Consistent proportional trade-offs in data envelopment analysis

Proportional trade-offs – as an enhanced form of the conventional absolute trade-offs – have recently been proposed as a method which can be used to incorporate prior views or information regarding the assessment of decision making units (DMUs) into relative efficiency measurement systems by Data Envelopment Analysis (DEA). A proportional trade-off is defined as a percentage change of the level of inputs/outputs so that the corresponding restriction is adapted with respect to the volume of the inputs and outputs of the DMUs in the analysis. It is well-known that the incorporation of trade-offs either in an absolute form or proportional form may lead in certain cases to serious problems such as infinity or even negative efficiency scores in the results. This phenomenon is often interpreted as a result of defining the set of trade-offs carelessly by the analyst. In this paper we show that this may not always be the case. The existing framework by which the trade-offs are combined mathematically to build a corresponding production technology may cause a problem rather than the definition of the trade-offs. We therefore develop analytical criteria and formulate computational methods that allow us to identify the above-mentioned problematic situations and test if all proportional trade-offs are consistent so that they can be applied simultaneously. We then propose a novel framework for aggregating local sets of trade-offs, which can be combined mathematically. The respective computational procedure is shown to be effectively done by a suggested algorithm. We also illustrate how the efficiency can be measured against an overall technology, which is formed by the union of these local sets. An empirical illustration in the context of engineering schools will be presented to explain the properties and features of the suggested approach

The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia

Most applications of data envelopment analysis (DEA) employ standard constant or variable returns-to-scale models. In this paper we suggest that these models may sometimes underutilize our knowledge of the underlying production process. For example, in the context of higher education considered in the reported application, individual universities often maintain a certain student-to-staff ratio which points that there should be an approximately proportional relationship between students and staff, at least in the medium to long run.Adifferent example is an observation that the teaching of postgraduate students generally requires more resources than the teaching of the same number of undergraduate students. In order to incorporate such information in a DEA model, we propose a novel approach that combines the recently developed hybrid returns-to-scale DEA model with the use of production trade-offs. The suggested approach leads to a better-informed model of production technology than the conventional DEA models. We illustrate this methodology by an application to Malaysian public universities. This approach results in a tangibly better efficiency discrimination than would be possible with the standard DEA models

The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia

Most applications of data envelopment analysis (DEA) employ standard constant or variable returns-to-scale (CRS or VRS) models. In this paper we suggest that these models may sometimes underutilize our knowledge of the underlying production process. For example, in the context of higher education considered in the reported application, individual universities often maintain a certain student-to-staff ratio which points that there should be an approximately proportional relationship between students and staff, at least in the medium to long run. A different example is an observation that the teaching of postgraduate students generally requires more resources than the teaching of the same number of undergraduate students. In order to incorporate such information in a DEA model, we propose a novel approach that combines the recently developed hybrid returns-to-scale DEA model with the use of production trade-offs. The suggested approach leads to a better-informed model of production technology than the conventional DEA models. We illustrate this methodology by an application to Malaysian public universities. This approach results in a tangibly better efficiency discrimination than would be possible with the standard DEA models

The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia

The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-015-1854-0Most applications of data envelopment analysis (DEA) employ standard constant or variable returns-to-scale (CRS or VRS) models. In this paper we suggest that these models may sometimes underutilize our knowledge of the underlying production process. For example, in the context of higher education considered in the reported application, individual universities often maintain a certain student-to-staff ratio which points that there should be an approximately proportional relationship between students and staff, at least in the medium to long run. A different example is an observation that the teaching of postgraduate students generally requires more resources than the teaching of the same number of undergraduate students. In order to incorporate such information in a DEA model, we propose a novel approach that combines the recently developed hybrid returns-to-scale DEA model with the use of production trade-offs. The suggested approach leads to a better-informed model of production technology than the conventional DEA models. We illustrate this methodology by an application to Malaysian public universities. This approach results in a tangibly better efficiency discrimination than would be possible with the standard DEA models

Analysing the Research and Teaching Quality Achievement Frontier

The paper analyses the nature of the achievement possibility frontier between research and teaching quality in higher education under a system of quality evaluation by reference to discrete quality grades. It finds several important reasons why the associated feasible set is likely to be non-convex, and hence where the assumptions of the widely used nonparametric frontier performance analysis technique of Data Envelopment Analysis are no longer valid. The paper therefore investigates the use of the alternative Free Disposal Hull technique, and compares the results of deploying these techniques to the performance evaluation of UK Departments of Economics.Research and teaching quality, Higher education, Departments of Economics, Data Envelopment Analysis (DEA), Free Disposal Hull

Do the opportunity costs of providing crop diversity differ between organic and conventional farms? The case of Finnish agriculture

The attractiveness of targeted environmental policies on farmlands depends crucially on the opportunity costs of the conservation programs. We use a crop diversity index as an indicator of environmental output to compare the efficiency of conventional and organic crop farms. Technical efficiency scores are estimated by applying data envelopment analysis to a sample of Finnish farms for the period 1994 – 2002. We also estimate shadow values, or the opportunity costs, of producing crop diversity. Our results show that there is variation in the shadow values between farms and the technology adopted. The findings provide a basis for designing cost-effective policy instruments such as auctions for conservation payments

Using data envelopment analysis for the efficiency and elasticity evaluation of agricultural farms

Data Envelopment Analysis (DEA) is a well-established relative efficiency measurement technique, which has been widely applied to evaluate the technical efficiency of agricultural units in different countries by focusing on different aspects of agricultural production. This research deals with the evaluation of efficiency through DEA in non-homogeneous agricultural production, where units produce a wide range of different outputs. The objectives are threefold. Firstly, we propose a novel methodological approach of integrating the production trade-offs concept of DEA into non-homogeneous agricultural efficiency evaluation to prevent the overstatement of the efficiency of specialist farms and overcome the issue of insufficient discrimination due to large number of outputs in the models. Secondly, we aim to integrate this methodological perspective to the theory of elasticity measurement on DEA frontiers. The efficient frontiers of DEA are not defined in functional forms as in the classical economic theory, therefore obtaining elasticity measures on them require different considerations. We introduce the production trade-offs to the elasticity measurement and derive the necessary models to calculate the elasticities of response in the presence of production trade-offs. As a third objective, before moving to the introduction of the trade-offs in elasticity measurement, for theoretical completeness, we first consider the elasticity measurement on DEA frontiers of constant returns-to-scale (CRS) technologies. Our proposed methodology and all the developed elasticity theory are illustrated in a real world case of Turkish agricultural sectors. We provide extensive empirical applications covering all the proposed theory and methodology. Among the results of this research, we provide an elasticity measurement framework, which enables us to calculate elasticities of response measures in both VRS and CRS technologies, with or without production tradeoffs included. We observe that the integration of production trade-offs provide better discrimination of efficiency scores compared to the models without trade-offs included. We also investigate how changing production trade-offs affect the efficiency and elasticity measures of the evaluated units

DEA-Based Incentive Regimes in Health-Care Provision

A major challenge to legislators, insurance providers and municipalities will be how to manage the reimbursement of health-care on partially open markets under increasing fiscal pressure and an aging population. Although efficiency theoretically can be obtained by private solutions using fixed-payment schemes, the informational rents and production distortions may limit their implementation. The healthcare agency problem is characterized by (i) a complex multi-input multi-output technology, (ii) information uncertainty and asymmetry, and (iii) fuzzy social preferences. First, the technology, inherently nonlinear and with externalities between factors, yield parametric estimation difficult. However, the flexible production structure in Data Envelopment Analysis (DEA) offers a solution that allows for the gradual and successive refinement of potentially nonconvex technologies. Second, the information structure of healthcare suggests a context of considerable asymmetric information and considerable uncertainty about the underlying technology, but limited uncertainty or noise in the registration of the outcome. Again, we shall argue that the DEA dynamic yardsticks (Bogetoft, 1994, 1997, Agrell and Bogetoft, 2001) are suitable for such contexts. A third important characteristic of the health sector is the somewhat fuzzy social priorities and the numerous potential conflicts between the stakeholders in the health system. Social preferences are likely dynamic and contingent on the disclosed information. Similarly, there are several potential hidden action (moral hazard) and hidden information (adverse selection) conflicts between the different agents in the health system. The flexible and transparent response to preferential ambiguity is one of the strongest justifications for a DEA-approach. DEA yardstick regimes have been successfully implemented in other sectors (electricity distribution) and we present an operalization of the power-parameter p in an pseudo-competitive setting that both limits the informational rents and incites the truthful revelation of information. Recent work (Agrell and Bogetoft, 2002) on strategic implementation of DEA yardsticks is commented in the healthcare context, where social priorities change the tradeoff between the motivation and coordination functions of the yardstick. The paper is closed with policy recommendations and some areas of further work.Data Envelopment Analysis, regulation, health care systems, efficiency, Health Economics and Policy,

Comparative evaluation of public universities in Malaysia using data envelopment analysis

Applications of Data Envelopment Analysis (DEA) for the assessment of performance of universities have been widely reported in the literature. Often the number of universities under the assessment is relatively small compared to the number of performance measures (inputs and outputs) used in the analysis, which leads to a low discriminating power of DEA models on efficiency scores. The main objective of this thesis is the development of improved DEA models that overcome the above difficulty, using a sample of public universities in Malaysia as an illustrative application. The proposed new approach combines the recently introduced Hybrid returns to scale (HRS) model with the use of additional information about the functioning of universities stated in the form of production trade-offs. The new model developed in this thesis, called Hybrid returns to scale model with trade-offs (HRSTO), is applied to a sample of eighteen universities, which is considered to be a very small sample for the DEA methodology. Our results show that, in contrast with standard DEA models, the new model is perfectly suitable for such samples and discriminates well between good and bad performers. The proposed combined use of HRS model with production trade-offs is a novel methodology that can be used in other applications of DEA. Overall, the thesis makes several contributions of the theory and practice of DEA. First, for the first time, it is shown that the higher education sector satisfies the assumptions and can be modelled using the proposed HRSTO model. Second, also for the first time, it is shown that production trade-offs can be assessed for such applications and the methodology of their assessment has been developed and used in the thesis. Third, it is demonstrated that the HRSTO model significantly improves the discriminating power of analysis compared to standard DEA models, which is particularly important for small data sets. Fourth, it is concluded that the HRS model is further improved if production trade-offs are used. Fifth, by experimenting with different specific values of production trade-offs, it is shown that even the most conservative estimates of trade-offs notably improve the model. Finally, our results contribute to the more general discussion of the performance of universities in Malaysia and identification of the best performers among them

EFFICIENCY IN AGRICULTURAL PRODUCTION OF BIODIVERSITY: ORGANIC VS. CONVENTIONAL PRACTICES

Promotion of environmental sustainable farming practices is an important policy goal for the whole agricultural sector. However, when the efficiency of production is measured in practice, enhancement of environmental quality such as biodiversity and other environmental amenities does not seem to be recognized as a positive output produced by agriculture. Here, we include crop diversity index as an indicator of environmental output in a comparison of efficiency of conventional and organic crop farms. Non-parametric technical efficiency scores are estimated applying data envelopment analysis on a sample of Finnish crop farms for 1994 – 2002. The results show that in a pooled data set conventional crop farms are more technically efficient than organic farms when only crop output is considered. When taking crop diversity into account the difference between production techniques vanishes. In separate comparisons of conventional and organic farms, the average efficiencies of the two groups do not differ statistically significantly. Thus, the assumptions on the technology and reference sets are crucial with respect to the results of the comparison. This has important implications for policy evaluations when alternative farming technologies are compared.crop diversity, Shannon index, DDEA, technical efficiency, Environmental Economics and Policy, Farm Management, Research Methods/ Statistical Methods,