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Industrial Sector Exports In Colombia: Efficient Frontier Analysis

Author

Listed:
  • Jorge A. Restrepo M
  • Lorenzo Portocarrero S
  • Juan Gabriel Vanegas L

Abstract

In this paper, a comparative analysis is carried out among the industrial sectors in Colombia that have the most employees during 2000-2011. 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. 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

Suggested Citation

  • Jorge A. Restrepo M & Lorenzo Portocarrero S & Juan Gabriel Vanegas L, 2015. "Industrial Sector Exports In Colombia: Efficient Frontier Analysis," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 8(2), pages 85-97.
    • Handle: RePEc:ibf:ijmmre:v:8:y:2015:i:2:p:85-97
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    References listed on IDEAS

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    1. Loaiza Quintero, Osmar Leandro & Franco Vásquez, Liliana Yaned, 2012. "Un estudio acerca de los determinantes de la productividad y la ineficiencia técnica en la industria colombiana, 1992-2007 [Determinants of productivity and technical inefficiency in Colombia’s man," MPRA Paper 47736, University Library of Munich, Germany, revised 20 Jun 2013.
    2. Hanoch, Giora & Rothschild, Michael, 1972. "Testing the Assumptions of Production Theory: A Nonparametric Approach," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 256-275, March-Apr.
    3. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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    Cited by:

    1. Mohamed Mehdi Jelassi & Ezzeddine Delhoumi, 2017. "On the Efficiency of Manufacturing Sectors: Evidence from a DEA Additive Bootstrap Model for Tunisia," Economics Bulletin, AccessEcon, vol. 37(2), pages 1393-1400.

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    More about this item

    Keywords

    Dynamic Simulation; Financial Analysis; DEA; Exports;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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