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Africa's Green Revolution? The determinants of the adoption of NERICAs in West Africa

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Author Info

  • Aliou Diagne

    ()
    (Africa Rice Centre, Cotonou, Benin)

  • Steven Glover

    (Overseas Development Institute, London, UK)

  • Ben Groom

    ()
    (Department of Gography and Environment, London School of Economics, London, UK)

  • Jonathan Phillips

    (Department of Economics, SOAS, University of London, UK)

Abstract

We analyse the rate and determinants of adoption of modern rice varieties (NERICAs) in Guinea, The Gambia and Cote d'Ivoire. The role of knowledge and information is evaluated using programme evaluation methods. Using household data collected by the Africa Rice Centre we show that the exposure and access to seeds lead to radically different levels of adoption by country: 30% in Cote D’Ivoire compared to around 90% for The Gambia and Guinea. Analysis of the determinants of adoption in each country reveals the heterogeneity in the role of agricultural and societal conditions and implies country/province specific policies are appropriate.

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Bibliographic Info

Paper provided by Department of Economics, SOAS, University of London, UK in its series Working Papers with number 174.

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Length: 39 pages
Date of creation: Jun 2012
Date of revision:
Handle: RePEc:soa:wpaper:174

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Related research

Keywords: NERICA Varieties; Technology Adoption; West Africa; Food Security;

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  1. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  2. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780199267699, October.
  3. Wooldridge, Jeffrey M., 2005. "Violating Ignorability Of Treatment By Controlling For Too Many Factors," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 21(05), pages 1026-1028, October.
  4. Guido Imbens & Jeffrey Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Working Papers 11259, National Bureau of Economic Research, Inc.
  6. Hotz, V. Joseph & Crump, Richard K. & Mitnik, Oscar A. & Imbens, Guido, 2009. "Dealing with Limited Overlap in Estimation of Average Treatment Effects," Scholarly Articles 3007645, Harvard University Department of Economics.
  7. Dalton, Timothy J. & Guei, Robert G., 2003. "Productivity Gains from Rice Genetic Enhancements in West Africa: Countries and Ecologies," World Development, Elsevier, Elsevier, vol. 31(2), pages 359-374, February.
  8. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 9(2), pages 85-110, Spring.
  9. Mark Rosenzweig & Andrew D. Foster, . "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Home Pages _068, University of Pennsylvania.
  10. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, Elsevier, vol. 73(1), pages 185-213, February.
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