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Productivity assessment of African seaports with biased technological change

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  • Carlos Pestana Barros
  • Nicolas Peypoch

Abstract

This paper analyses the productivity of a representative sample of African seaports from 2002 to 2008. Productivity scores are decomposed, based on the Luenberger productivity indicator, and the nature of technological change is analysed. The paper finds that Nigerian seaports are the most efficient, followed by Angola and Mozambique. Discussions of the results as well as related policy implications are provided.

Suggested Citation

  • Carlos Pestana Barros & Nicolas Peypoch, 2012. "Productivity assessment of African seaports with biased technological change," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(6), pages 663-675, May.
    • Handle: RePEc:taf:transp:v:35:y:2012:i:6:p:663-675
    DOI: 10.1080/03081060.2012.710033
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    References listed on IDEAS

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    1. Chambers, Robert G., 1996. "A New Look at Exact Input, Output, Productivity, and Technical Change Measurement," Working Papers 197840, University of Maryland, Department of Agricultural and Resource Economics.
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    Cited by:

    1. Brida, Juan Gabriel & Deidda, Manuela & Pulina, Manuela, 2014. "Tourism and transport systems in mountain environments: analysis of the economic efficiency of cableways in South Tyrol," Journal of Transport Geography, Elsevier, vol. 36(C), pages 1-11.
    2. Carlos Pestana Barros & Zhongfei Chen & Peter Wanke, 2016. "Efficiency in Chinese seaports: 2002–2012," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(3), pages 295-316, September.
    3. Tomas Baležentis & Alfons Oude Lansink, 2020. "Measuring dynamic biased technical change in Lithuanian cereal farms," Agribusiness, John Wiley & Sons, Ltd., vol. 36(2), pages 208-225, April.
    4. Quintano, Claudio & Mazzocchi, Paolo & Rocca, Antonella, 2021. "Evaluation of the eco-efficiency of territorial districts with seaport economic activities," Utilities Policy, Elsevier, vol. 71(C).
    5. Molinos-Senante, María & Maziotis, Alexandros & Sala-Garrido, Ramón, 2014. "The Luenberger productivity indicator in the water industry: An empirical analysis for England and Wales," Utilities Policy, Elsevier, vol. 30(C), pages 18-28.
    6. Marcelo Müller Beuren & Rafael Andriotti & Guilherme Bergmann Borges Vieira & José Luis Duarte Ribeiro & Francisco José Kliemann Neto, 2018. "On measuring the efficiency of Brazilian ports and their management models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(1), pages 149-168, March.
    7. Shaher Z. Zahran & Jobair Bin Alam & Abdulrahem H. Al-Zahrani & Yiannis Smirlis & Stratos Papadimitriou & Vangelis Tsioumas, 2020. "Analysis of port efficiency using imprecise and incomplete data," Operational Research, Springer, vol. 20(1), pages 219-246, March.
    8. Carlos P. Barros & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73, March.
    9. Claudio Quintano & Paolo Mazzocchi & Antonella Rocca, 2020. "A competitive analysis of EU ports by fixing spatial and economic dimensions," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-19, December.
    10. Pedro Moskovics & Peter Wanke & Yong Tan & Ali Meftah Gerged, 2024. "Market structure, ESG performance, and corporate efficiency: Insights from Brazilian publicly traded companies," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 241-262, February.
    11. Maha Kalai & Kamel Helali, 2016. "Technical Change and Total Factor Productivity Growth in the Tunisian Manufacturing Industry: A Malmquist Index Approach," African Development Review, African Development Bank, vol. 28(3), pages 344-356, September.

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