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Efficiency Measure from Dynamic Stochastic Production Frontier: Application to Tunisian Textile, Clothing, and Leather Industries

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  • Rim Ben Ayed-Mouelhi
  • Mohamed Goa�ed

Abstract

This paper adresses the measurement of technical efficiency of textile, clothing, and leather (TCL) industries in Tunisia through a panel data estimation of a dynamic translog production frontier. It provides a perspective on productivity and efficiency that should be instructive to a developing economy which will face substantial competitive pressure along the gradual economic liberalisation process. The importance of TCL industries in Tunisian manufacturing sector is a reason for obtaining more knowledge of productivity and efficiency for this key industry. Dynamic is introduced to reflect the production consequences of the adjustment costs, which are associated with changes in factor inputs. Estimation of a dynamic error components model is considered using the system generalized method of moments (GMM) estimator suggested by Arellano and Bover (1995), Another look at the instrumental-variable estimation of error-components models, J. Econometrics 68:29-51) and Blundell and Bond (Blundell, R., Bond, S. (1998a), Initial conditions and moment restrictions in dynamic panel data models. J. Econometrics 87:115-143; Blundell, R., Bond, S. (1998b), GMM estimation with persistent panel data: an application to production functions, Paper presented at the Eighth International Conference on Panel Data, Goteborg University). Our study evaluates the sensitivity of the results, particularly of the efficiency measures, to different specifications. Firm-specific time-invariant technical efficiency is obtained using the Schmidt and Sickles (Schmidt, P., Sickles, R. C. (1984). Production frontiers and panel data. J. Bus. Econ. Stat. 2:367-374) approach after estimating the dynamic frontier. We stress the importance of allowing for lags in adjustment of output to inputs and of controlling for time-invariant variables when estimating firm-specific efficiency. The results suggest that the system GMM estimation of the dynamic specification produces the most accurate parameter estimates and technical efficiency measure. Mean efficiency scores is of 68%. Policy implications of the results are outlined.

Suggested Citation

  • Rim Ben Ayed-Mouelhi & Mohamed Goa�ed, 2003. "Efficiency Measure from Dynamic Stochastic Production Frontier: Application to Tunisian Textile, Clothing, and Leather Industries," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 93-111, February.
    • Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:93-111
    DOI: 10.1081/ETC-120017976
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    1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    2. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    3. Mohamed Goaïed & Rym Ayed-Mouelhi, 2000. "Efficiency Measurement With Unbalanced Panel Data: Evidence from Tunisian Textile, Clothing and Leather Industries," Journal of Productivity Analysis, Springer, vol. 13(3), pages 249-262, May.
    4. Ahn, Seung C. & Schmidt, Peter, 1997. "Efficient estimation of dynamic panel data models: Alternative assumptions and simplified estimation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 309-321.
    5. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Cited by:

    1. Aditi Bhattacharyya, 2012. "Adjustment of inputs and measurement of technical efficiency: A dynamic panel data analysis of the Egyptian manufacturing sectors," Empirical Economics, Springer, vol. 42(3), pages 863-880, June.
    2. Coll Serrano, V. & Blasco Blasco, O.Mª., 2009. "Evolución de la eficiencia técnica de la industria textil española en el periodo 1995-2005. Análisis mediante un modelo frontera estocástica/Technical Efficiency In The Textile Industry Of Spain In Th," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 27, pages 779(32á)-77, Diciembre.
    3. Mohamed Ali Marouani & Rim Mouelhi, 2016. "Contribution of Structural Change to Productivity Growth: Evidence from Tunisia," Journal of African Economies, Centre for the Study of African Economies, vol. 25(1), pages 110-132.
    4. repec:dau:papers:123456789/11536 is not listed on IDEAS
    5. Massimiliano Agovino & Agnese Rapposelli, 2015. "Agglomeration externalities and technical efficiency in Italian regions," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(5), pages 1803-1822, September.
    6. Fethi AMRI & Rim MOUELHI, 2013. "Productivity Growth And Competition In Tunisian Manufacturing Firms," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 37, pages 37-64.
    7. Elitsa R. Banalieva & Michael D. Santoro & Joy Ruihua Jiang, 2012. "Home Region Focus and Technical Efficiency of Multinational Enterprise," Management International Review, Springer, vol. 52(4), pages 493-518, August.
    8. Michael Gasiorek, 2007. "Determinants of Productivity in Morocco: The Role of Trade?," Working Papers 716, Economic Research Forum, revised 01 Jan 2007.

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