Hospital Efficiency: An Empirical Analysis of District and Grant-in-Aid Hospitals in Gujarat

This study focuses on analysing the hospital efficiency of district level government hospitals and grant-in-aid hospitals in Gujarat. The study makes an attempt to provide an overview of the general status of the health care services provided by hospitals in the state of Gujarat in terms of their technical and allocative efficiency. One of the two thrusts behind addressing the issue of efficiency was to take stock of the state of healthcare services (in terms of efficiency) provided by grant-in-aid hospitals and district hospitals in Gujarat. The motivation behind addressing the efficiency issue is to provide empirical analysis of governments policy to provide grants to not-for-profit making institutions which in turn provide hospital care in the state. The study addresses the issue whether grant-in-aid hospitals are relatively more efficient than public hospitals. This comparison between grant-in-aid hospitals and district hospitals in terms of their efficiency has been of interest to many researchers in countries other than India, and no consensus has been reached so far as to which category is more efficient. The relative efficiency of government and not-for-profit sector has been reviewed in this paper. It is expected that the findings of the study would be useful to evaluate this policy and help policy makers to develop benchmarks in providing the grants to such institutions.

Measuring efficiency and productivity in professional football teams: Evidence from the English Premier League

Professional football clubs are unusual businesses, their performance judged on and off the field of play. This study is concerned with measuring the efficiency of clubs in the English Premier League. Information from clubs’ financial statements is used as a measure of corporate performance. To measure changes in efficiency and productivity the Malmquist non-parametric technique has been used. This is derived from the Data Envelopment Analysis (DEA) linear programming approach, with Canonical Correlation Analysis (CCA) being used to ensure the cohesion of the input-output variables. The study concludes that while clubs operate close to efficient levels for the assessed models, there is limited technological advance in their performance in terms of the displacement of the technological frontier

Uma Avaliação do potencial da analise de envoltoria de dados (DEA) no diagnostico da produtividade de unidades de produção agropecuaria

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro TecnologicoO objetivo deste trabalho consiste em um estudo sobre os métodos de mensuração do grau de eficiência e produtividade relativa de insumos e produtos de um conjunto de 131 unidades de produção da agropecuária catarinense. Estes métodos não paramétricos são comumente designados por DEA (Data Envelopment Analysis) e são operacionalizados através de programação matemática. No presente trabalho procurou-se avaliar o significado dos pesos (valorações) atribuídas a insumos e produtos através da utilização de um modelo básico DEA - CCR com rendimentos escala constante. A análise buscou estabelecer um grupo de Estabelecimentos agrícolas padrões de referências (benchmarks) com vistas a avaliar o grau de eficiência produtiva e a estabilidade dos resultados à medida que as restrições sobre os pesos se-tornam mais severas. Os resultados obtidos indicaram uma concordância razoável entre as médias dos pesos computados e os preços de mercado correspondentes. Embora exista uma grande variabilidade entre as unidades de produção, os resultados obtidos com diferentes níveis de limitação apresentaram efeitos modestos sobre os resultados gerais da análise, evidenciando a robustez do modelo DEA - CCR utilizado. Finalizando fizemos uma análise sobre o papel da Extensão Rural frente a UTDs ineficientes e de como utilizar os dados de DEA para tornar estas UTDs eficientes

Essays on building and evaluating two-stage DEA models of efficiency and effectiveness

Researchers are not consistent in their choice of input and output variables when using two-stage data envelopment analysis (DEA) models to measure efficiency and effectiveness. This inconsistency has resulted in the development of many different two-stage DEA models of efficiency and effectiveness for the financial industry. In this dissertation, I improved the statistical method from the MASc dissertation (Attarwala, 2016) by adding more features. These features are documented in Chapter 2 on page 4 and page 5. This statistical method evaluates efficiency and effectiveness models in the banking industry. It relies on the semi-strong version of the efficient market hypothesis (EMH). The EMH is motivated by the wisdom of the crowds, discussed in Section 2.2.2. Previously (Attarwala, 2016), I found that the two-stage DEA model of Kumar and Gulati (2010) is not consistent with the semi-strong EMH for Indian and American banks. In this dissertation, using my improved statistical method, I show that the two-stage DEA model of Kumar and Gulati (2010) is not consistent with the semi-strong EMH for banks in Brazil, Canada, China, India, Japan, Mexico, South Korea and the USA from 2000- 2017. I address the question of whether a universal two-stage DEA model of efficiency and effectiveness exists by building a variable selection framework. This variable selection framework automatically generates two-stage DEA models of efficiency and effectiveness. To do this, it uses the improved statistical method and a genetic search (GS) algorithm. The variable selection framework finds the best, universal, two-stage DEA model of efficiency and effectiveness consistent with the semi-strong definition of EMH for banks in Brazil, Canada, China, India, Japan, Mexico, South Korea and the USA and from 2000-2017. I investigated the causal relationship between (a) the quantitative measures of efficiency and effectiveness from the best two-stage DEA model generated by the variable selection framework and (b) Tobin’s Q ratio, a financial market-based measure of bank performance. Not only do I provide bank managers with a reasonable proxy for measuring efficiency and effectiveness, but I also address the question of whether acting on these input and output variables improves the performance of banks in the financial market. Finally, I set up an optimization problem and find an optimal path from the two-stage DEA model of Kumar and Gulati (2010) to the best two-stage DEA model found by the variable selection framework. This optimal path provides a set of actionable items for converting a two-stage DEA model that is not consistent with the semi-strong EMH to one that is