New tools for dealing with errors-in-variables in DEA.

Errors in variables; Tool;

New Tools for Dealing with Errors-in-Variables in DEA.

We develop a series of novel conceptual tools to systematically account for errors-in-variables in Data Envelopment Analysis (DEA). These tools allow for statistical inference while requiring minimal statistical distribution assumptions, and therefore constitute a valuable addition to the tools currently available for dealing with errors-in-variables. An empirical application for large European Union financial institutions illustrates the proposed approach.Data Envelopment Analysis (DEA), errors-in-variables, efficiency depth, robust reference sets, financial institutions

QUALITY INDICATORS AND INTERMEDIATE PRODUCTS: A NON-PARAMETRIC APPROACH

In this paper we propose a methodology to measure the characteristics and composition of intermediate products using productivity indicators based on directional distance functions. We evaluate how quality attributes interact with the quantity level in grapes production, and find evidence of a trade-off between quantity and aggregate quality for Chardonnay.Marketing,

Resistant estimates for high dimensional and functional data based on random projections

We herein propose a new robust estimation method based on random projections that is adaptive and, automatically produces a robust estimate, while enabling easy computations for high or infinite dimensional data. Under some restricted contamination models, the procedure is robust and attains full efficiency. We tested the method using both simulated and real data.Comment: 24 pages, 6 figure