José María Gavilán

Public resource usage in health systems: a data envelopment analysis of the efficiency of health systems of autonomous communities in Spain

OBJECTIVES The efficiency in the management of public resources is one of the main pillars of the welfare state. The objective of this work is to analyze the efficiency of the public resources that regional governments in Spain (Autonomous Communities (AC)) invest in health systems (HS). STUDY DESIGN A dataset from of the Ministry of Health, Social Services and Equality of Spain has been used, which contains the most important indicators from the National HS. The following variables have been chosen in this study: the health care expenses per resident, the percentage of this investment that is forwarded to labour expenses, frequency of hospital care services, frequency of specialized external health care services and, primary health care services in medicine and nursing per resident. METHODS To this end, Data Envelopment Analysis (DEA) is applied, which enables researchers and managers to obtain measurements of efficiency of the analyzed regions, and to propose corrective steps to achieve efficiency for inefficient HS. Moreover, the super-efficiency measurement is shown for a constant and a variable scale. RESULTS The results show that there are three groups of AC, first a group composed by six HS that are globally efficient, a second group composed by eight HS that are globally inefficient, and a third group composed by three HS that are efficient in some terms and their efficiency can be improved. CONCLUSIONS It is concluded that DEA is an appropriate method for evaluating efficiencies of health systems and giving the adjustments for the application of economic, social and organizational policies to improve their efficiencies.

The measurement of production efficiency in scientific journals through stochastic frontier analysis models: Application to quantitative economics journals

The importance of a scientific journal is usually established by considering the number of citations received by the papers that the journal publishes. In this way, the number of citations received by a scientific journal can be considered as a measure of the total production of the journal. In this paper, in order to obtain measures of the efficiency in the production process, the approach provided by stochastic frontier analysis (SFA) is considered, and econometric models are proposed. These models estimate a frontier production, which is the maximum achievable number of citations to the journal based on its resources. The efficiency can then be measured by considering the difference between the actual production and the estimated frontier. This approach is applied to the measurement of the productive efficiency of the journals of the JCR social sciences edition database, which belong simultaneously to the areas of “economics” and “social sciences, mathematical methods”.

A Comparison Between Maximum Likelihood and Bayesian Estimation of Stochastic Frontier Production Models

In this paper, the finite sample properties of the maximum likelihood and Bayesian estimators of the half-normal stochastic frontier production function are analyzed and compared through a Monte Carlo study. The results show that the Bayesian estimator should be used in preference to the maximum likelihood owing to the fact that the mean square error performance is substantially better in the Bayesian framework.