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Subjective Risks and Barriers to Perennial Bioenergy Production: Estimating a Structural Model with Data from a Hypothetical Market Experiment

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  • Smith, David J.

Abstract

Due in part to concerns over energy security and the environmental impacts of fossil fuels, recent United States energy policy has included provisions to promote renewable energy. The Energy Policy Act includes provisions for advanced biofuels from cellulosic biomass. Perennial bioenergy crops such as perennial grasses and woody crops are an alternative source of feedstock for biofuel with lower environmental impacts than their annual counterparts. Previous work has shown that, when perennial grasses are financially competitive with a farmer’s current crops, a majority of farmers will produce perennial grasses but only on a small portion of their land. One potential explanation for this is the risk posed by growing a new crop and selling it into a new emerging market. Therefore this study uses the land allocation under risk framework developed by Just and Zilberman (1988) to estimate structural parameters. The structural system is estimated using full information maximum likelihood. Observation of the acreage choice is condi- tional on the risk-adjusted profits being positive making the estimation method analogous to Heckman’s simultaneous sample correction method. As a result of using a structural mixed-processes system the scale parameter of the discrete choice equation can be identi- fied. Results suggest that agricultural landowners perceive an order of magnitude higher risk to perennial bioenergy production than their current production system. These results are partly driven by the risk management options currently available for commodity crops such as crop insurance, futures markets, and risk reducing inputs. Agricultural landowners also perceive woody crops as risker and with higher adoption costs than perennial grasses.

Suggested Citation

  • Smith, David J., 2016. "Subjective Risks and Barriers to Perennial Bioenergy Production: Estimating a Structural Model with Data from a Hypothetical Market Experiment," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236343, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea16:236343
    DOI: 10.22004/ag.econ.236343
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    References listed on IDEAS

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    1. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    2. Just, Richard E. & Zilberman, David, 1988. "The effects of agricultural development policies on income distribution and technological change in agriculture," Journal of Development Economics, Elsevier, vol. 28(2), pages 193-216, March.
    3. Mesbah Motamed & Lihong McPhail & Ryan Williams, 2016. "Corn Area Response to Local Ethanol Markets in the United States: A Grid Cell Level Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 726-743.
    4. Bocquého, G. & Jacquet, F., 2010. "The adoption of switchgrass and miscanthus by farmers: Impact of liquidity constraints and risk preferences," Energy Policy, Elsevier, vol. 38(5), pages 2598-2607, May.
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    Keywords

    Crop Production/Industries; Production Economics; Resource /Energy Economics and Policy; Risk and Uncertainty;
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