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Reconsidering Post Green Revolution Food Choices: New Processing Technologies and Food Security in India


  • Miller-Tait, Evan
  • Luckert, Marty
  • Mohapatra, Sandeep
  • Swallow, Brent


Though the Green Revolution has played a large role in producing food for increasing populations, the mass production of calories has come with costs. For example, varieties of finger millet (Eleusine coracana, known in India as ragi), which have largely been replaced during the Green Revolution, are generally more nutritious than high yielding varieties of cereals such as rice, maize, and wheat (National Research Council, 1996). Before being consumed, ragi must be ground into flour, and the drudgery associated with the preparation of this grain for consumption could be prohibiting ragi production amongst subsistence farmers (Finnis, 2009). To help promote the consumption of ragi flour, scholars have advocated the introduction of innovations in processing ragi for small and large-scale entrepreneurs (e.g., Singh and Raghuvanshi 2012). Recently, small-scale flourmills have been introduced into rural villages by the M.S. Swaminathan Research Foundation with the goal of reversing the decline in local ragi consumption and improving food security amongst households in the community that are disadvantaged and have lower levels of wealth. The establishment of these mills was facilitated by entrepreneurial Self-Help Groups (SHGs). This intervention provides us with an opportunity to investigate the introduction of a new technology, facilitated by SHGs. The objective of our research is to investigate the determinants that drive households‟ use of ragi processing technology. We investigate these determinants using a unique primary dataset, collected from 575 households in rural Tamil Nadu in 2012. Spatial (GIS) techniques were used extensively in our sampling plan and analysis. We employ a two-stage technology adoption framework as a basis for analyzing two key decisions made by the household regarding the production of ragi flour: 1) whether or not to adopt the processing technology (the adoption equation), and – conditional upon adoption – 2) how much ragi flour to produce (the intensity equation). This approach allows us to address a number of key policy questions: Is ragi flour a “poor-person‟s food” (i.e. an inferior good, as suggested by social stigma), or is it a normal good? How do demographic factors affect the adoption and intensity of use of this technology? What are the effects of the prices of ragi grain, ragi flour, and wheat flour on the adoption and intensity decisions? How do the travel costs of accessing these mills affect household‟s decision to adopt the milling services? In analyzing these questions, we pay attention to potential selection biases in adoption caused by unobserved variables. We explore whether the effects of these unobserved variables are consistent with increasing or decreasing welfare. We find that the mills are systematically being placed in close proximity to wealthier households, despite evidence that disadvantaged households have a higher propensity to adopt this technology.

Suggested Citation

  • Miller-Tait, Evan & Luckert, Marty & Mohapatra, Sandeep & Swallow, Brent, 2013. "Reconsidering Post Green Revolution Food Choices: New Processing Technologies and Food Security in India," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150347, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea13:150347

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    References listed on IDEAS

    1. Leung, Siu Fai & Yu, Shihti, 1996. "On the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 197-229.
    2. S. Mahendra Dev, 2008. "India," Chapters,in: Handbook on the South Asian Economies, chapter 1 Edward Elgar Publishing.
    3. Mohapatra, Sandeep & Rozelle, Scott & Goodhue, Rachael, 2007. "The Rise of Self-Employment in Rural China: Development or Distress?," World Development, Elsevier, vol. 35(1), pages 163-181, January.
    4. Borjas, George J & Bronars, Stephen G, 1989. "Consumer Discrimination and Self-employment," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 581-605, June.
    5. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    6. Kawaguchi Daiji, 2005. "Negative Self Selection into Self-employment among African Americans," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(1), pages 1-27, May.
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