Loaiza Quintero, Osmar Leandro and Franco Vásquez, Liliana Yaned (2012): Un estudio acerca de los determinantes de la productividad y la ineficiencia técnica en la industria colombiana, 1992-2007.
Preview |
PDF
MPRA_paper_47736.pdf Download (460kB) | Preview |
Abstract
The aim of this article is to estimate the determinants of industrial productivity growth in Colombia’s regions. In this regard, we follow to Kumbhakar and Lovell (2000), who decompose total factor productivity growth into three sources: technical change, scale economies and technical efficiency. To this end, a stochastic frontier model, similar to that of Battese and Coelli (1995), is estimated. This model allow to associate technical efficiency to a set of explanatory variables. This way, the Battese and Coelli’s model allows to get a deeper understanding of the causes of productivity growth. This article finds that throughout the period 1992-1999, productivity growth is mainly explained by an increase in technical efficiency, due to the softening of Colombia’s foreign trade restrictions. However, throughout the period 2000-2007, productivity growth is mainly explained by technical change, which possibly related to the increase in foreign investment and to tax deductions to foster the imports of capital goods.
Este trabajo se propone estimar los determinantes del crecimiento de la productividad industrial en los departamentos de Colombia. En particular, siguiendo a Kumbhakar y Lovell (2000), se descompone la productividad total factorial en tres elementos: cambio técnico, economías de escala y eficiencia técnica. Con este fin, se estima un modelo de frontera estocástica siguiendo la propuesta de Battese y Coelli (1995). Este modelo permite, además, asociar la eficiencia técnica con un conjunto de variables explicativas. De esta forma, el modelo de Battese y Coelli (1995) permite ahondar en los determinantes de la PTF. Se encuentra que en el periodo 1992-1999 el aumento de la productividad puede ser atribuido principalmente al aumento en la eficiencia técnica, debido a la mayor exposición de la industria nacional a la competencia extranjera por la disminución de las barreras arancelarias. Por el contrario, en el periodo 2000-2007, el crecimiento de la productividad puede ser atribuido principalmente al cambio técnico, posiblemente asociado al incremento de la inversión extranjera y los incentivos tributarios a la importación de bienes de capital.
Item Type: | MPRA Paper |
---|---|
Original Title: | Un estudio acerca de los determinantes de la productividad y la ineficiencia técnica en la industria colombiana, 1992-2007 |
English Title: | Determinants of productivity and technical inefficiency in Colombia’s manufacturing, 1992-2007 |
Language: | Spanish |
Keywords: | Stochastic frontier, total factor productivity, technical efficiency, manufacturing industry. Frontera estocástica, productividad total factorial, eficiencia técnica, industria manufacturera. |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity L - Industrial Organization > L6 - Industry Studies: Manufacturing > L60 - General |
Item ID: | 47736 |
Depositing User: | Osmar Leandro Loaiza Quintero |
Date Deposited: | 16 Jul 2013 10:49 |
Last Modified: | 28 Sep 2019 11:27 |
References: | Abramovitz, Moses (1993). “The Search for the Sources of Growth: Areas of Ignorance, Old and New.” Journal of Economic History, Vol. 53, No. 2, pp. 217-243. Abramovitz, Moses (1956). “Resource and Output Trends in the United States Since 1870.” American Economic Review, Vol. 46, pp. 5-23. Acevedo, María y Ramírez, Jorge (2005). “Diferencias regionales en la eficiencia técnica del sector confecciones en Colombia: Una análisis de fronteras estocásticas.” Innovar, Vol. 15, No. 26, pp. 90-105. Affuso, Ermanno (2010). “Spatial Autoregressive Stachastic Frontier Analysis: an applicatoin to an impact evaluation study.” Working Paper, Auburn University. Aigner, J. y Chu, S. (1968). “On Estimating the Industry Production Function.” American Economic Review, Vol. 58, No. 4, pp. 826-839. Aigner, J.; Lovell, K. y Schmidt, P. (1977). “Formulation and Estimation of Stochastic Frontier Production Function Models.” Journal of Econometrics, Vol. 6. No. 1, pp. 21-37 Barrios, Erniel y Lavado, Rouselle (2010). “Spatial Stochastic Frontier Models.” Discussion Paper Series, Philippine Institute for Development Studies. Badel, Alejandro (2002). “Sistema Bancario Colombiano: ¿Somos eficientes a nivel internacional?” Archivos de Economía, Departamento Nacional de Planeación. Battese, George y Coelli, Tim (1992). “Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India.” The Journal of Productivity Analisys, Vol. 3, pp. 153-169. Charnes, A.; Cooper, W. y Rhodes E. (1978). “Measuring the Efficiency of Decision-Making Units.” European Journal of Operational Research, Vol. 2, No. 6, pp. 429-444. Coelli, Tim y Henningsen, Arne (2011). frontier: Stochastic Frontier Analysis. R package version 0.997-2. http://CRAN.R-project.org/package=frontier Coelli, Timothy; Prasada, D.S.; O’Donnell, Crhistopher y Battese, George (2005). An introduction to efficiency and productivity analysis. Springer. Consejo Privado de Competitividad (2012). Informe nacional de competitividad, 212-2013: Ruta a la prosperidad colectiva. Zetta Comunicadores, Bogotá. Cornwell, Christopher; Schmidt, Peter y Sickles, Robin (1990). “Production frontiers with cross-sectional and time-series variation in efficiency levels.” Journal of Econometrics, Vol. 46, pp. 185-200. Cornwell, Cristopher y Schmidt, Peter (1993). "Production Frontiers and Efficiency Measurement," Working Paper, No. 427e, Georgia, College of Business Administration, Department of Economics. Cuervo, Luis y Josefina, González (1997). Industria y ciudades en la era de la mundialización: un enfoque socio espacial. CIDER y Tercer Mundo Editores, Bogotá. Elhorst, Paul (2010). “Spatial Panel Data Models.” En: Fisher, Manfred y Getis, Arthur (Eds.). Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications. Springer. Debreu, Gerard (1951). “The coefficient of resource utilization.” Econometrica, Vol. 19, No. 3, pp. 273-292. Diewert, Erwin (1993). “Fisher Ideal Output, Input and Productivity Indexes Revisited.” En: Diewert y Nakamura (editors), Essays in Index Number Theory, Volume I. Elsevier Science Publishers. Färe, Rolf y Grosskpf, Shawna (1992). “Malmquist Productivity Indexes and Fisher Ideal Indexes.” The Economic Journal, Vol. 102, No. 410, pp. 158-160. Farrel, M. J. (1957). “The measurement of productive efficiency.” Journal of the Royal Statistical Society, Serie A, Vol. 120, No. 3, pp. 253-282. Fisher, Manfred y Getis, Arthur (2010). Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications. Springer. Fried, Harold; Lovell, Knox y Schmidt, Shelton (2008). “Efficiency and Productivity.” En: Fried, Harold; Lovell, Knox y Schmidt, Shelton (Eds.), The Measurement of Productive Efficiency and Productivity Growth. Oxford University Press. Franco, Liliana y Raymond, José Luis (2009). “Convergencia Económica Regional: el caso de los departamentos colombianos”. Ecos de Economía, No.28. Universidad EAFIT Gallón, Santiago (2007). “Crecimiento de la productividad total factorial de la industria regional colombiana: aplicación de modelos de frontera estocástica.” En Lotero J. (Ed.), Industria y Región en Colombia: Desarrollo espacial, productividad y competitividad comercial durante la apertura de los noventa. Centro de Investigaciones Económicas, Universidad de Antioquia, Medellín. Greene, William (2008). “The Econometric Approach to Efficiency Analysis.” En: Fried, Harold; Lovell, Knox y Schmidt, Shelton (Eds.), The Measurement of Productive Efficiency and Productivity Growth. Oxford University Press. Greene, William (2004). “Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization’s Panel Data on National Health Care Systems.” Health Economics, Vol. 13, pp. 959-980. Grupo de Estudios del Crecimiento Económico-Greco (2002). El crecimiento económico de colombiano en el siglo XX. Banco de la República. Harberger, Arnold (1978). “Perspectives on capital and technology in less developed countres.” En M.J Artis y A.R Nobay (eds.), Contemporary Economic Analysis, Londres, Croom Helm. Harberger, Arnold (1969). “La tasa de rendimiento del capital en Colombia.” Revista Planeación y Desarrollo, Vol. 1, No. 3, pp. 13-42. Huang, Cliff y Liu, Jin-Tan (1994). “Estimation of a non-neutral stochastic frontier production function.” Journal of Productivity Analysis, Vol. 5, pp. 171-180. Iregui, María; Melo, Fernando y Ramírez, Teresa (2006). “Productividad Regional y Sectorial en Colombia: Análisis utilizando datos de panel.” Borradores de Economía, No. 378, Banco de la República. Iregui, María; Melo, Ligia y Ramos, Jorge (2007). “Análisis de la eficiencia de la educación en Colombia.” Revista de Economía del Rosario, Vol. 10, No. 1, pp. 21-41. Jondrow, James; Lovell, Knox; Materov, Ivan y Schmidt, Peter (1982) “On the estimation of technical inefficiency in the stochastic frontier production function model.” Journal of Econometrics, Vol. 19, No. 2-3, pp. 233-238. Kapoor, Mudit; Keleijan, Harry y Prucha, Ingmar (2007). “Panel data models with spatially correlated components.” Journal of Econometrics, No. 140, pp. 97-130. Kumbhakar, Subal y Lovell, Knox (2000). Stochastic Frontier Analysis. Cambridge University Press. Kumbhakar, Subal; Denny, M. y Fuss, M. (2000). “Estimation and decomposition of productivity change when production is not efficient: a panel data approach.” Econometric Reviews, Vol. 19, No. 9, pp. 425-460. Kumbhakar, Subal (1990). “Production frontiers, panel data and time varying technical inefficiency.” Journal of Econometrics, Vol. 46, pp. 201-211. Lambarra F, Serra T. y Gil J.M. (2007). “Technical efficiency analysis and decomposition of productivity growth of Spanish olive farms.” Journal of Agricultural Research, Vol.5, No. 3, pp. 259-270. Meeusen, W. y Van den Broeck (1977). “Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error.” Internation Economic Review, Vol. 18, No. 2, pp. 293-323. Medina, Pablo; Meléndez, Marcela y Seim, Katja (2003). “Productivity Dynamics of the Colombian Manufacturing Sector.” Working Paper, Universidad de los Andes. Mutis, Hernando (2006). “Una aplicación del análisis de frontera estocástica: el caso de hospitales de nivel II en Colombia.” Lecturas Matemáticas, Vol. 27, pp. 259-270. Nehru, Virkam y Ashok, Dhareshwar (1993). “A new database on physical capital stock: sources, methodology and results.” Revista de Análisis Económico, Vol. 8, No. 1, pp 37-59. OECD (2001). Measuring Productivity: Measrement of Aggregate and Industry-level Productivity Growth. Pavlyuk, Dmitry (2010). “Multi-tier spatial stochastic frontier model for competition and cooperation of european airports.” Transport and Telecommunication, Vol. 11, No. 3, pp. 57-66. Perdomo, Andrés y Hueth, Darrel (2010). “Funciones de producción y eficiencia técnica en el eje cafetero colombiano: una aproximación con frontera estocástica.” Documentos CEDE, Universidad de los Andes. Pires, Jorge O. y Garcia, Fernando (2004). “Productivity of Nations: a Stochastic Frontier Approach to Tfp Decomposition.” Textos para discussao, No. 143, Escola de Economia de São Paulo, Getulio Vargas Foundation (Brasil). Puig-Junoy, Jaume (2001). “Technical inefficiency and public capital in U.S. states: a stochastic frontier approach.” Journal of Regional Science, Vol. 41, No. 1, pp. 75-96. R Core Team (2012). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/. Solow, Robert (1957). “Technical Change and the Aggregate Production Function.” The Review of Economics and Statistics, Vol. 39, No. 3, pp. 312-320. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/47736 |