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

Agricultural Economics

Volumn 37, Issue 2-3, 2007, Pages 201-210

  Diagne, Aliou ^a   Demont, Matty ^a  

^a AFRICA RICE CENTER AFRICARICE   (Benin)

Author keywords

Average treatment effect; NERICA; Rice; Technology adoption; West Africa

Indexed keywords

EMPIRICAL ANALYSIS; ESTIMATION METHOD; INVESTMENT; POLICY ANALYSIS; RICE; TECHNOLOGY ADOPTION;

AFRICA; COTE D'IVOIRE; SUB-SAHARAN AFRICA; WEST AFRICA;

EID: 36849090086     PISSN: 01695150     EISSN: 15740862     Source Type: Journal    
DOI: 10.1111/j.1574-0862.2007.00266.x     Document Type: Conference Paper

References (23)

1. Angrist, J. D., Imben, G. W., Rubin, D. B., 1996. Identification and causal effects using instrumental variables. J. Am. Stat. Assoc. 91, 444 455.
2. Besley, T., Case, A., 1993. Modeling technology adoption in developing countries. The American Economic Review, Vol. 83, No. 2, Papers and Proceedings of the 105 Annual Meeting of the American Economic Association, Anaheim, California. pp. 396 402.
3. Blundell, R., Costa Dias, M., 2000. Evaluation methods for non-experimental data. Fiscal Studies 21 (4 427 468.
4. Cameron, C., Trivedi, P., 2005. Microeconometrics: Methods and Applications. Cambridge University Press, New York.
5. Dalton, T. J., 2004. A household hedonic model of rice traits: economic values from farmers in West Africa. Agric. Econ. 31, 149 159.
6. Diagne, A., 2006. The diffusion and adoption of NERICA rice varieties in Côte d'Ivoire. Dev. Econ. 44, 2 June 2006.
7. Dimara, E., Skuras, D., 2003. Adoption of agricultural innovations as a two-stage partial observability process. Agric. Econ. 28, 187 196.
8. Doss, C. R., 2006. Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement. Ag. Econ. 34 (3 207 219.
9. Feder, G., Just, R. E., Zilberman, D., 1985. Adoption of agricultural innovations in developing countries: a survey. Econ. Dev. Cult. Change 33 (2 255 295.
10. Heckman, J., 1996. Randomization and social program evaluation as an instrumental variable. Rev. Econ. Stat. 77 (2 336 341.
11. Heckman, J. J., Lalonde, R. J., Smith, J. A., 1999. The economics and econometrics of active labor markets programs. In, Ashenfelter, O. C., Card, D. (Eds Handbook of Labor Economics 3B. Elsevier Sciences, North-Holland.
12. Heckman, J, Vytlacil, E., 2007a. Econometric evaluation of social programs, part I: causal models, structural models and econometric policy. In Handbook of econometrics, Vol. 6B, J. Heckman and E. Leamer, eds. Elsevier Science, Amsterdam.
13. Heckman, J, Vytlacil, E., 2007b. Econometric evaluation of social programs, part II: using the marginal treatment effect to organize alternative economic estimators to evaluate social programs and to forecast their effects in new environments. In Handbook of econometrics, Vol. 6B, J. Heckman and E. Leamer, eds. Elsevier Science, Amsterdam.
14. Imbens, G. W., 2004. Nonparametric estimation of average treatment effects under exogeneity: a review. Rev. Econ. Stat. 86 (1 4 29.
15. Imbens, G. W., Newey, W., 2003. Identification and estimation of triangular simultaneous equations models without additivity. MIT Department of Economics Working Paper.
16. Lee, M.-J., 2005. Micro-econometrics for policy, program and treatment effects. Advanced texts in econometrics. Oxford University Press, New York.
17. Matzkin, R., 2003. Nonparametric estimation of nonadditive random functions. Econometrica 71, 1339 1375.
18. Moffitt, R., 1991. Program evaluation with nonexperimental data. Eval. Rev. 15 (3 291 314.
19. Rosenbaum, P. R., Rubin, D. R., 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41 55.
20. Saha, L., Alan, L. H., Robert, S., 1994. Adoption of emerging technologies under output uncertainty. Am. J. Agric. Econ. 76, 836 846.
21. Sunding, D., Zilberman, D., 2001. The agricultural innovation process: research and technology adoption in a changing agricultural sector. In: Gardner, B., Rausser, G. (Eds Handbook of Agricultural and Resource Economics. Elsevier Science, Amsterdam, pp. 207 261.
22. Wooldridge, J., 2002. Econometric analysis of cross section and panel data. The MIT Press, Cambridge, MA.
23. Yatchew, A., Griliches, Z., 1985. Specification error in probit models. Rev. Econ. Stat. 67 (1 134 139.