Dealing with endogeneity in data envelopment analysis applications

Although the presence of the endogeneity is frequently observed in economic production processes, it tends to be overlooked when practitioners apply data envelopment analysis (DEA). In this paper we deal with this issue in two ways. First, we provide a simple statistical heuristic procedure that enables practitioners to identify the presence of endogeneity in an empirical application. Second, we propose the use of an instrumental input DEA (II-DEA) as a potential tool to address this problem and thus improve DEA estimations. A Monte Carlo experiment confirms that the proposed II-DEA approach outperforms standard DEA in finite samples under the presence of high positive endogeneity. To illustrate our theoretical findings, we perform an empirical application on the education sector

Market access and seaport efficiency: the case of container handling in Norway

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/Comprehensive studies on the impact of market access on port efficiency are scarce, and the problem that market access indicators are potentially endogenous lacks treatment in maritime economics. This paper offers both theoretical and empirical advances to fill these research gaps. First, it pioneers in the use of Stochastic semi-Nonparametric Envelopment of Z variables Data for measuring port efficiency, and further develops the methodology for panel data and proposes an instrumental variable extension for dealing with endogenous market access indicators. Second, it advances the empirical port literature by developing a unique panel dataset on Norwegian container ports encompassing a comprehensive set of foreland and hinterland connectivity measures. Our comprehensive assessment suggests that the role of market access in determining port efficiency is uncertain.Market access and seaport efficiency: the case of container handling in NorwaypublishedVersio

Data Envelopment Analysis, Endogeneity and the Quality Frontier for Public Services

Applying Data Envelopment Analysis (DEA) to real-world public policy issues can raise many interesting complications beyond those considered in standard models of DEA. One of these complications arises if the funding levels of public service providers, and their ability to attract and retain clients and able staff, depend upon the quality of the output which they produce. This dependency introduces additional inter-relationships between inputs and outputs beyond the uni-directional Production Possibility Frontier (PPF) relationship considered by standard DEA models. The paper therefore analyses the multiplier effects which can be generated by these additional relationships, in which key resource inputs become endogenous variables subject to the external environmental variables which the public service provider faces across these different relationships. The magnitude of these multiplier effects can be captured by focusing DEA on the estimation of an Achievement Possibility Frontier, which reveals the wider set of opportunities which are available to a public service provider to improve its own output quality than that revealed by the estimation of the PPF associated with standard models of DEA. In doing so, the paper enables DEA to be still applied, but in modified form, to the estimation of the scope for improved output of any given public service provider in the presence of such resource endogeneity

Has minority foreign investment in China�s banks improved their cost efficiency?

Since 2001, foreign investors have been permitted to acquire minority ownership stakes in China�s banks. This paper assesses whether there is any evidence of a cost efficiency payoff in those banks that have taken on foreign investment. Data Envelopment Analysis is first used to generate measures of cost efficiency for China�s banks over the period 2001-2006. A second stage regression is then performed to determine whether foreign investment has an impact on cost efficiency. The results indicate a positive impact, although one that is only marginally significant. Policy implications are discussed.

Are Hospital Pharmacies More Efficient if They Employ Nurses?

This paper assesses the efficiency of utilizing nurses in Washington State hospital pharmacies. We take the perspective of a pharmacy department manager and model an input oriented hospital pharmacy production process. Data envelopment analysis (DEA) is used to examine both scale efficiency and technical efficiency, and differences across hospital pharmacies that use and do not use nurse staffing are analyzed using cross-tabulations and nonparametric hypothesis tests. The results indicate that the use of nurse staffing does not significantly impact either scale or technical efficiency. Thus, permitting nurses to play a greater role in hospital pharmacies does not adversely affect efficiency. This paper has important policy implications for hospital administrators and pharmacists.

Data envelopment analysis efficiency of public services: bootstrap simultaneous confidence region

Public services, such as higher education, medical services, libraries or public administration offices, provide services to their customers. To obtain opinion-satisfaction indices of customers, it would be necessary to survey all the customers of the service (census), which is impossible. What is possible is to estimate the indices by surveying a random customer sample. The efficiency obtained with the classic data envelopment analysis models, considering the opinion indices of the customers of the public service as output data estimated with a user sample, will be an estimation of the obtained efficiency if the census is available. This paper proposes a bootstrap methodology to build a confidence region to simultaneously estimate the population data envelopment analysis efficiency score vector of a set of public service-producing units, with a fixed confidence level and using deterministic input data and estimated customer opinion indices as output data. The usefulness of the result is illustrated by describing a case study comparing the efficiency of libraries.Peer Reviewe

Efficiency of Hospitals in the Czech Republic

The paper estimates cost efficiency of 99 general hospitals in the Czech Republic during 2001-2008 using Stochastic Frontier Analysis. We estimate a baseline model and also a model accounting for various inefficiency determinants. Group-specific inefficiency is present even having taken care of a number of characteristics. We found that inefficiency increases with teaching status, more than 20,000 treated patients a year, not-for-profit status and a larger share of the elderly in the municipality. Inefficiency decreases with less than 10,000 patients treated a year, larger population, and more hospitals in the region.Efficiency, hospitals, stochastic frontier analysis

Ensayos sobre la estimación de la eficiencia técnica educativa bajo la presencia de endogeneidad

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, leída el 25-03-2015La presente Tesis Doctoral contribuye, teórica y empíricamente, a entender hasta qué punto el problema de endogeneidad, uno de los principales problemas observado frecuentemente en los procesos de producción educativos, afecta a la estimación de la eficiencia técnica mediante el Análisis Envolvente de Datos (DEA). Asimismo, esta investigación combina ideas de la literatura de evaluación de impacto con las técnicas de medición de eficiencia no paramétricas con el fin de aportar potenciales soluciones para hacer frente a este problema en aplicaciones empíricas educativas y obtener así estimaciones de la eficiencia más precisas.El Capítulo 1 analiza teóricamente en qué medida la presencia de endogeneidad en el proceso de producción puede afectar a las estimaciones DEA en muestras finitas, de modo que los investigadores que aplican esta técnica conozcan la precisión de sus estimaciones. Para ello, en primer lugar se ilustra desde un punto de vista conceptual el problema de la endogeneidad y sus implicaciones en la estimación de la eficiencia. En segundo lugar, utilizando datos generados en un experimento de Monte Carlo evaluamos cómo diferentes niveles de endogeneidad positiva y negativa pueden afectar al desempeño de DEA. A pesar de que DEA es robusto a la presencia de endogeneidad negativa, la existencia de una endogeneidad positiva y significativa perjudica gravemente el desempeño de DEA. A partir de los resultados hallados previamente, la siguiente pregunta que surge es ¿Cómo podemos hacer frente a este problema en una aplicación empírica cuando sospechamos de la presencia de este tipo de endogeneidad? Esto implica responder dos cuestiones, cómo identificar el problema y cómo enfrentarlo. A partir de las simulaciones de Monte Carlo se propone un método heurístico sencillo que permite identificar correctamente la presencia de inputs endógenos en todos los escenarios simulados. Además, a partir de la técnica de Variables Instrumentales (VI) ampliamente utilizada en econometría, ofrecemos una nueva estrategia que permite abordar efectivamente el problema de endogeneidad en la estimación de la eficiencia técnica, el instrumental Input DEA Adicionalmente a este ejercicio teórico, los capítulos 2 y 3 proporcionan evidencia de dos aplicaciones empíricas en el que el problema de endogeneidad está presente.En el capítulo 2 se aplican las estrategias propuestas en el Capítulo 1 a datos de colegios públicos de educación secundaria en Uruguay. Utilizando el método heurístico detectamos que el nivel socio-económico medio de los colegios está alta y positivamente correlacionado con la eficiencia técnica de los mismos, y por lo tanto aplicamos la estrategia II-DEA para estimar la eficiencia técnica de los colegios controlando por endogeneidad. En el capítulo 3, tomando nuevamente ideas de la literatura de evaluación de impacto, se utilizan datos de un experimento natural en las escuelas de educación primaria en España para estimar la eficiencia de los maestros. En base a la asignación aleatoria de los estudiantes a las clases dentro de los colegios explotamos la variación exógena de la eficiencia técnica entre los maestros para evaluar su desempeño. Esta estrategia nos permite obtener una medida objetiva del verdadero efecto del maestro sobre los logros de los estudiantes y explorar los principales factores que explican la eficiencia de los docentes. Más allá de los resultados concretos de cada contexto educativo analizado (que se discuten en cada capítulo), ambos análisis proporcionan evidencia robusta de que el tomar o no en consideración el problema de endogeneidad conduce a resultados radicalmente diferentes en términos de las recomendaciones de política educativa pública para mejorar la calidad de la enseñanza.Fac. de Ciencias Económicas y EmpresarialesTRUEunpu

Social Capital, R&D and Industrial Districts

The main idea behind this paper is that social capital is not, as generally suggested by the socio-economic literature, an individual attitude towards something which does not imply privately appropriable economic benefits. Actually, SC might and should be interpreted as a public component of an investment which implies private and public benefits entangled with each other. In order to put forward this idea, a dynamic theoretical model that assumes social capital as the public component of the impure public good R&D is developed. It shows that the ‘civic culture’ of the district area in which the firm works is not sufficient as an incentive to increase its investment in social capital, because this investment strictly depends on the economic convenience of investing in the impure public good. Social capital /networking dynamics might positively and complementarily evolve only if the opportunity cost of investing in innovation is sufficiently low. We consequently focus our attention on a specialized industrial district located in the Emilia Romagna region – the biomedical district of Mirandola (Modena) – characterised by a strong pattern of innovative activity. Using a proxy for innovative activity as dependant variable, we observe that R&D and networking/social capital arise as complementary driving forces for innovation outputs. When empirical evidence confirms that this complementarity plays a key role, and consequently strong links exist between market and non-market dynamics relating to firms, the role for policy actions targeted to social capital is larger. The policy effort should be targeted toward both market and non-market characteristics taken together, rather than solely to the production of (local) public goods (social capital) or innovation inputs as independent elements of firm processes. The input of SC alone is not sufficient to ensure innovation and growth: economic incentives matter. On the other hand, whenever SC dynamics are crucial for R&D private investments, the effect of economic incentives depends on the presence and degree of their complementarity.Social capital, R&D, Technological innovation, Industrial districts