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Journal of African Economies Advance Access originally published online on October 4, 2007
Journal of African Economies 2008 17(2):277-304; doi:10.1093/jae/ejm020
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© The author 2007. Published by Oxford University Press on behalf of the Centre for the Study of African Economies. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

Using a Contingent Valuation Approach for Improved Solid Waste Management Facility: Evidence from Enugu State, Nigeria

William M. Fontaa,b,1, H. Eme Ichokua, Kanayo K. Ogujiubac and Jude O. Chukwuc

a Environmental/Health Economics Unit, Department of Economics, University of Nigeria, Nsukka, Enugu State, Nigeria
b Poverty in Africa Alternative, Nigeria
c Public Policy Units, Department of Economics, University of Nigeria, Nsukka, Enugu State, Nigeria

Corresponding author: William M. Fonta, Environmental Economics Unit, Department of Economics, University of Nigeria Nsukka, Enugu State, Nigeria. Telephone: +234 8035408395. E-mail: williamfonta{at}yahoo.co.uk

For most public projects, especially environmental projects that are partly funded by multilateral donor agencies, cost–benefit analysis has become a routine procedure for the approval of project funds. These agencies are very keen to know whether the target community or country possesses the aggregate willingness to pay for the project. The two most commonly applied techniques for such analysis are stated preference and behavioural techniques. In this study, we employ the contingent valuation method (CVM), the most widely applicable of the stated preference methods, to establish empirical grounds for pricing the services of a new solid waste management (SWM) improvement facility in Enugu State, Nigeria, initiated by the UK Department for International Development, the State's Environmental Protection Agency, and State and Local Government Programme. We find that CVM can be fruitfully used to support the design and implementation of new SWM facilities and that analysis of the valuation function can give qualitative information that is difficult to identify using baseline surveys or most conventional economic valuation techniques.

JEL classifications: C52, C81, D62, O22, Q53

1 The authors acknowledged with enormous gratitude the valuable insights and inputs into this paper from Augustin Fosu and an anonymous referee. We sincerely appreciate their inputs without which this paper would not have been suitable for publication. We equally thank E. Strazzera, A.O. Okore, A. Okorafor and N. Ugwuozor (CEO Povinaa) for very useful comments and suggestions. Usual disclaimer applies. The views expressed herein are those of the authors and do not necessarily reflect those of DFID/ENSEPA/SLGP.


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