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

Benjamin Crost, Bhavani Shankar, Richard Bennett, Stephen Morse

Research output: Contribution to journalArticlepeer-review

Abstract

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

Original languageEnglish (US)
Pages (from-to)24-36
Number of pages13
JournalJournal of Agricultural Economics
Volume58
Issue number1
DOIs
StatePublished - Feb 1 2007
Externally publishedYes

Keywords

  • Biotechnology
  • Development economics
  • Genetic modification
  • Productivity analysis

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Economics and Econometrics

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