Inequality and GM Crops : A Case - Study of Bt Cotton in India

Introduction Farmers are not all the same. Some are more willing to take risks and adopt new technology than others, while some are simply better farmers than others. This has been the case since the birth of agriculture, but debates surrounding ‘inequality’ have, if anything, become more intense in the past 10 years with the increasing popularity of genetically modified (GM) crops. Proponents argue that GM crops represent a major breakthrough in the fight against famine and poverty (Delmer, 2005) and their economic and other advantages to farmers explains their popularity wherever they have been released (Raney, 2006), while critics argue that GM adopters are more likely to be the ‘better’ farmers (in terms of education, ability, interest, access to resources, etc.) within the community. Hence ‘better’ farmers get richer while those farmers unable to take the risks and provide the necessary investment get poorer. Thus, inequality is exacerbated. But what is the evidence for such inequality, both in terms of adoption of GM varieties and the benefits, if any, that they provide? Estimating ‘inequality’ amongst households is a complex field of study, and has not, as yet, been the centerpiece of GM research in developing countries. Instead, the focus has been more upon the impact of GM crops assessed in economic terms across different categories of farmer, typically on a per hectare/acre basis. There are, of course, moral dimensions to this issue as well as material concerns such as the potential for social tension (Quadrado et al., 2001). The typical focus within many studies of inequality is upon income, but it has to be stressed that inequality can be considered in terms of other factors such as education, health care, assets, quality of the natural environment, expenditure, etc. (Sen, 1985; Cohen, 2000). There are a number of measures of equality of distribution of income amongst individuals Stephen Morse, Richard Bennett, and Yousouf Ismael University of Reading, United Kingdom Critics of genetically modified (GM) crops often contend that their introduction enhances the gap between rich and poor farmers, as the former group are in the best position to afford the expensive seed as well as provide other inputs such as fertilizer and irrigation. The research reported in this paper explores this issue with regard to Bt cotton (cotton with the endotoxtin gene from Bacillus thuringiensis conferring resistance to some insect pests) in Jalgaon, Maharashtra State, India, spanning the 2002 and 2003 seasons. Questionnaire-based survey results from 63 non-adopting and 94 adopting households of Bt cotton were analyzed, spanning 137 Bt cotton plots and 95 non-Bt cotton plots of both Bt adopters and non-adopters. For these households, cotton income accounted for 85 to 88% of total household income, and is thus of vital importance. Results suggest that in 2003 Bt adopting households have significantly more income from cotton than do non-adopting households (Rp 66,872 versus Rp 46,351) but inequality in cotton income, measured with the Gini coefficient (G), was greater amongst non-adopters than adopters. While Bt adopters had greater acreage of cotton in 2003 (9.92 acres versus 7.42 for non-adopters), the respective values of G were comparable. The main reason for the lessening of inequality amongst adopters would appear to be the consistency in the performance of Bt cotton along with the preferred non-Bt cultivar of Bt adopters – Bunny. Taking gross margin as the basis for comparison, Bt plots had 2.5 times the gross margin of non-Bt plots of non-adopters, while the advantage of Bt plots over non-Bt plots of adopters was 1.6 times. Measured in terms of the Gini coefficient of gross margin/acre it was apparent that inequality was lessened with the adoption of Bunny (G = 0.47) and Bt (G = 0.3) relative to all other non-Bt plots (G = 0.63). Hence the issue of equality needs to be seen both in terms of differences between adopters and non-adopters as well as within each of the groups.