COMPARATIVE ANALYSIS OF PRODUCTION EFFICIENCY IN WEST AFRICA
Yıl 2021,
Cilt: 5 Sayı: 1, 99 - 116, 25.03.2021
Alexandrov N. S. Semanou
Kamil Uslu
Öz
The status of West Africa as one of the least developed regions in the world eases the multiplication of studies on development in the area. However, despite their high number, these studies are more about macroeconomics policies and show little interest in the quality of the production process itself. This paper makes a comparative analysis of West African countries’ efficiency with a focus on four neighbouring countries. These are Benin, Ghana, Ivory Coast and Togo. The study is motivated by
the need for going beyond the widely used growth accounting models and performing a comparative analysis between countries using another approach: The Stochastic Frontier Analysis. We find that technical efficiency is relatively high in the zone and varies from a country to another and over time. Ivory Coast turned out to be among the most efficient countries in the production process in the region. Incorporating human capital to the labour factor has different effects on efficiency according to the countries considered. Besides, the comparative analysis sheds light on the differences between the selected countries in both returns to scales and factors’ contribution to output.
Kaynakça
- Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. Journal of productivity analysis, 3(1-2), 153-169.
- Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical economics, 20(2), 325-332
- Coelli, T. (1995). Estimators and hypothesis tests for a stochastic frontier function: A Monte Carlo analysis. Journal of productivity analysis, 6(3), 247-268.
- Coelli, T. J., Rao, D. S. P., O’Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis. Springer Science & Business Media.
- Christensen, L. R., Jorgenson, D. W., & Lau, L. J. (1973). Transcendental logarithmic production frontiers. The review of economics and statistics, 28-45.
- Horrace, W. C., & Schmidt, P. (1996). Confidence statements for efficiency estimates from stochastic frontier models. Journal of Productivity Analysis, 7(2-3), 257-282.
- Karagiannis, G., & Tzouvelekas, V. (2009). Parametric measurement of time-varying technical inefficiency: results from competing models. Agricultural Economics Review, 10(389-2016-23315), 50.
- Kodde, D. A., & Palm, F. C. (1986). Wald criteria for jointly testing equality and inequality restrictions. Econometrica: journal of the Econometric Society, 1243-1248.
- Koop, G., Osiewalski, J., & Steel, M. F. (1999). The components of output growth: A stochastic frontier analysis. Oxford Bulletin of Economics and Statistics, 61(4), 455-487.
- Koop, G., Osiewalski, J., & Steel, M. F. (2000 a). A stochastic frontier analysis of output level and growth in Poland and western economies. Economics of Planning, 33(3), 185-202.
- Koop, G., Osiewalski, J., & Steel, M. F. (2000 b). Modeling the sources of output growth in a panel of countries. Journal of Business & Economic Statistics, 18(3), 284-299.
- Kotsemir, M. (2013). Measuring national innovation systems efficiency–a review of DEA approach. Higher School of Economics Research Paper No. WP BRP, 16.
- Kumbhakar, S. C., & Wang, H. J. (2005). Estimation of growth convergence using a stochastic production frontier approach. Economics Letters, 88(3), 300-305.
- Limam, Y. R. (2002). The components of output growth: A stochastic frontier analysis.
- Mastromarco, C. (2005) Measuring efficiency in developing countries. Unpublished Ph.D. thesis, University of Glasgow.
- Mastromarco, C. (2008). Stochastic frontier models. Italia: University of Salento. [online] Available: http:// www.camillamastromarco.it/CIDE/STFR.pdf (12/09/2018).
- Piesse, J., & Thirtle, C. (2000). A stochastic frontier approach to firm level efficiency, technological change, and productivity during the early transition in Hungary. Journal of comparative economics, 28(3), 473-501.
- Schmidt, P., & Sickles, R. C. (1984). Production frontiers and panel data. Journal of Business & Economic Statistics, 2(4), 367-374.
- Semanou, A. N. S., & Uslu, K. (2019). Comparative Analysis of Growth Convergence in Selected West African Countries. Business and Economic Research, 9(3), 87-101.
Yıl 2021,
Cilt: 5 Sayı: 1, 99 - 116, 25.03.2021
Alexandrov N. S. Semanou
Kamil Uslu
Kaynakça
- Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. Journal of productivity analysis, 3(1-2), 153-169.
- Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical economics, 20(2), 325-332
- Coelli, T. (1995). Estimators and hypothesis tests for a stochastic frontier function: A Monte Carlo analysis. Journal of productivity analysis, 6(3), 247-268.
- Coelli, T. J., Rao, D. S. P., O’Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis. Springer Science & Business Media.
- Christensen, L. R., Jorgenson, D. W., & Lau, L. J. (1973). Transcendental logarithmic production frontiers. The review of economics and statistics, 28-45.
- Horrace, W. C., & Schmidt, P. (1996). Confidence statements for efficiency estimates from stochastic frontier models. Journal of Productivity Analysis, 7(2-3), 257-282.
- Karagiannis, G., & Tzouvelekas, V. (2009). Parametric measurement of time-varying technical inefficiency: results from competing models. Agricultural Economics Review, 10(389-2016-23315), 50.
- Kodde, D. A., & Palm, F. C. (1986). Wald criteria for jointly testing equality and inequality restrictions. Econometrica: journal of the Econometric Society, 1243-1248.
- Koop, G., Osiewalski, J., & Steel, M. F. (1999). The components of output growth: A stochastic frontier analysis. Oxford Bulletin of Economics and Statistics, 61(4), 455-487.
- Koop, G., Osiewalski, J., & Steel, M. F. (2000 a). A stochastic frontier analysis of output level and growth in Poland and western economies. Economics of Planning, 33(3), 185-202.
- Koop, G., Osiewalski, J., & Steel, M. F. (2000 b). Modeling the sources of output growth in a panel of countries. Journal of Business & Economic Statistics, 18(3), 284-299.
- Kotsemir, M. (2013). Measuring national innovation systems efficiency–a review of DEA approach. Higher School of Economics Research Paper No. WP BRP, 16.
- Kumbhakar, S. C., & Wang, H. J. (2005). Estimation of growth convergence using a stochastic production frontier approach. Economics Letters, 88(3), 300-305.
- Limam, Y. R. (2002). The components of output growth: A stochastic frontier analysis.
- Mastromarco, C. (2005) Measuring efficiency in developing countries. Unpublished Ph.D. thesis, University of Glasgow.
- Mastromarco, C. (2008). Stochastic frontier models. Italia: University of Salento. [online] Available: http:// www.camillamastromarco.it/CIDE/STFR.pdf (12/09/2018).
- Piesse, J., & Thirtle, C. (2000). A stochastic frontier approach to firm level efficiency, technological change, and productivity during the early transition in Hungary. Journal of comparative economics, 28(3), 473-501.
- Schmidt, P., & Sickles, R. C. (1984). Production frontiers and panel data. Journal of Business & Economic Statistics, 2(4), 367-374.
- Semanou, A. N. S., & Uslu, K. (2019). Comparative Analysis of Growth Convergence in Selected West African Countries. Business and Economic Research, 9(3), 87-101.