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The Price of Inefficiency in Indian Agriculture

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  • Badau, Flavius
  • Rada, Nicholas

Abstract

We use an innovative approach to predict agricultural revenues had farmers optimally reallocated production among agricultural commodities in order to minimize inefficiency. To that end, we employ a newly constructed 1980-2008 state-level production account of Indian agriculture, a directional distance frontier specification, and an innovative output-reallocation predictive model to test whether India’s farmers have achieved maximum potential revenues from their choice of agricultural commodity mix given the various policy, environmental, and input supply constraints. The results show substantial levels of technical inefficiency in Indian agriculture (18%). The output reallocation model predicts that Indian agricultural revenues could have been 22 % higher had farmers optimally shifted their agricultural commodity mix in order to minimize inefficiency.

Suggested Citation

  • Badau, Flavius & Rada, Nicholas, 2016. "The Price of Inefficiency in Indian Agriculture," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235622, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea16:235622
    DOI: 10.22004/ag.econ.235622
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    References listed on IDEAS

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    1. Rolf Färe & Carlos Martins-Filho & Michael Vardanyan, 2010. "On functional form representation of multi-output production technologies," Journal of Productivity Analysis, Springer, vol. 33(2), pages 81-96, April.
    2. Cross, Robin & Färe, Rolf & Grosskopf, Shawna & Weber, William L., 2013. "Valuing Vineyards: A Directional Distance Function Approach," Journal of Wine Economics, Cambridge University Press, vol. 8(1), pages 69-82, May.
    3. Badau, Flavius & Färe, Rolf & Gopinath, Munisamy, 2016. "Global resilience to climate change: Examining global economic and environmental performance resulting from a global carbon dioxide market," Resource and Energy Economics, Elsevier, vol. 45(C), pages 46-64.
    4. Bostian, Moriah B. & Herlihy, Alan T., 2014. "Valuing tradeoffs between agricultural production and wetland condition in the U.S. Mid-Atlantic region," Ecological Economics, Elsevier, vol. 105(C), pages 284-291.
    5. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
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    More about this item

    Keywords

    Agricultural and Food Policy; Crop Production/Industries; Food Security and Poverty; Livestock Production/Industries; Production Economics; Productivity Analysis;
    All these keywords.

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