the Web — An Application to the Mediterranean Countries

A key element of competitiveness in the tourism industry is the use of new information and communications technology (ICT). To analyse the efficiency in attracting tourists via the Web for a set of 16 Mediterranean countries, the authors use non-parametric bounded adjusted measure (BAM) models. Two models are proposed: the first analyses the influence of each countrys basic characteristics on the number of tourists who visit it, while the second relates these characteristics to the number of websites dedicated to tourism. The ordering provided by the two BAM models enables comparison of the efficiency in the real attraction of tourists with the effort of attracting them via the Web.

Bounded directional distance function models

AbstractBounded additive models in data envelopment analysis (DEA) under the assumption of constant returns to scale (CRS) were recently introduced in the literature (Cooper et al. in J Product Anal 35(2):85–94, 2011; Pastor et al. in J Product Anal 40:285–292, 2013; Pastor et al. in Omega 56:16–24, 2015). In this paper, we propose to extend the so far generated knowledge about bounded additive models to the family of directional distance function (DDF) models in DEA, giving rise to a completely new subfamily of bounded or partially-bounded CRS-DDF models. We finally check the new approach on a real agricultural panel data set estimating efficiency and productivity change over time, resorting to the Luenberger indicator in a context where at least one variable is naturally bounded.

The Reverse Directional Distance Function

The aim of any Data Envelopment Analysis (DEA) inefficiency model is to calculate the efficient projection of each unit belonging to a certain finite sample. The reverse directional distance function (RDDF) is a new tool developed in this chapter that allows us to express any known DEA inefficiency model as a directional distance function (DDF). Hence, given a certain DEA inefficiency model, its RDDF is a specific DDF that truly reproduces the functioning of the considered DEA model. Automatically, all the interesting properties that apply to any DDF are directly transferable to the considered DEA model through its RDDF. Hence, the RDDF enlarges the set of properties exhibited by any DEA model. For instance, given any DEA inefficiency model, its economic inefficiency—in any of its three possible versions—, can be easily defined and decomposed as the sum of technical inefficiency and allocative inefficiency thanks to the RDDF. We further propose to transform any non-strong DDF into a strong DDF, i.e., into a DDF that projects all the units onto the strongly efficient frontier. This constitutes another indication of the transference capacity of the RDDF, because its strong version constitutes in itself a strong version of the original DEA model considered. We further propose to search for alternative projections so as to minimize profit inefficiency, and add an appendix showing how to search for multiple optimal solutions in additive-type models.

La valoración de arbolado en España. Una revisión

In this paper we review the main methods of tree appraisal used in Spain. Methods are grouped by major trees utilities: fruit, forestry, environmental and ornamental. We intend to offer an overview of which have been and are the main applications of these methods and suggest the main lines of future works. KEYWORDs: Trees, forest, fruit, ornamental, appraisal. JEL classification: Q10, Q51, Q57, L73. DOI: 10.7201/earn.2012.01.05. DOI: 10.7201/earn.2012.01.05.