Relative efficiency in government environmental entities: en evaluation of the regional autonomous corporations (CAR) of colombia
Published
Apr 17, 2013
Almetrics
Dimensions
Google Scholar
##plugins.themes.bootstrap3.article.details##
Abstract
This paper evaluates the relative efficiency of the Colombian Regional Autonomous Corporations (CAR) using the directional distance function within the structure of data envelopment analysis, which allows for the incorporation of desirable and undesirable outputs. The input and output information was gathered from the institutional sites of each CAR and from the reports of the National System for the Prevention and Attention of Disasters in Colombia. It was determined that only 18.75% of the 32 evaluated CARs are completely efficient and that the inefficiency averageis close to 60%. We hope that the obtained results will be of use inguiding the increase in efficiency in the utilization of resources and for the identification of those CARs that could set an example for the rest.
Keywords
Data envelopment analysis, relative efficiency, regional autonomous corporations, undesirable outputs, directional distance functionAnálisis envolvente de datos, eficiencia relativa, corporaciones autónomas regionales, salidas indeseadas, función de distancia direccional
References
ARNELL, N. Climate change and global water resources: SRES emissions and socio-economic scenarios. Global Environmental Change. 2004, vol. 14, pp. 31-52.
BIERMANN, F. ‘Earth system governance’ as a cross cutting theme of global change research. Global Environmental Change. 2007, vol. 17, pp. 326-337.
BLACKMAN, A.; MORGENSTERN, R. y TOPPING, E. Institutional analysis of Colombia’s Autonomous Regional Corporations (CARs). June, 2006. Washington, DC. Resources for the future.
CAYÓN, E. y SARMIENTO-SABOGAL, J. Measuring relative efficiencies in the shoe industry sector in Colombia: A DEA approach [documento en línea]. 2009..
CHARNES, A.; COOPER, W. y RHODES, E. Measuring the efficiency of decision making units. European Journal of Operation Research. 1978, vol. 2, pp. 429-444.
CHUNG, Y. H.; FÄRE, R. y GROSSKOPF, S. Productivity and undesirable outputs: a directional distance function approach. Journal of Environmental Management. 1997, vol. 51, núm. 3, pp. 229-240.
COOPER, W.; SEIFORD, L. M. y TONE, K. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. s. l.: Kluwer Academic Publishers, 2000.
COOPER, W.; SEIFORD, L. M.; THANASSOULIS, E. y ZANAKIS S. H. (editors). DEA and its uses in different countries. European Journal of Operation Research. 2004, vol. 154, núm. 2, pp. 337-344.
CORPORACIONES AUTÓNOMAS REGIONALES [web en línea]. Páginas web de cada entidad, consultadas en el periodo 01-08-2011/08-08-2011.
COTTE, A. Economic development and growth in Colombia: an empirical analysis with superefficiency DEA and panel data models. Socio-Economic Planning Sciences. 2011, vol. 45, pp. 154-164.
CUNHA, R. y GARZÓN, F. Performance-based potable water and sewer service regulation: The regulatory model. Cuadernos de Administración. 2007, vol. 20, núm. 34, pp. 283-298.
FÄRE, R.; GROSSKOPF, S.; LOVELL, C. A. K. y PASURKA, C. Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. The Review of Economics and Statistics. 1989, vol. 71, núm. 1, pp. 90-98.
FEROZ, E.; RAAB, R.; ULLEBERG, G. y ALSHARIF, K. Global warming and environmental production efficiency ranking of the Kyoto Protocol nations. Journal of Environmental Management. 2009, vol. 90, pp. 1178-1183.
FOOD SECURITY AND GLOBAL ENVIRONMENTAL CHANGE: Emerging challenges [editorial]. Environmental Science & Policy. 2009, vol. 12, pp. 373-377.
HITZ, S. y SMITH, J. Estimating global impacts from climate change. Global Environmental Change. 2004, vol. 14, pp. 201-218.
INSTITUTO DE INVESTIGACIÓN DE RECURSOS BIOLÓGICOS ALEXANDER VON HUMBOLDT. Corporaciones autónomas regionales [web en línea] [consulta: 11-08-2011].
JAHANSHAHLOO, G.; VENCHEH, A.; FOROUGHI, A. y MATIN, R. Inputs/outputs estimation in DEA when some factors are undesirable. Applied Mathematics and Computation. 2004, vol. 156, pp. 19-32.
LEÓN, C. y PALACIOS, F. Evaluation of rejected cases in an acceptance system with data envelopment analysis and goal programming. Journal of the Operational Research Society. 2009, vol. 60, pp. 1411-1420.
LOZANO, S. y GUTIÉRREZ, E. Slack based-measure of efficiency of airports with airplanes delays as undesirable outputs. Computers and Operations Research. 2011, vol. 38, núm. 1, pp. 131-139.
PARDO, C. Energy efficiency development in German and Colombian non-energy-intensive sectors: a non-parametric analysis. Energy Efficiency. 2011, vol. 4, núm. 1, pp. 115-131.
PATHOMSIRI, S.; HAGHANI, A.; DRESNER, M. y WINDLE, R. Impact of undesirable outputs on the productivity of US airports. Transportation Research Part E 44. 2008, pp. 235-259.
PÉREZ, Y.; ARAQUE, D. y LANCHEROS, J. La eficiencia relativa en los colegios distritales de Bogotá: una aplicación del análisis envolvente de datos. Cuadernos de Administración. 2003, vol.16, núm. 26, pp. 35-60.
PITTMAN, R. Multilateral productivity comparisons with undesirable outputs. The Economic Journal. 1983, vol. 93, pp. 883-891.
POLSKY, C.; NEFF, R. y YARNAL, B. Building comparable global change vulnerability assessments: The vulnerability scoping diagram. Global Environmental Change. 2007, vol. 17, pp. 472-485.
POMBO, C. y TABORDA, R. Performance and efficiency in Colombia’s power distribution system: Effects of the 1994 reform. Energy Economics. 2006, vol. 28, pp. 339-369.
SÁNCHEZ-TRIANA, E. y ORTOLANO, L. Organizational learning and environmental impact assessment at Colombia’s Cauca Valley Corporation. Environmental Impact Assessment Review. 2001, vol. 21, pp. 223-239.
SEIFORD, L M. y ZHU, J. Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research. 2002, vol. 142, pp. 16-20.
SISTEMA NACIONAL PARA LA PREVENCION Y ATENCION DE DESASTRES. Temporada invernal 2010-2011 [web en línea]. [Consulta: 27-04-2011].
TONN, B. An equity first, risk-based framework for managing global climate change. Global Environmental Change. 2003, vol. 13, pp. 295-306.
TORO, J.; DUARTE, O.; REQUENA, I. y ZAMORANO, M. Determining vulnerability importance in environmental impact assessment: The case of Colombia. Environmental Impact Assessment Review. 2012, vol. 32, pp. 107-117.
TYTECA, D. On the measurement of the environmental performance of firms – A literature review and a productive efficiency perspective. Journal of Environmental Management. 1996, vol. 46, pp. 281-308.
VASCO, C. Economic evaluation of current conditions of competition and efficiency of automotive and rail systems in Colombia. Energy Policy. 2012. DOI: 10.1016/j.enpol.2012.03.029.
WANG, K.; YU, S. y ZHANG, W. China’s regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation. Mathematical and Computer Modelling. 2012. Article in Press.
WEBER, M. y WEBER, W. Productivity and efficiency in the trucking industry accounting for traffic fatalities. International Journal of Physical Distribution & Logistics Management. 2004, vol. 34, núm. 1, pp. 39-61.
ZHOU, P.; ANG, B. y POH, K. A survey of data envelopment analysis in energy and environmental studies. European Journal of Operation Research. 2008, vol. 189, pp. 1-18.
ZHOU, P.; ANG, B. y POH, K. Measuring environmental performance under different environmental DEA technologies. Energy Economics. 2008, vol. 30, pp. 1-14.
BIERMANN, F. ‘Earth system governance’ as a cross cutting theme of global change research. Global Environmental Change. 2007, vol. 17, pp. 326-337.
BLACKMAN, A.; MORGENSTERN, R. y TOPPING, E. Institutional analysis of Colombia’s Autonomous Regional Corporations (CARs). June, 2006. Washington, DC. Resources for the future.
CAYÓN, E. y SARMIENTO-SABOGAL, J. Measuring relative efficiencies in the shoe industry sector in Colombia: A DEA approach [documento en línea]. 2009.
CHARNES, A.; COOPER, W. y RHODES, E. Measuring the efficiency of decision making units. European Journal of Operation Research. 1978, vol. 2, pp. 429-444.
CHUNG, Y. H.; FÄRE, R. y GROSSKOPF, S. Productivity and undesirable outputs: a directional distance function approach. Journal of Environmental Management. 1997, vol. 51, núm. 3, pp. 229-240.
COOPER, W.; SEIFORD, L. M. y TONE, K. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. s. l.: Kluwer Academic Publishers, 2000.
COOPER, W.; SEIFORD, L. M.; THANASSOULIS, E. y ZANAKIS S. H. (editors). DEA and its uses in different countries. European Journal of Operation Research. 2004, vol. 154, núm. 2, pp. 337-344.
CORPORACIONES AUTÓNOMAS REGIONALES [web en línea]. Páginas web de cada entidad, consultadas en el periodo 01-08-2011/08-08-2011.
COTTE, A. Economic development and growth in Colombia: an empirical analysis with superefficiency DEA and panel data models. Socio-Economic Planning Sciences. 2011, vol. 45, pp. 154-164.
CUNHA, R. y GARZÓN, F. Performance-based potable water and sewer service regulation: The regulatory model. Cuadernos de Administración. 2007, vol. 20, núm. 34, pp. 283-298.
FÄRE, R.; GROSSKOPF, S.; LOVELL, C. A. K. y PASURKA, C. Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. The Review of Economics and Statistics. 1989, vol. 71, núm. 1, pp. 90-98.
FEROZ, E.; RAAB, R.; ULLEBERG, G. y ALSHARIF, K. Global warming and environmental production efficiency ranking of the Kyoto Protocol nations. Journal of Environmental Management. 2009, vol. 90, pp. 1178-1183.
FOOD SECURITY AND GLOBAL ENVIRONMENTAL CHANGE: Emerging challenges [editorial]. Environmental Science & Policy. 2009, vol. 12, pp. 373-377.
HITZ, S. y SMITH, J. Estimating global impacts from climate change. Global Environmental Change. 2004, vol. 14, pp. 201-218.
INSTITUTO DE INVESTIGACIÓN DE RECURSOS BIOLÓGICOS ALEXANDER VON HUMBOLDT. Corporaciones autónomas regionales [web en línea]
JAHANSHAHLOO, G.; VENCHEH, A.; FOROUGHI, A. y MATIN, R. Inputs/outputs estimation in DEA when some factors are undesirable. Applied Mathematics and Computation. 2004, vol. 156, pp. 19-32.
LEÓN, C. y PALACIOS, F. Evaluation of rejected cases in an acceptance system with data envelopment analysis and goal programming. Journal of the Operational Research Society. 2009, vol. 60, pp. 1411-1420.
LOZANO, S. y GUTIÉRREZ, E. Slack based-measure of efficiency of airports with airplanes delays as undesirable outputs. Computers and Operations Research. 2011, vol. 38, núm. 1, pp. 131-139.
PARDO, C. Energy efficiency development in German and Colombian non-energy-intensive sectors: a non-parametric analysis. Energy Efficiency. 2011, vol. 4, núm. 1, pp. 115-131.
PATHOMSIRI, S.; HAGHANI, A.; DRESNER, M. y WINDLE, R. Impact of undesirable outputs on the productivity of US airports. Transportation Research Part E 44. 2008, pp. 235-259.
PÉREZ, Y.; ARAQUE, D. y LANCHEROS, J. La eficiencia relativa en los colegios distritales de Bogotá: una aplicación del análisis envolvente de datos. Cuadernos de Administración. 2003, vol.16, núm. 26, pp. 35-60.
PITTMAN, R. Multilateral productivity comparisons with undesirable outputs. The Economic Journal. 1983, vol. 93, pp. 883-891.
POLSKY, C.; NEFF, R. y YARNAL, B. Building comparable global change vulnerability assessments: The vulnerability scoping diagram. Global Environmental Change. 2007, vol. 17, pp. 472-485.
POMBO, C. y TABORDA, R. Performance and efficiency in Colombia’s power distribution system: Effects of the 1994 reform. Energy Economics. 2006, vol. 28, pp. 339-369.
SÁNCHEZ-TRIANA, E. y ORTOLANO, L. Organizational learning and environmental impact assessment at Colombia’s Cauca Valley Corporation. Environmental Impact Assessment Review. 2001, vol. 21, pp. 223-239.
SEIFORD, L M. y ZHU, J. Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research. 2002, vol. 142, pp. 16-20.
SISTEMA NACIONAL PARA LA PREVENCION Y ATENCION DE DESASTRES. Temporada invernal 2010-2011 [web en línea].
TONN, B. An equity first, risk-based framework for managing global climate change. Global Environmental Change. 2003, vol. 13, pp. 295-306.
TORO, J.; DUARTE, O.; REQUENA, I. y ZAMORANO, M. Determining vulnerability importance in environmental impact assessment: The case of Colombia. Environmental Impact Assessment Review. 2012, vol. 32, pp. 107-117.
TYTECA, D. On the measurement of the environmental performance of firms – A literature review and a productive efficiency perspective. Journal of Environmental Management. 1996, vol. 46, pp. 281-308.
VASCO, C. Economic evaluation of current conditions of competition and efficiency of automotive and rail systems in Colombia. Energy Policy. 2012. DOI: 10.1016/j.enpol.2012.03.029.
WANG, K.; YU, S. y ZHANG, W. China’s regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation. Mathematical and Computer Modelling. 2012. Article in Press.
WEBER, M. y WEBER, W. Productivity and efficiency in the trucking industry accounting for traffic fatalities. International Journal of Physical Distribution & Logistics Management. 2004, vol. 34, núm. 1, pp. 39-61.
ZHOU, P.; ANG, B. y POH, K. A survey of data envelopment analysis in energy and environmental studies. European Journal of Operation Research. 2008, vol. 189, pp. 1-18.
ZHOU, P.; ANG, B. y POH, K. Measuring environmental performance under different environmental DEA technologies. Energy Economics. 2008, vol. 30, pp. 1-14.
How to Cite
Britto-Agudelo, R. A., Buitrago-Suescùn, O. Y., Puerto-Suarez, J. D., & Ramìrez, J. C. (2013). Relative efficiency in government environmental entities: en evaluation of the regional autonomous corporations (CAR) of colombia. Ingenieria Y Universidad, 17(1), 205–224. https://doi.org/10.11144/Javeriana.iyu17-1.rege
Section
Articles