Industrial Sector Export: Data Envelope Analysis
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Industrial Sector Export: Data Envelope Analysis
- 1. Industrial Sector Exports in Colombia: Efficient Frontier Analysis Jorge A. Restrepo M Institución Universitaria Autónoma de las Américas Lorenzo Portocarrero Sierra. Institución Universitaria Tecnológico de Antioquia Juan Gabriel Vanegas L. Institución Universitaria Tecnológico de Antioquia
- 2. Schedule • Abstract • Theoritical Background • Methodology • Results • Conclusions
- 3. Abstract • In this paper, a comparative analysis is carried out among the industrial sectors in Colombia that have the most employees during 20002011. A dynamic simulation is used, and a Data Envelopment Analysis (DEA) is applied in order to obtain an overall index of technical efficiency in Colombia's industrial sectors for the use of resources. Similarly, an industrial sector efficiency ranking for exports is drawn up. This index determines the presence of unused resources, which is useful to devise strategies to support exports.
- 4. Abstract • The analysis is based on a Monte Carlo simulation forecast to determine the average values of the period for the input variables: number of businesses, employees, assets, and energy used to produce the output variables. That is, gross production and exports. The purpose is to compare the effectiveness of the factors of production to generate exports, and determine the possibility of improving inefficient sectors. The goal is to participate in the internationalization process in a proper way.
- 5. General Context Flexible Ausencia de errores de especificación Información particularizada para cada UTD Parametrics Frontier Analysis Estocastic Frontiers Bayesian Estimation No Parametrics Eficcient Technique Assesment DEA Productivity Assesment Partial Global Malmquist Multifactorial Parametrics Index Number Teory Other Analysis No Parametrics No Parametrics Techniques: Not require a specific function Parametrics Techniques: They do not require a function that relates the inputs and outputs Media Function Amswer Divisia + TornqVist
- 6. General Context He established the conceptual basis for the measurement of efficiency The differentiate technical efficiency and prices. Production function, estimation problems Farrel (1957) He felt the production function from the observation of actual units of production Origin empirical production function and the concept of relative efficiency
- 7. General Context Technical efficiency Quantifies the capacity of a production unit to generate the maximum possible amount of goods using the minimum amount of resources Oriented Input: it measures the ability of a unit to generate the largest amount of goods using a fixed amount of resources Oriented output: measures the ability of a unit to produce fixed assets (or services) using the fewest possible resources Nonparametric method: it does not presuppose the existence of an f (Inputs, Outputs). No statistical: assumes not captured efficiency to follow some kind of probability distribution
- 8. General Context Efficiency price: It measures a company's ability to produce goods/services with a maximum total value through the use of resources at the minimum possible cost. Input orientation: The ability of a company to produce goods with the highest possible value using a quantity fixed resources. It means to achieve the minimum Output orientation: The ability cost of producing a given level of of a company to produce a product when the proportions of quantity fixed assets using the factors of production used are resources with the lowest modified. possible value.
- 9. General Context Fuente; Mercado et al (1998) Objetivo: medir la eficiencia productiva de ocho Unidades: A, B, C, D, E, F, G y H
- 10. Methodology The analysis is based on a Monte Carlo simulation forecast to determine the average values of the period for the input variables NE PO AT EC Inputs NB: número de establecimientos, EM: personal ocupado, AS: activos y EU: energía consumida Outputs GP: producción bruta y EX: exportaciones. PB EX The purpose is to compare the effectiveness of the factors of production to generate exports, and determine the possibility of improving inefficient sectors. The goal is to participate in the internationalization process in a proper way.
- 11. Methodology
- 12. Sector Sector's Description CIIU15 Production of Foodstuffs and Beverages CIIU24 Manufacturing of Chemical Substances and Products CIIU17 Manufacturing of Textile Products CIIU25 Manufacturing of Rubber and Plastic Products CIIU26 Manufacturing of Other Non-Metallic Mineral Products CIIU36 CIIU28 Manufacturing of Furniture; Manufacturing Companies Manufacturing of Products Made of Metal, except Machinery and Equipment CIIU29 Manufacturing of Machinery and Equipment CIIU22 Editing, Printing and Record Playing Activities CIIU21 Manufacturing of Paper and Paper Products
- 13. Results Inputs Sector NB EM Outputs AS EU EX GP Sectors analyzed with more than 20,000 employees CIIU15 1.771 152.675 27.407 3.102 4.768 53.715 CIIU24 827 75.554 13.496 1.769 3.053 23.390 CIIU18 1.021 60.705 1.672 130 540 5.197 CIIU25 775 53.208 6.557 1.198 751 8.099 CIIU17 419 45.972 4.635 897 564 4.873 CIIU26 499 38.502 12.022 1.716 470 9.687 CIIU28 740 37.162 2.066 241 278 4.339 CIIU36 698 33.976 1.610 195 375 3.231 CIIU22 683 33.115 2.859 181 186 4.322 CIIU29 585 31.246 1.928 148 409 3.652 CIIU19 410 21.146 602 94 260 1.574
- 15. Results Sector NE PO AT EC EX PB CIIU15 1.771,00 152.675,00 27.407,37 3.102,46 4.767,82 53.715,18 CIIU24 827,00 75.554,00 13.495,92 1.768,66 3.053,18 23.389,80 CIIU18 1.021,00 60.705,00 1.671,57 130,45 539,55 5.197,12 CIIU25 434,74 32.191,90 3.967,32 441,74 751,22 8.099,34 CIIU17 235,78 18.688,91 2.608,45 321,52 564,27 4.872,76 CIIU26 319,40 27.534,75 4.942,89 559,53 859,87 9.687,47 CIIU28 510,57 32.201,47 1.790,06 177,21 419,00 4.339,23 CIIU36 462,00 28.790,53 1.364,62 142,34 375,20 3.312,50 CIIU22 510,25 32.166,16 1.781,22 176,20 417,53 4.322,43 CIIU29 585,00 31.246,00 1.927,67 148,17 409,16 3.652,15 Porcentajes de Mejora por sector CIIU15 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% CIIU24 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% CIIU18 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% CIIU25 43,91% 39,50% 39,50% 63,12% 0,00% 0,00% CIIU17 43,73% 59,35% 43,73% 64,17% 0,00% 0,00% CIIU26 35,99% 28,48% 58,89% 67,39% 83,13% 0,00% CIIU28 31,00% 13,35% 13,35% 26,41% 50,77% 0,00% CIIU36 33,81% 15,26% 15,26% 27,16% 0,00% 2,52% CIIU22 25,29% 2,87% 37,70% 2,87% 124,03% 0,00% CIIU29 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
- 16. Resultas The case of the SECTORS: CIIU25; CIIU17; CIIU26; CIIU28; CIIU36 and CIIU22; they have been inefficient in 2011. CIIU1 7 NB:419 EM:45.972 AS:4.653MM EU:897MM NB:236 EM:18.688: AS:2.208MM EU:321MM GP:4.873MM EX:564MM NB:43.73%->183 EM:59.35%->27.283 AS:43%.>2.027MM EU62.52%->576MM
- 17. Conclusions • It conducted a comparative analysis between the industrial sectors of Colombia most employers in the period 20002011; through the dynamic simulation and the DEA (data envelope analysis) technique, was a global index of technical efficiency of industrial sectors in Colombia, showing that more than 60% of the analyzed sectors are inefficient in the use of NE; PO; EN and EC to generate PB and EX; which leads to problems of international competitiveness. This rate determines the presence of idle resources on scanned Inputs, useful information in the design of strategies to support the industrial sector to face the signing of FTA and improve the possibilities of exporting.
- 18. CONCLUSIONS • The colombian manufacturing system, as a whole it is inefficient, intends the measurement of efficiency with the countries which signed FTA to establish policies and government plans to face international competition. • Continuous demonstrations and stoppages of the conveyor and agricultural sector, it is necessary to address efficiency diagnostics, micro-level, to enrich the discussion of the competitiveness of the different sectors of the Colombian economy.