IDEAS home Printed from https://ideas.repec.org/p/ags/nddaae/23488.html
   My bibliography  Save this paper

Demand Estimation For Agricultural Processing Co-Products

Author

Listed:
  • Wachenheim, Cheryl J.
  • Novak, Patrick J.
  • DeVuyst, Eric A.
  • Lambert, David K.

Abstract

Co-products of processing agricultural commodities are often marketed through private transaction rather than through public markets or those in which public transaction information is recorded or available. The resulting lack of historical price information prohibits the use of positive time series techniques to estimate demand. Demand estimates for co-products are of value to both livestock producers, who obtain them for use in livestock rations, and processors, who must sell or otherwise dispose of them. Linear programming has long been used, first by researchers and later as a mainstream tool for nutritionists and producers, to formulate least-cost livestock rations. Here it is used as a normative technique to estimate step function demand schedules for co-products by individual livestock classes within a crop-reporting district. Regression is then used to smooth step function demand schedules by fitting demand data to generalized Leontief cost functions. Seemingly unrelated regression is used to estimate factor demand first adjusted for data censoring using probit analysis. Demand by individual livestock classes is aggregated over the number of livestock within a region. Quantities demanded by beef cows for each of the three co-products considered, sugarbeet pulp, wheat middlings, and potato waste, are large relative to other species because of their predominance in the district. At the current price for sugarbeet pulp, quantity demanded by district livestock is low. However quantity demanded is price elastic and becomes much greater at lower prices. Wheat middlings can be an important component of livestock rations, even at higher prices. At a price slightly below the current price, local livestock demand would exhaust the wheat middlings produced at the district's only wheat processing plant. Potato waste is most appropriate for ruminant diets because these animals are able to consume a large quantity of this high moisture feedstuff. Potato waste can be a cost-effective component in beef and dairy rations. Practically, livestock markets for potato waste must be in close proximity to a potato processing plant. Its high moisture content limits the distance it can be economically transported. At current prices, potato waste can be economically included in the ration for beef cows on a farm nearly 100 miles from the processing plant, although storage challenges may restrict use of the feed to closer operations.

Suggested Citation

  • Wachenheim, Cheryl J. & Novak, Patrick J. & DeVuyst, Eric A. & Lambert, David K., 2001. "Demand Estimation For Agricultural Processing Co-Products," Agribusiness & Applied Economics Report 23488, North Dakota State University, Department of Agribusiness and Applied Economics.
  • Handle: RePEc:ags:nddaae:23488
    DOI: 10.22004/ag.econ.23488
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/23488/files/aer453.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.23488?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Konyar, Kazim & Knapp, Keith, 1986. "Demand for Alfalfa Hay in California," Research Reports 251941, University of California, Davis, Giannini Foundation.
    2. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
    3. Ludo Peeters & Yves Surry, 1997. "A Review Of The Arts Of Estimating Price‐Responsiveness Of Feed Demand In The European Union," Journal of Agricultural Economics, Wiley Blackwell, vol. 48(1‐3), pages 379-392, January.
    4. Diewert, W E, 1971. "An Application of the Shephard Duality Theorem: A Generalized Leontief Production Function," Journal of Political Economy, University of Chicago Press, vol. 79(3), pages 481-507, May-June.
    5. Johnson, D. Demcey & Varghese, Beena, 1993. "Estimating Regional Demand for Feed Barley: A Linear-Programming Approach," Agricultural Economics Reports 23127, North Dakota State University, Department of Agribusiness and Applied Economics.
    6. Y. Surry, 1990. "Econometric Modelling Of The European Community Compound Feed Sector: An Application To France," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(3), pages 404-421, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nakakeeto, Gertrude & Chidmi, Benaissa, 2016. "An Almost Ideal Demand Estimation for Seafood in Texas," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230142, Southern Agricultural Economics Association.

    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. Friedrich Schneider & Klaus Salhofer & Erwin Schmid & Gerhard Streicher, 2001. "Was the Austrian agricultural policy least cost efficient?," Economics working papers 2001-03, Department of Economics, Johannes Kepler University Linz, Austria.
    2. Keith R. McLaren & Ou Yang, 2014. "A Class of Demand Systems Satisfying Global Regularity and Having Complete Rank Flexibility," Monash Econometrics and Business Statistics Working Papers 6/14, Monash University, Department of Econometrics and Business Statistics.
    3. Soregaroli, Claudio & Huff, Karen & Meilke, Karl D., 2002. "Demand System Choice Based On Testing The Engel Curve Specification," Working Papers 34139, University of Guelph, Department of Food, Agricultural and Resource Economics.
    4. Ma, Hengyun & Rae, Allan N. & Huang, Jikun, 2004. "Livestock Productivity In China: Data Revision And Total Factor Productivity Decomposition," China Agriculture Project Working Papers 23691, Massey University, Centre for Applied Economics and Policy Studies.
    5. Mardones, Cristian & Alvial, Esteban, 2024. "Evaluation of a carbon tax in Costa Rica linking a demand system focused on energy goods and an input-output model," Applied Energy, Elsevier, vol. 363(C).
    6. Mutuc, Maria Erlinda M. & Rejesus, Roderick M. & Pan, Suwen & Yorobe, Jose M., 2012. "Impact Assessment of Bt Corn Adoption in the Philippines," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(1), pages 117-135, February.
    7. Valentin Zelenyuk, 2023. "Productivity analysis: roots, foundations, trends and perspectives," Journal of Productivity Analysis, Springer, vol. 60(3), pages 229-247, December.
    8. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    9. Abdoul G. Sam & Babatunde O. Abidoye & Sihle Mashaba, 2021. "Climate change and household welfare in sub-Saharan Africa: empirical evidence from Swaziland," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 439-455, April.
    10. Frédéric Reynès, 2011. "The cobb-douglas function as an approximation of other functions," SciencePo Working papers Main hal-01069515, HAL.
    11. Fadhuile, Adelaide & Lemarie, Stephane & Pirotte, Alain, 2011. "Pesticides Uses in Crop Production: What Can We Learn from French Farmers Practices?," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103654, Agricultural and Applied Economics Association.
    12. Cordoba, Jose M. & Hammond, Peter J., 1998. "Asymptotically strategy-proof Walrasian exchange," Mathematical Social Sciences, Elsevier, vol. 36(3), pages 185-212, December.
    13. Geweke, John & Petrella, Lea, 2014. "Likelihood-based inference for regular functions with fractional polynomial approximations," Journal of Econometrics, Elsevier, vol. 183(1), pages 22-30.
    14. Elena Lasarte Navamuel & Fernando Rubiera Moroll & Dusan Paredes, 2014. "City size and household food consumption: demand elasticities in Spain," Applied Economics, Taylor & Francis Journals, vol. 46(14), pages 1624-1641, May.
    15. LOFGREN Asa & MILLOCK Katrin & NAUGES Céline, 2007. "Using Ex Post Data to Estimate the Hurdle Rate of Abatement Investments - An application to the Swedish Pulp and Paper Industry and Energy Sector," LERNA Working Papers 07.06.227, LERNA, University of Toulouse.
    16. Chatura Sewwandi Wijetunga, 2016. "Rice production structures in Sri Lanka: The normalized translog profit function approach," Asian Journal of Agriculture and rural Development, Asian Economic and Social Society, vol. 6(2), pages 21-35, February.
    17. Chantal Le Mouël, 1992. "Import tariffs, domestic distortions and "market linkages"," Working Papers hal-01959660, HAL.
    18. Barnett, William A. & Serletis, Apostolos, 2008. "The Differential Approach to Demand Analysis and the Rotterdam Model," MPRA Paper 12319, University Library of Munich, Germany.
    19. Zhang, Wei & Alston, Julian M., 2013. "Factor Substitution and Technical Change in the U.S. Dairy Processing and Manufacturing Industry," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150707, Agricultural and Applied Economics Association.
    20. Binswanger, Hans P., 1972. "The Measurement Of Biased Technical Change In The Many Factors Case: U.S. And Japanese Agriculture," Staff Papers 13786, University of Minnesota, Department of Applied Economics.

    More about this item

    Keywords

    Agribusiness;

    Statistics

    Access and download statistics

    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:nddaae:23488. 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/dandsus.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.