Stephen Haag

Sensitivity of efficiency classifications in the additive model of data envelopment analysis

In contrast to existing sufficient conditions for preservation of efficiency under special perturbations and matrix structural assumptions, sensitivity of the additive models classifications in data envelopment analysis (DEA) is investigated by means of new DEA formulations focusing on the stability (sensitivity) of an organizations classification (whether efficient or inefficient). The formulations for the additive model are linear programming problems whose solutions yield a particular region of stability, a ‘cell’, in which an organizations classification remains unchanged. The largest such cell can always be easily computed for each organization and additionally theoretically characterized simply as optimal solutions of particular linear programming problems.

Assessing the relative efficiency of agricultural production units in the Blackland Prairie, Texas

The way in which data envelopment analysis (DEA) can be used to assess the relative technical efficiency of agricultural production units is illustrated. Two variants of the existing DEA additive model introduced, each eliminating earlier difficults encountered inapplication and theory. These new models are demonstrated through application to agricultural data obtained from the Blackland Prairie, Texas.

Efficient provision of child quality of life in less developed countries: conventional development indexes versus a programming approach to development indexes

Abstract Using a linear programming approach, we establish a child quality of life (CQL) index by evaluating the ability of a less developed country (LDC) to maximize specific child development goals subject to minimizing specific resource availability indicators. This approach — which ranks LDCs from the most robustly efficient to the most robustly in efficient in their ability to maximize goals while minimizing resource utilization — avoids using equal or subjective weights employed in conventional ranking schemes. The ranking of the 38 LDCs yields unexpected results and suggests a very different way of measuring and evaluating development policy.

An Income Efficiency Model Approach to the Economic Consequences of Osha Cotton Dust Regulation

This paper used Data Envelopment Analysis IDEA) to test the economic consequences of the Occupational Health and Safety Administration (OSHA) cotton dust standards by comparing the relative efficiency of firms affected by cotton dust in SIC 2200 and 2300 for the years before and after the Supreme Court upheld the regulation in 1981. Accounting-based inputs of common equity, total assets and production costs were minimized, while total revenue was maximized. Using available Compustat firms, we found that the surviving firms under stiff foreign competition had become more efficient during the post-regulatory period as predicted. The results indicate the usefulness of DEA as an alternative method of testing the economic consequences of a regulation.