Gary Simpson

Negative data in DEA: A directional distance approach applied to bank branches

This paper is drawn from the use of data envelopment analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but apart from some exceptions, traditional DEA models have hitherto been restricted to non-negative data. We report on the development of a model to handle unrestricted data in a DEA framework and illustrate the use of this model on data from the bank concerned.

Assessing pupil and school performance by non-parametric and parametric techniques

AbstractThis paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall inefficiency of a unit (a pupil) into a unit specific and a higher level (a school) component. By a sample of entry and exit attainments of 3017 girls in British ordinary single sex schools, we test the robustness of the non-parametric and parametric estimates. Finally, the paper uses the traditional MLM model in a best practice framework so that pupil and school efficiencies can be computed.

A Path Dependent Contingent-Claims Approach to Capacity Investments

This note presents a contingent-claims approach to strategic capacity planning. We develop models for capacity choice and expansion decisions in a single firm environment where investment is irreversible and demand is uncertain. These models illustrate specifically the relevance of path-dependent options analysis to planning capacity investments when the firm adopts demand tracking or average capacity strategies. It is argued that Asian/average type real options can explain hysteresis phenomena in addition to providing superior control of assets in place.

Programmatic efficiency comparisons between unequally sized groups of DMUs in DEA

Data envelopment analysis (DEA) is a popular non-parametric technique for determining the efficiency of a homogeneous set of decision-making units (DMUs). In many practical cases, there is some doubt if the all the DMUs form a single group with a common efficiency distribution. The Mann–Whitney rank statistic has been used in DEA both to test if two groups of DMUs come from a common efficiency distribution and also to test if the two groups have a common frontier, each of which are likely to have important but different policy implications for the management of the groups. In this paper it is demonstrated that where the Mann–Whitney rank statistic is used for the second of these it is likely to overestimate programmatic inefficiency, particularly of the smaller group. A new non-parametric statistic is proposed for the case of comparing the efficient frontiers of two groups, which overcomes the problems we identify in the use of the Mann–Whitney rank statistic for this purpose.

Dealing With Outliers When Setting Targets by DEA

Thanassoulis and Simpson (1999) outlined an approach for setting targets by DEA for individuals that will be realistic yet demanding. The approach featured the use of DEA to identify ‘exceptional’ individuals who should be dropped as potential referents so that the targets would be more realistic. The paper used the example of setting achievement targets for school children. Tie technical details to identifying exceptional individuals were contained in an Appendix that was inadvertently omitted from Thanassoulis and Simpson (1999). This note presents the Appendix both in the context of setting targets and more generally as a method for identifying outliers.