Bias from farmer self-selection in genetically modified crop productivity estimates: Evidence from Indian data

Journal of Agricultural Economics

Volumn 58, Issue 1, 2007, Pages 24-36

  Crost, Benjamin ^a   Shankar, Bhavani ^a   Bennett, Richard ^a   Morse, Stephen ^a  

^a UNIVERSITY OF READING   (United Kingdom)

Author keywords

Biotechnology; Development economics; Genetic modification; Productivity analysis

Indexed keywords

BIOTECHNOLOGY; COTTON; CROP PRODUCTION; CROP YIELD; DEVELOPING WORLD; DEVELOPMENT ECONOMICS; PANEL DATA; TRANSGENIC PLANT;

ASIA; EURASIA; INDIA; SOUTH ASIA;

BACILLUS THURINGIENSIS; GOSSYPIUM HIRSUTUM; HEXAPODA;

EID: 33846425726     PISSN: 0021857X     EISSN: 14779552     Source Type: Journal    
DOI: 10.1111/j.1477-9552.2007.00076.x     Document Type: Article

References (23)

1. Angrist, J. D. and Krueger, A. B. 'Instrumental variables and the search for identification: From supply and demand to natural experiments', Journal of Economic Perspectives, Vol. 15, (2001) pp. 69-85.
2. Barrett, C. B., Moser, C. M., McHugh, O. V. and Barison, J. 'Better technology, better plots, or better farmers? Identifying changes in productivity and risk among Malagasy rice farmers', American Journal of Agricultural Economics, Vol. 86, (2004) pp. 869-888.
3. Bennett, R., Ismael, Y., Morse, S. and Shankar, B. 'Reductions in insecticide use from adoption of Bt cotton in South Africa: Impacts on economic performance and toxic load to the environment', Journal of Agricultural Science, Vol. 142, (2004) pp. 665-674.
4. Bennett, R., Kambhampati, U., Morse, S. and Ismael, B. 'Farm-level economic performance of genetically modified cotton in Maharashtra, India', Review of Agricultural Economics, Vol. 28, (2006) pp. 59-71.
5. Bound, J., Jaeger, D. A., Baker, R. M. 'Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variables is weak', Journal of the American Statistical Association, Vol. 90, (1995) pp. 443-450.
6. FAO. The State of Food and Agriculture 2003-2004 (Rome: FAO, 2004).
7. GRAIN. GM Cotton Set to Invade West Africa: Time to Act! (GRAIN: Cotonou, Benin, 2004). http://www.grain.org/briefings_files/ Btcotton-june-2004-en.pdf. Last accessed: January 2006.
8. Hausman, J. and Taylor, W. 'Panel data and unobservable individual effects', Econometrica, Vol. 49, (1981) pp. 1377-1398.
9. Heckman, J. and Robb, R. 'Alternative methods for evaluating the impact of interventions', in: J. Heckman and B. Singer (eds) Longitudinal Analysis of Labor Market Data (New York: Cambridge University Press, 1985, pp. 156-245).
10. Huang, J., Hu, R., Rozelle, S., Qiao, F. and Pray, C. E. 'Transgenic varieties and productivity of smallholder cotton farmers in China', Australian Journal of Agricultural and Resource Economics, Vol. 46, (2002) pp. 367-387.
11. Huang, J., Hu, R., Rozelle, S. and Pray, C. E. 'Insect-resistant GM rice in farmers'fields: Assessing productivity and health effects in China', Science, Vol. 308, (2005) pp. 688-690.
12. James, C. Global Status of Commercialized Biotech/GM Crops: 2005. ISAAA Briefs, No. 34 (Ithaca, NY: ISAAA, 2005).
13. Marra, M., Pannell, D. J. and Ghadim, A. A. 'The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: Where are we on the learning curve?' Agricultural Systems, Vol. 75, (2003) pp. 215-234.
14. Nuffield Council on Bioethics. The Use of Genetically Modified Crops in Developing Countries (London: Nuffield Council for Bioethics, 2003).
15. Pray, C. E., Bengali, P. and Ramaswami, B. Costs and Benefits of Biosafety Regulation in India: A Preliminary Assessment (Paper presented at the 8th ICABR International Conference on Agricultural Biotechnology: International Trade and Domestic Production, Ravello, Italy, 2004). http://www.economia.uniroma2.it/conferenze/icabr2004/papers/Pray.C.zip. Last accessed: January 2006.
16. Qaim, M. and de Janvry, A. 'Bt cotton and pesticide use in Argentina: Economic and environmental effects', Environment and Development Economics, Vol. 10, (2005) pp. 179-200.
17. Qaim, M., Subramanian, A., Gopal, N. and Zilberman, D. 'Adoption of Bt cotton and impact variability: Insights from India', Review of Agricultural Economics, Vol. 28, (2006) pp. 48-58.
18. Qaim, M. and Zilberman, D. 'Yield effects of genetically modified crops in developing countries', Science, Vol. 299, (2003) pp. 900-902.
19. Rosenbaum, P. and Rubin, D. B. 'The central role of the propensity score in observational studies for causal effects', Biometrika, Vol. 70, (1983) pp. 41-55.
20. Shankar, B. and Thirtle, C. 'Pesticide productivity and transgenic cotton technology: The South African smallholder case'. Journal of Agricultural Economics, Vol. 56, (2005) pp. 97-116.
21. Thirtle, C., Beyers, L., Ismael, Y. and Piesse, J. 'Can GM-technologies help the poor? The impact of Bt cotton in Makhatini Flats, KwaZulu-Natal', World Development, Vol. 31, (2003) pp. 717-732.
22. Winship, C. and Morgan, S. L. 'The estimation of causal effects from observational data', Annual Review of Sociology, Vol. 25, (1999) pp. 659-706.
23. Winship, C. and Mare, R. D. 'Models for sample selection bias', Annual Review of Sociology, Vol. 18, (1992) pp. 327-350.