Miki Tsutsui

Network DEA: A slacks-based measure approach

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them to DEA models, we propose a slacks-based network DEA model, called Network SBM, that can deal with intermediate products formally. Using this model we can evaluate divisional efficiencies along with the overall efficiency of decision making units (DMUs).

Economic impact of regulatory reforms in the electricity supply industry: a panel data analysis for OECD countries

Abstract This paper reexamines the impact of the regulatory reforms on price in the electricity supply industry, using panel data for 19 OECD countries for the period 1987–1999 and compares the results with those found in an earlier study by Steiner (Regulation, industry structure and performance in the electricity supply industry, OECD Economics Department Working Paper, ECO/WKP, 2000, p. 11). We found that expanded retail access is likely to lower the industrial price and increase the price differential between industrial customers and household customers, as expected. We also found that the unbundling of generation and the introduction of a wholesale spot market did not necessarily lower the price and may possibly have resulted in a higher price. This finding is not consistent with expectations and differs from Steiner (2000), but it is plausible in the light of recent experiences in many countries.

Comparison of Productive and Cost Efficiencies among Japanese and US Electric Utilities

Using Data Envelopment Analysis (DEA), this article measures both overall cost efficiency and technical efficiency to compare bilaterally between Japanese and US electric utilities in the annual periods from 1984 to 1993. Nine Japanese and 14 US vertically integrated investor-owned electric utilities are examined in this study. An intertemporal efficiency index, measuring the intertemporal shift of an efficiency frontier, is measured for the examination of productivity improvement over a time period. Country average overall cost efficiency indices are also proposed and broken down into technical, scale and allocative efficiencies in terms of cross-sectional and time-series performance analyses. The main empirical results include: (1) the overall cost efficiency of Japanese electric utilities was consistently higher than that of US electric utilities from 1984 to 1993; (2) Japanese utilities were more efficient than US utilities in terms of technical, allocative and scale efficiencies; (3) allocative inefficiency was a main source of overall cost inefficiency for the Japanese utilities. Our empirical results indicate that high electricity tariffs are mainly due to an excessive amount of capital investment, a source of allocative inefficiency, found in Japanese utilities. This finding may imply that electricity prices of Japanese utilities can be reduced by creating a free market where the utilities can increase inexpensive power purchase from independent power producers through competitive bidding, and/or they procure inexpensive equipments.

Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model.

The purpose of this study was to perform an interim evaluation of the policy effect of the current reform of Japan’s municipal hospitals. We focused on efficiency improvements both within hospitals and within two separate internal hospital organizations. Hospitals have two heterogeneous internal organizations: the medical examination division and administration division. The administration division carries out business management and the medical-examination division provides medical care services. We employed a dynamic-network data envelopment analysis model (DN model) to perform the evaluation. The model makes it possible to simultaneously estimate both the efficiencies of separate organizations and the dynamic changes of the efficiencies. This study is the first empirical application of the DN model in the healthcare field. Results showed that the average overall efficiency obtained with the DN model was 0.854 for 2007. The dynamic change in efficiency scores from 2007 to 2009 was slightly lower. The average efficiency score was 0.862 for 2007 and 0.860 for 2009. The average estimated efficiency of the administration division decreased from 0.867 for 2007 to 0.8508 for 2009. In contrast, the average efficiency of the medical-examination division increased from 0.858 for 2007 to 0.870 for 2009. We were unable to find any significant improvement in efficiency despite the reform policy. Thus, there are no positive policy effects despite the increased financial support from the central government.

An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency

Firstly, we discuss differences between Farrell and Pareto-Koopmans efficiency measures in DEA, and propose a composite method for discriminating them. Then, we extend the method to so-called “epsilon based-measure (EBM).” The EBM can examine the robustness and stability of efficiency measure of DMUs regarding parametric change of input multiplier variables. Lastly, we propose a scheme for selecting an appropriate value of epsilon with recourse to actual cost shares of input resources.

Bridging radial and non-radial measures of efficiency in DEA

Data envelopment analysis (DEA) has been utilized worldwide for measuring efficiencies of banks, telecommunications, electric utilities and so forth. Yet, the existing models have some well-known shortcomings that limit their usefulness. In DEA we have two fundamental approaches to measuring efficiency with very different characteristics; radial and non-radial. We demonstrate a method for linking these two approaches in a unified framework called Connected-SBM (slacks-based measure). It includes two scalar parameters, and by changing the parameter values we can relocate the analysis anywhere between the radial and the non-radial models. An appropriate choice of these parameters can overcome the key shortcomings inherent in the two approaches, namely, proportionality and mixed patterns of slacks.

How to Deal with Non-Convex Frontiers in Data Envelopment Analysis

In data envelopment analysis, we are often puzzled by the large difference between the constant-returns-scale and variable returns-to-scale scores, and by the convexity production set syndrome in spite of the S-shaped curve, often observed in many real data sets. In this paper, we propose a solution to these problems. Initially, we evaluate the constant-returns-scale and variable returns-to-scale scores for all decision-making units by means of conventional methods. We obtain the scale-efficiency for each decision-making unit. Using the scale-efficiency, we decompose the constant-returns-scale slacks for each decision-making unit into scale-independent and scale-dependent parts. Following this, we eliminate scale-dependent slacks from the data set, and thus obtain a scale-independent data set. Next, we classify decision-making units into several clusters, depending either on the degree of scale-efficiency or on some other predetermined characteristics. We evaluate slacks of scale-independent decision-making units within the same cluster using the constant-returns-scale model, and obtain the in-cluster slacks. By summing the scale-dependent and the in-cluster slacks, we define the total slacks for each decision-making unit. Following this, we evaluate the efficiency score of the decision-making unit and project it onto the efficient frontiers, which are no longer guaranteed to be convex and are usually non-convex. Finally, we define the scale-dependent data set by which we can find the scale elasticity of each decision-making unit. We apply this model to a data set of Japanese universities’ research activities.

Slacks-Based Network DEA

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs versus multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them to DEA models, we propose a slacks-based network DEA model that can deal with intermediate products formally. Using this model we can evaluate divisional efficiencies along with the overall efficiency of decision making units (DMUs).