Javier Salinas-Jiménez

On the Role of Weight Restrictions in Data Envelopment Analysis

This paper examines the role that weight restrictions play in Data Envelopment Analysis (DEA). It is argued that the decision to include a factor (input or output) in a DEA model represents an implicit judgement that the factor has a non-trivial weight. It therefore seems perverse to allow DEA to assign a trivial weight to that factor in assessing the efficiency of a unit. There is therefore a strong case for imposing restrictions on factor weights. However, many existing methods of weight restriction are in practice unwieldy. This paper proposes an alternative approach we term contingent weight restriction which is both practical and intellectually consistent with the DEA philosophy. The paper explores the implications of alternative methods of weight restriction using simulated data from a well known production process.

Data envelopment analysis applied to quality in primary health care

The performance of primary care should ultimately be judged on its effect on the health outcome of individual patients. However, for the foreseeable future, it is inconceivable that the outcome data necessary to come to a judgement on performance will be available. And in any case, specification of the statistical model necessary to analyze outcome is fraught with difficulty. This paper therefore sets out a model of primary care performance which is based on the premise that certain measurable quality indicators can act as proxies for outcome. This being the case, a model of performance can be deduced which takes into account the effect of resources and patient characteristics on outcome. The most appropriate analytic technique to make this model operational is data envelopment analysis (DEA). It is argued that DEA can handle multiple dimensions of performance more comfortably, and is less vulnerable to the misspecification bias that afflicts statistically based models. The issues are illustrated with an example from English Family Health Service Authorities.

Measuring efficiency in education: an analysis of different approaches for incorporating non-discretionary inputs

Measuring efficiency in the education sector is a highly complex task. One of the reasons is that the main resource of schools (the type of students they have) lie outside of their control, which means that it must be treated differently to other factors in analysis. This study examines the different options available in the literature for incorporating non-controllable inputs in a data envelopment analysis in order to determine the most appropriate model for evaluating schools. Our empirical study presents the results obtained using the model proposed by Fried et al . (1999), though we use bootstrap techniques to avoid problems of bias in the estimations.

An assessment of the efficiency of Spanish Courts using DEA

The objective is to provide a measure of technical efficiency of the Administrative Litigation Division of the Spanish High Courts. The concept of efficiency to be measured and the most adequate technique for carrying out the efficiency analysis are selected by considering the specific characteristics of public production. The analysis is undertaken by using data envelopment analysis (DEA) and various homogeneity tests (returns to scale and restrictions on weights) are applied in order to ensure a correct comparison between Courts. Some additional extensions to the analysis (such as the calculus of efficient delays and an approximation to the calculus of global efficiency) are carried out.

Exploring differences in corruption: the role of neighboring countries

The aim of this paper is to study whether corruption spreads across neighboring countries. Spatial econometric techniques are used to analyze corruption interactions, testing whether the perception of corruption in neighboring countries affect a country’s own corruption once other variables are controlled for. For a given country it is found that corruption varies neither with the behavior of its neighbors (there is no endogenous interaction) nor with their exogenous characteristics (there is no contextual interaction). Corruption is therefore not contagious, but neighboring countries tend to show similar levels of corruption because they face similar characteristics and similar institutional environments.

Do Budget Institutions Matter?: Fiscal Consolidation in the New EU Member States

This paper studies the influence that the recently reformed budgetary institutions in the new EU member states may have had on their public finances. We test if their newly formed institutions have already started to shape their fiscal outcomes, as EU-15 institutions did in the past. To answer this question, this paper develops new institutional indices and performs an empirical analysis on the sample of new EU member states—those that joined in 2004 and 2007—for the period 1993-2004. The results confirm that budgetary institutions have a similar influence in the new member states as they had in the EU-15. The role of a strong finance minister is even more important than previous studies suggest.

Assessing Public Sector Efficiency: Issues and Methodologies

Methodological issues relevant when assessing the efficiency of public units are discusses by Pedraja-Chaparro, Salinas-Jimenez and Smith with reference to non-parametric approaches. First they note that public sector activities usually are aimed at achieving various goals other than efficiency, and that often there is a trade-off among various objectives. Output from public sector units is usually not traded on the market and public sector units do not face competition and the threat of bankruptcy. Consequently, the techniques employed to estimate efficiency scores should adjust to take into account problems in the measurement of outputs and inputs and uncertainty as regards the technology. Given its flexibility, data envelopment analysis seems an appealing approach to be used when addressing public sector efficiency.

Exploring factors affecting the level of happiness across countries: A conditional robust nonparametric frontier analysis

In this paper we propose an innovative approach based on life satisfaction to estimate efficiency measures for individuals considering how they convert their resources into higher levels of happiness. We use an extension of the conditional nonparametric robust approach which allows us to consider a mixed set of contextual variables that can affect the levels of life satisfaction. Our empirical analysis includes data about 31,854 individuals from 26 OECD countries participating in the last wave of the World Values Survey. Results obtained indicate that the most efficient individuals in achieving happiness tend to live in northern and central European countries whereas the less efficient individuals are found, in average, in Asian transitional economies. In addition, it is also found that most of the traditional determinants of wellbeing (e.g. age, marital status, religion or unemployment) also have a significant impact on efficiency measures.

Performance measurement of local welfare programmes: evidence from Madrid’s regional government

Interest in how social assistance programmes are organized has recently heightened, fed by concerns about the limits on achieving greater efficiency. Most available evidence considers performance indicators that are too general, there being few studies relating the use of inputs to outcomes. We compare different performance indicators of Madrids programme with resource endowments in a group of local agencies of social services. In addition to constructing a detailed system of input and performance indicators, an empirical analysis of efficiency for each of the social services agencies is carried out using data envelopment analysis. Results confirm that there is a wide margin for obtaining efficiency gains. The empirical analysis shows that some detected inefficiencies arise from an excessive number of staff in relation to the work to be performed. Agencies with a higher incidence of social problems present higher efficiency scores.

Educational mismatch and job aspirations

Purpose - – The purpose of this paper is to analyze the relationship between education, job aspirations and subjective well-being. This analysis is done across the entire well-being distribution and taking account of educational mismatches that could condition individuals’ satisfaction if education generates certain aspirations which are not met by the individuals. Design/methodology/approach - – Using data from the European Social Survey, a quantile regression model is estimated. This approach allows one to assess the impact of the education variables at different points of the happiness conditional distribution. Findings - – The results are consistent with the hypothesis that the impact of education on subjective well-being varies across the distribution, with education effects lower at the top of the happiness distribution. It is also found that education generates certain aspirations among individuals in regard to the job they expect to hold and that people suffer a psychological cost when those aspirations are not met. This “aspiration mechanism” seems however to weaken as one moves along the distribution. Originality/value - – The central contribution of this paper lies in the treatment of job aspirations through different variables of educational mismatch. Although rising aspirations have often been highlighted as the main mechanism that could explain the weak relationship between education and subjective well-being, this mechanism has barely been analyzed empirically. Moreover, the effects of educational mismatch on individual satisfaction have only been analyzed at the mean of the conditional distribution. The value of this study is therefore twofold, focussing on the analysis across the entire well-being distribution of the aspiration mechanism generated by education in regard to the job an individual expects to hold.