IDEAS home Printed from https://ideas.repec.org/p/ags/aaea15/205818.html
   My bibliography  Save this paper

The Biomass Crop Assistance Program: Critical, Notional, or Distortional Support for Cellulosic Biofuels?

Author

Listed:
  • Miao, Ruiqing
  • Khanna, Madhu

Abstract

This study intends to quantify the impacts of the Biomass Crop Assistance Program (BCAP) on biomass production and on land use. With a focus on corn, corn stover, soybeans, miscanthus, and switchgrass, we investigate farmers’ optimal land allocation among these five crops or biomass feedstock across 1,836 counties in the rain-fed area of the United States under various assumptions about farmers’ time and risk preferences as well as credit constraint status. The results show that under its current budget ($125 million within five years), BCAP only has a moderate effect on incentivizing biomass production (up to 4.8 million metric tons per year). BCAP’s impact on biomass production first increases then decreases in biomass price. The impact peaks when biomass price is $30 to $40 per metric ton. We also find that BCAP incentivizes biomass production on low quality land much more than production on high quality land. The geographical distribution of BCAP payments and of land use change caused by BCAP is studied as well.

Suggested Citation

  • Miao, Ruiqing & Khanna, Madhu, 2015. "The Biomass Crop Assistance Program: Critical, Notional, or Distortional Support for Cellulosic Biofuels?," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205818, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea15:205818
    DOI: 10.22004/ag.econ.205818
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/205818/files/Miao_Khanna_BCAP_AAEA2015.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.205818?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Xiaodong Du & David A. Hennessy, 2012. "The planting real option in cash rent valuation," Applied Economics, Taylor & Francis Journals, vol. 44(6), pages 765-776, February.
    2. Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
    3. Zhu, Ying & Ghosh, Sujit K. & Goodwin, Barry K., 2008. "Modeling Dependence in the Design of Whole Farm---A Copula-Based Model Approach," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6282, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohit Anand & Ruiqing Miao & Madhu Khanna, 2019. "Adopting bioenergy crops: Does farmers’ attitude toward loss matter?," Agricultural Economics, International Association of Agricultural Economists, vol. 50(4), pages 435-450, July.
    2. Feng, Xiaoguang & Hayes, Dermot J., 2014. "Is Government Involvement Really Necessary: Implications for Systemic Risk and Crop Reinsurance Contracts," ISU General Staff Papers 201410010700001002, Iowa State University, Department of Economics.
    3. Miao, Ruiqing & Khanna, Madhu, 2017. "Costs of meeting a cellulosic biofuel mandate with perennial energy crops: Implications for policy," Energy Economics, Elsevier, vol. 64(C), pages 321-334.
    4. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Hamza, Taher & Ben Haj Hamida, Hayet & Mili, Mehdi & Sami, Mina, 2024. "High inflation during Russia–Ukraine war and financial market interaction: Evidence from C-Vine Copula and SETAR models," Research in International Business and Finance, Elsevier, vol. 70(PB).
    6. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    7. Miao, Ruiqing & Hennessy, David A. & Feng, Hongli, 2016. "The Effects of Crop Insurance Subsidies and Sodsaver on Land-Use Change," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    8. Wang, Mengjiao & Liu, Jianxu & Yang, Bing, 2024. "Does the strength of the US dollar affect the interdependence among currency exchange rates of RCEP and CPTPP countries?," Finance Research Letters, Elsevier, vol. 62(PA).
    9. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    10. Kojadinovic, Ivan & Yan, Jun, 2010. "Comparison of three semiparametric methods for estimating dependence parameters in copula models," Insurance: Mathematics and Economics, Elsevier, vol. 47(1), pages 52-63, August.
    11. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    12. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    13. Corduas, Marcella, 2015. "A statistical model for consumer preferences: the case of Italian extra virgin olive oil," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202701, European Association of Agricultural Economists.
    14. Guillermo Martínez-Flórez & Artur J. Lemonte & Germán Moreno-Arenas & Roger Tovar-Falón, 2022. "The Bivariate Unit-Sinh-Normal Distribution and Its Related Regression Model," Mathematics, MDPI, vol. 10(17), pages 1-26, August.
    15. Nasreldin, Osama Ahmed & Devesa, Teresa Serra, 2014. "Price volatility of food staples. The case of millet in Niger," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182728, European Association of Agricultural Economists.
    16. Rémillard, Bruno & Scaillet, Olivier, 2009. "Testing for equality between two copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 377-386, March.
    17. Bouezmarni, T. & Rombouts, J.V.K., 2009. "Semiparametric multivariate density estimation for positive data using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2040-2054, April.
    18. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    19. Wanling Huang & Artem Prokhorov, 2014. "A Goodness-of-fit Test for Copulas," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 751-771, October.
    20. Majeed, Fahd & Khanna, Madhu & Miao, Ruiqing & Betes, Elena Blanc & Hudiburg, Tara & DeLucia, Evan, 2022. "Payment for carbon mitigation reduces riskiness of bioenergy crop production," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322277, Agricultural and Applied Economics Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea15:205818. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.