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How Relevant Has Been the Learning-by-Doing for Brazilian Sugarcane Ethanol Production?

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  • Héctor M. Núñez

    (Division of Economics, CIDE)

Abstract

This paper examines the role of several factors in reducing the production costs of Brazilian sugarcane ethanol, including learning-by-doing (LBD), economies of scale, rising factor prices, market competitiveness, and exogenous technological changes. Using the aggregate industry-level data over the period 1975- 2010, we find that the reduction in production costs of sugarcane ethanol was primarily driven by autonomous technological changes and unrelated to LBD. The increase in energy prices raised production costs of sugarcane ethanol, while the effects of other input prices on reducing production costs of sugarcane ethanol are found to be insignificant. By increasing the costs of procuring key inputs for ethanol production, market competitiveness had a negative effect on reducing production costs of sugarcane ethanol. The role of economies of scale in affecting sugarcane ethanol production costs is inconclusive depending on model specifications.

Suggested Citation

  • Héctor M. Núñez, 2013. "How Relevant Has Been the Learning-by-Doing for Brazilian Sugarcane Ethanol Production?," Working Papers DTE 552, CIDE, División de Economía.
  • Handle: RePEc:emc:wpaper:dte552
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    File URL: http://www.economiamexicana.cide.edu/RePEc/emc/pdf/DTE/DTE552.pdf
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    References listed on IDEAS

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    1. Fransman, Martin, 1986. "International competitiveness, technical change and the state: The machine tool industry in Taiwan and Japan," World Development, Elsevier, vol. 14(12), pages 1375-1396, December.
    2. Papineau, Maya, 2006. "An economic perspective on experience curves and dynamic economies in renewable energy technologies," Energy Policy, Elsevier, vol. 34(4), pages 422-432, March.
    3. Hettinga, W.G. & Junginger, H.M. & Dekker, S.C. & Hoogwijk, M. & McAloon, A.J. & Hicks, K.B., 2009. "Understanding the reductions in US corn ethanol production costs: An experience curve approach," Energy Policy, Elsevier, vol. 37(1), pages 190-203, January.
    4. Richard G. Newell & Adam B. Jaffe & Robert N. Stavins, 1999. "The Induced Innovation Hypothesis and Energy-Saving Technological Change," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(3), pages 941-975.
    5. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    6. Chen, Xiaoguang & Khanna, Madhu, 2012. "Explaining the reductions in US corn ethanol processing costs: Testing competing hypotheses," Energy Policy, Elsevier, vol. 44(C), pages 153-159.
    7. Söderholm, Patrik & Sundqvist, Thomas, 2007. "Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies," Renewable Energy, Elsevier, vol. 32(15), pages 2559-2578.
    8. Oecd, 2006. "Agricultural Market Impacts of Future Growth in the Production of Biofuels," OECD Papers, OECD Publishing, vol. 6(1), pages 1-57.
    9. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    10. David Popp, 2002. "Induced Innovation and Energy Prices," American Economic Review, American Economic Association, vol. 92(1), pages 160-180, March.
    11. Isoard, Stephane & Soria, Antonio, 2001. "Technical change dynamics: evidence from the emerging renewable energy technologies," Energy Economics, Elsevier, vol. 23(6), pages 619-636, November.
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    More about this item

    Keywords

    Sugarcane ethanol; Production cost reductions; Learning-by-doing; Technological changes;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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