Our review of 137 published papers in the economics literature was disaggregated by the typical sampling levels used in field research that examines the adoption and impact of Genetically Engineered (GE) technologies. The levels include farmer, consumer, trade, and industry. Here we present salient notes from the impact on farmers.

Peer-reviewed research indicates that, on average, during the first decade of their use by smallholder farmers in developing economies, transgenic crops—and in particular Bt cotton—provide economic advantages for adopting farmers. There are several methodological limitations associated with the first generation studies which have been identified in most cases by the authors themselves. These limitations have implications for findings and for policy formulation. They should also be addressed (and are being addressed) in the next generation of studies.

  • The majority of studies reviewed used primary field data collected from farmers, farm records, or field trials conducted by researchers
  • Most ex post (after deliberate release) studies used methods such as partial budgeting/farm accounting and a specification of a model grounded on theoretical economics frameworks such as production functions or random utility models.
  • Few studies have been ex ante (before deliberate release). Most of these use field data and an econometric estimation to then project potential economic impacts.
  • Most studies focused on Bt cotton and were conducted in India, China, and South Africa.  This is not a surprising outcome as this was one of the first and most widely diffused technology in developing countries.
  • A set of studies in Mexico and Argentina examined the implications of intellectual property rights on economic benefits earned by farmers.

Literature review caveats:

  • On average, across all studies, farmers gained from the introduction and use of GM technologies. This does not mean that all farmers profited from its adoption. Furthermore, the magnitude of economic benefits varied widely across geography and the nature of the cropping season. These outcomes are neither surprising nor specific to transgenic technologies.
  • The study period length had a dramatic impact on findings. The nature of adoption, technology impact, and innovation processes usually develops over time and, in some cases, it may take decades for such processes to completely unfold. This has major implications for technology assessments and for technology assessments within a regulatory process such as biosafety.
  • Since the majority of studies were conducted early in the adoption process, they focused on first round impacts on yields, pesticide changes, and impacts on other inputs such as labor.
  • Some attention has been paid to impacts on poverty, inequality, health, and the environment. Due to the time period during which the studies were conducted, the later assessments were done fairly simply, using mostly indicators rather than formal economic theory or frameworks.
  • Few authors have studied few events to date. As a result, generalization about other events can’t be made.
  • Most studies reviewed need to address selection, measurement, and estimation biases and thus endogeneity. Researchers have to consider such sampling and statistical issues when designing field surveys, especially in ex post studies and when using data collected for baselines and/or the basis to conduct projections/estimations in ex ante studies.

Reference

Smale, Melinda; Zambrano, Patricia; Gruère, Guillaume; Falck-Zepeda, José; Matuschke, Ira; Horna, Daniela; Nagarajan, Latha; Yerramareddy, Indira; Jones, Hannah. 2009. Measuring the economic impacts of transgenic crops in developing agriculture during the first decade: Approaches, findings, and future directions. (Food policy review 10) Washington, D.C.: International Food Policy Research Institute (IFPRI) 107 pages
http://www.ifpri.org/sites/default/files/publications/pv10.pdf  
 http://dx.doi.org/10.2499/0896295117FPRev10

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