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Commodity Storage and the Market Effects of Biofuel Policies

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  • Carter, Colin A
  • Rausser, Gordon C
  • Smith, Aaron

Abstract

Legislation passed in 2007 by the U.S. Congress increased by about 1.3 billion bushels the net amount of corn required to be processed annually into ethanol for motor-fuel use. We estimate that corn prices were about 30% higher from 2006 to 2014 than they would have been without this demand increase. We develop a partially identified structural vector autoregression model. Our identification strategy is unique in the literature because it enables us to estimate the effects of transitory shocks, such as weather, separately from the effects of persistent shocks, such as the increased ethanol mandate. Moreover, by only partially identifying our model, we show how to generate robust conclusions without strong identifying assumptions.

Suggested Citation

  • Carter, Colin A & Rausser, Gordon C & Smith, Aaron, 2017. "Commodity Storage and the Market Effects of Biofuel Policies," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt61t114zb, Department of Agricultural & Resource Economics, UC Berkeley.
  • Handle: RePEc:cdl:agrebk:qt61t114zb
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    Cited by:

    1. Nicolas Legrand & Christophe Gouel, 2022. "The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data," Working Papers hal-03809825, HAL.
    2. Christiane Baumeister & Reinhard Ellwanger & Lutz Kilian, 2016. "Did the Renewable Fuel Standard Shift Market Expectations of the Price of Ethanol?," CESifo Working Paper Series 6282, CESifo.
    3. Johnson, David R. & Geldner, Nathan B. & Liu, Jing & Baldos, Uris Lantz & Hertel, Thomas, 2023. "Reducing US biofuels requirements mitigates short-term impacts of global population and income growth on agricultural environmental outcomes," Energy Policy, Elsevier, vol. 175(C).
    4. Valenti, Daniele & Bertoni, Danilo & Cavicchioli, Davide & Olper, Alessandro, 2023. "Understanding the role of supply and demand factors in the global wheat market: a Structural Vector Autoregressive approach," FEEM Working Papers 338780, Fondazione Eni Enrico Mattei (FEEM).
    5. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
    6. Karali, Berna & Isengildina-Massa, Olga & Irwin, Scott H. & Adjemian, Michael K. & Johansson, Robert, 2019. "Are USDA reports still news to changing crop markets?," Food Policy, Elsevier, vol. 84(C), pages 66-76.
    7. An, Henry & Qiu, Feng & Rude, James, 2021. "Volatility spillovers between food and fuel markets: Do administrative regulations affect the transmission?," Economic Modelling, Elsevier, vol. 102(C).
    8. De Lipsis, Vincenzo & Agnolucci, Paolo, 2024. "Climate change and the US wheat commodity market," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
    9. Iglesias Pinedo, Wilman J., 2021. "The impact of Renewable Energy Standards on the biomass supply and agricultural land demand in the US Great Plains Region," 2021 Annual Meeting, August 1-3, Austin, Texas 314085, Agricultural and Applied Economics Association.
    10. Jaimes, Richard & Gerlagh, Reyer, 2020. "Resource-richness and economic growth in contemporary U.S," Energy Economics, Elsevier, vol. 89(C).
    11. Eugenio S.A. Bobenrieth & Juan R.A. Bobenrieth & Ernesto A. Guerra & Brian D. Wright & Di Zeng, 2021. "Putting the Empirical Commodity Storage Model Back on Track: Crucial Implications of a “Negligible” Trend," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1034-1057, May.
    12. Irwin, Scott H., 2020. "Trilogy for troubleshooting convergence: Manipulation, structural imbalance, and storage rates," Journal of Commodity Markets, Elsevier, vol. 17(C).
    13. Ferguson, Shon & Ubilava, David, 2022. "Global commodity market disruption and the fallout," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(04), January.
    14. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Taheripour, Farzad & Baumes, Harry & Tyner, Wally Taheripour, Farzad, 2019. "Impacts of the U.S. Renewable Fuel Standard on Commodity and Food Prices," Conference papers 333127, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    16. Newes, Emily & Clark, Christopher M. & Vimmerstedt, Laura & Peterson, Steve & Burkholder, Dallas & Korotney, David & Inman, Daniel, 2022. "Ethanol production in the United States: The roles of policy, price, and demand," Energy Policy, Elsevier, vol. 161(C).
    17. Taheripour, Farzad & Baumes, Harry S. & Tyner, Wallace E., 2020. "Economic impacts of the U.S. Renewable Fuel Standard: An ex-post evaluation," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304252, Agricultural and Applied Economics Association.
    18. Gerveni, Maria & Serra, Teresa & Irwin, Scott H. & Hubbs, Todd, 2023. "Price connectedness in U.S. ethanol terminal markets," Energy Economics, Elsevier, vol. 124(C).
    19. Christopher L. Gilbert & Harriet Kasidi Mugera, 2020. "Competitive Storage, Biofuels and the Corn Price," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(2), pages 384-411, June.
    20. Baldi, Florencia & Merener, Nicolas, 2021. "Displacement Risk in Agricultural Commodity Markets: The Impact of Plant-Based Meat," 2021 Annual Meeting, August 1-3, Austin, Texas 314057, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    Substance Misuse; Agriculture; energy policy; ethanol; partial identification; vector autoregression; Applied Economics; Agricultural Economics & Policy;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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