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Taking a new look at empirical models of adoption: average treatment effect estimation of adoption rates and their determinants

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  • Aliou Diagne
  • Matty Demont

Abstract

This article shows that the observed sample adoption rate does not consistently estimate the population adoption rate even if the sample is random. It is proved that instead the sample adoption rate is a consistent estimate of the population joint exposure and adoption rate, which does not inform about adoption per se. Likewise, it is shown that a model of adoption with observed adoption outcome as a dependent variable and where exposure to the technology is not observed and controlled for cannot yield consistent estimates of the determinants of adoption. The article uses the counterfactual outcomes framework to show that the true population adoption rate corresponds to what is defined in the modern policy evaluation literature as the average treatment effect (ATE), which measures the effect or impact of a “treatment” on a person randomly selected in the population. In the adoption context, a “treatment” corresponds to exposure to the technology. The article uses the ATE estimation framework to derive consistent nonparametric and parametric estimators of population adoption rates and their determinants and applies the results to consistently estimate the population adoption rates and determinants of the NERICA (New Rice for Africa) rice varieties in Côte d'Ivoire. The ATE methodological approach developed in the article has significant policy implications with respect to judging the intrinsic merit of a new technology in terms of its potential demand by the target population independently of issues related to its accessibility and in terms of the decision to invest or not in its wide‐scale dissemination.

Suggested Citation

  • Aliou Diagne & Matty Demont, 2007. "Taking a new look at empirical models of adoption: average treatment effect estimation of adoption rates and their determinants," Agricultural Economics, International Association of Agricultural Economists, vol. 37(2‐3), pages 201-210, September.
    • Handle: RePEc:bla:agecon:v:37:y:2007:i:2-3:p:201-210
    DOI: 10.1111/j.1574-0862.2007.00266.x
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    1. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6a.
    2. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January.
    3. Robert Moffitt, 1991. "Program Evaluation With Nonexperimental Data," Evaluation Review, , vol. 15(3), pages 291-314, June.
    4. J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6b.
    5. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, number 9780199267699.
    6. Dalton, Timothy J., 2004. "A household hedonic model of rice traits: economic values from farmers in West Africa," Agricultural Economics, Blackwell, vol. 31(2-3), pages 149-159, December.
    7. Aliou DIAGNE, 2006. "Diffusion And Adoption Of Nerica Rice Varieties In Côte D’Ivoire," The Developing Economies, Institute of Developing Economies, vol. 44(2), pages 208-231, June.
    8. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    9. Dimara, Efthalia & Skuras, Dimitris, 2003. "Adoption of agricultural innovations as a two-stage partial observability process," Agricultural Economics, Blackwell, vol. 28(3), pages 187-196, May.
    10. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, September.
    11. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    12. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-139, February.
    13. Besley, Timothy & Case, Anne, 1993. "Modeling Technology Adoption in Developing Countries," American Economic Review, American Economic Association, vol. 83(2), pages 396-402, May.
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