{"id":1248,"date":"2016-07-14T19:32:53","date_gmt":"2016-07-14T17:32:53","guid":{"rendered":"https:\/\/cio.umh.es\/?p=1248"},"modified":"2016-07-14T19:32:53","modified_gmt":"2016-07-14T17:32:53","slug":"conferencia-de-la-profa-dra-gabriela-sicilia","status":"publish","type":"post","link":"https:\/\/cio.umh.es\/en\/2016\/07\/14\/conferencia-de-la-profa-dra-gabriela-sicilia\/","title":{"rendered":"Conferencia de la Profa. Dra. Gabriela Sicilia"},"content":{"rendered":"<p>[:es]<span style=\"color: #000000\"><strong>T\u00edtulo:<\/strong> El problema de la endogeneidad ligado al An\u00e1lisis Envolvente de Datos (DEA)<\/span><br \/>\n<span style=\"color: #000000\"><strong>Ponente: <\/strong> Gabriela Sicilia<\/span><br \/>\n<span style=\"color: #000000\"><strong>Date:<\/strong> 27\/07\/2016 12:00 h<\/span><br \/>\n<span style=\"color: #000000\"><strong>Lugar:<\/strong> Sala de Seminarios, Edificio Torretamarit<\/span><br \/>\n<span style=\"color: #000000\"><strong>Resumen:<\/strong><\/span><br \/>\n<span style=\"color: #000000\">La presencia de endogeneidad es frecuente en varios procesos de producci\u00f3n econ\u00f3mica, sin embargo, ha recibido poca atenci\u00f3n en la literatura de fronteras y generalmente se pasa por alto cuando se utiliza el An\u00e1lisis Envolvente de Datos (DEA) para estimar la eficiencia t\u00e9cnica. Recientemente, Cordero, Sant\u00edn y Sicilia (2015) concluyen que cuando uno de los inputs del proceso de producci\u00f3n est\u00e1 alta y positivamente correlacionado con la eficiencia, las estimaciones DEA resultan sesgadas. Asimismo, encuentran que el deterioro de las estimaciones DEA es impulsado por la identificaci\u00f3n err\u00f3nea de las DMUs m\u00e1s ineficientes con bajos niveles del input end\u00f3geno. Estos resultados adquieren gran relevancia, ya que los escenarios end\u00f3genos positivos altos son similares a los que se observan en muchos procesos de producci\u00f3n. En este contexto, la estimaci\u00f3n de la eficiencia t\u00e9cnica mediante modelos DEA sin tener en cuenta la presencia de endogeneidad conduce a estimaciones equ\u00edvocas de la eficiencia, donde muchas de las DMU m\u00e1s ineficientes son identificadas como unidades de referencia, lo que conducir\u00e1 a recomendaciones de pol\u00edtica inapropiadas. En esta charla se mostrar\u00e1 la investigaci\u00f3n que aborda dos cuestiones fundamentales: \u00bfc\u00f3mo podemos detectar la presencia de un input end\u00f3geno? Y, \u00bfc\u00f3mo podemos hacer frente a este problema para mejorar las estimaciones DEA? En primer lugar, proporcionamos un procedimiento heur\u00edstico simple que permite identificar la presencia de un input end\u00f3geno. En segundo lugar, se propone la utilizaci\u00f3n de una estrategia que denominamos \u201cInstrumental Input DEA\u201d (II-DEA) como una soluci\u00f3n potencial para tratar el problema de endogeneidad. Los resultados de los experimentos Monte Carlo confirman que el enfoque II-DEA muestra un mejor desempe\u00f1o que el DEA est\u00e1ndar cuando un input presenta una alta correlaci\u00f3n positiva con la eficiencia t\u00e9cnica. Por \u00faltimo, se mostrar\u00e1 una aplicaci\u00f3n emp\u00edrica para ilustrar los resultados te\u00f3ricos.<\/span><br \/>\n<span style=\"color: #000000\"><strong>Breve Bio:<\/strong><\/span><br \/>\n<span style=\"color: #000000\"> Gabriela Sicilia es Doctora en Econom\u00eda por la Universidad Complutense de Madrid (2015). Sus principales l\u00edneas de investigaci\u00f3n son la medici\u00f3n de la eficiencia y la inferencia causal aplicadas al \u00e1mbito de la educaci\u00f3n, combinando tanto elementos metodol\u00f3gicos como aplicados. Su trabajo ha dado lugar a diversas publicaciones en revistas indexadas en JCR tales como European Journal of Operational Research, Scientometrics, Pacific Economic Review, Latin American Economic Review y The Social Science Journal y han sido presentados en m\u00e1s de 20 congresos nacionales e internacionales. Ha participado en diversos proyectos de investigaci\u00f3n competitivos y es colaboradora habitual de la Fundaci\u00f3n Europea Sociedad y Educaci\u00f3n.<\/span>[:en]<strong>Title: <\/strong> Addressing the endogeneity issue in DEA applications<br \/>\n<strong>Speaker:<\/strong> Gabriela Sicilia<br \/>\n<strong>Date:<\/strong> 27\/07\/2016 12:00 h<br \/>\n<strong>Location: <\/strong>Sala de Seminarios, Edificio Torretamarit<br \/>\n<strong>Abstract:<\/strong><br \/>\nThe presence of the endogeneity is frequently observed in several economic production processes, however, it has received little attention in the frontier literature and it is overlooked when practitioners apply data envelopment analysis (DEA). Recently, Cordero, Sant\u00edn and Sicilia (2015) concluded that when one input in the production process is highly and positively correlated with the true efficiency level, endogeneity arises and DEA estimates are flawed. In addition, they find that this decline in DEA performance is further driven by the misidentification of the most inefficient DMUs with low levels of the endogenous input. These findings take on greater significance since high positive endogenous scenarios are similar to those that are likely to be found in many production processes. In this context, the estimation of the technical efficiency using DEA models without taking into account the presence of endogeneity leads to inaccurate efficiency estimates where many of the most inefficient DMUs are identified as benchmarks, which will lead to inappropriate performance-based recommendations. Building upon this evidence, in this research we address two key issues: how can we detect the presence of an endogenous input? And, how can we deal with this problem in DEA empirical applications to overcome this problem and improve estimations? First, we provide a simple heuristic procedure which allows practitioners to identify the presence of an endogenous input in an empirical research. Second, we propose the use of an instrumental input DEA (II-DEA) as a potential solution to deal with the endogeneity problem in order to improve DEA estimations. Monte Carlo results confirm that II-DEA approach outperforms standard DEA when an input has a high a positive correlation with the technical efficiency. Finally, we perform an empirical application to illustrate our theoretical findings.<br \/>\n<strong>Brief Bio:<\/strong><br \/>\nPh.D. in Economics at Complutense University of Madrid (2015). Her main lines of research are the measurement of efficiency and productivity and causal inference applied to the field of education, combining both methodological and applied elements. Her work has led to several publications in scientific international journals such as the European Journal of Operational Research, Scientometrics, Pacific Economic Review, Latin American Economic Review and The Social Science Journal and have been discusssed in more than 20 national and international conferences and workshops. She has also participated in several competitive research projects and is a regular contributor to the European Foundation Society and Education.[:]<\/p>","protected":false},"excerpt":{"rendered":"<p>[:es]T\u00edtulo: El problema de la endogeneidad ligado al An\u00e1lisis Envolvente de Datos (DEA)<br \/>\nPonente:  Gabriela Sicilia<br \/>\nFecha: 27\/07\/2016 12:00 h<br \/>\nLugar: Sala de Seminarios, Edificio Torretamarit<br \/>\nResumen:<br \/>\nLa presencia de endogeneidad es frecuente en varios procesos de producci\u00f3n econ\u00f3mica, sin embargo, ha recibido poca atenci\u00f3n en la literatura de fronteras y generalmente se pasa por alto cuando se utiliza [&#8230;]<\/p>","protected":false},"author":3477,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[4,873],"tags":[],"_links":{"self":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts\/1248"}],"collection":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/users\/3477"}],"replies":[{"embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/comments?post=1248"}],"version-history":[{"count":0,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/posts\/1248\/revisions"}],"wp:attachment":[{"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/media?parent=1248"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/categories?post=1248"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cio.umh.es\/en\/wp-json\/wp\/v2\/tags?post=1248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}