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On measuring indebtedness of African countries: A stochastic frontier debt production function

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  • Nkamleu, Guy Blaise

Abstract

At least since the early 1990s, the problem of Africa’s debt was a recurring theme in the development debate and many suggestions for debt relief have now been implemented. However, a thorough solution is hampered by the existence of multiple ways of scaling debt. This paper provides a framework for comprehensively measuring indebtedness and gives therefore a basis for setting objective principles for debt reduction measures. The paper uses a stochastic frontier production function approach and the technical efficiency computation procedure to develop an indebtedness index for 46 African countries. The results indicate an indebtedness index across countries ranging from a minimum of 3.6 (South-Africa) to a maximum of 92 (Zambia), with an average of 69. Countries, which have experienced extended civil wars, are generally less indebted, while countries with more corrupt governments have generally contracted more multilateral debt. The paper ends by raising a number of implications for a better approach of debt management in Africa.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 14661.

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Date of creation: 2006
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Handle: RePEc:pra:mprapa:14661

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Related research

Keywords: External debt; Stochastic frontier; Indebtedness index; Institutions; African countries;

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References

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  1. Nkamleu, Guy Blaise, 2003. "Productivity Growth, Technical Progress and Efficiency Change in African Agriculture," MPRA Paper 11380, University Library of Munich, Germany.
  2. Dollar, David & Alesina, Alberto, 2000. "Who Gives Foreign Aid to Whom and Why?," Scholarly Articles 4553020, Harvard University Department of Economics.
  3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
  5. Li, Xiaoying & Liu, Xiaming, 2005. "Foreign Direct Investment and Economic Growth: An Increasingly Endogenous Relationship," World Development, Elsevier, vol. 33(3), pages 393-407, March.
  6. Robert J Barro & Jong-Wha Lee, 2003. "IMF Programs: Who Is Chosen and What Are the Effects?," Departmental Working Papers 2003-09, The Australian National University, Arndt-Corden Department of Economics.
  7. Butkiewicz, James L. & Yanikkaya, Halit, 2005. "The Effects of IMF and World Bank Lending on Long-Run Economic Growth: An Empirical Analysis," World Development, Elsevier, vol. 33(3), pages 371-391, March.
  8. Joachim Binam Nyemeck & Guy Blaise Nkamleu, 2006. "Potentiel de Productivité et Efficacité Technique du Secteur Agricole en Afrique," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 54(3), pages 361-377, 09.
  9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
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