IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/70911.html

Global End-Use Demand for Cotton: A Time-Varying Parameter Model

Author

Listed:
  • MacDonald, Stephen

Abstract

A Cooley-Prescott model is used to estimate trends in income and price response of end-use demand for cotton in developed countries. By comparing trends in parameter variation between different groups of developed countries it is possible to develop hypotheses regarding the varying impact of product promotion and structural change between regions.

Suggested Citation

  • MacDonald, Stephen, 1997. "Global End-Use Demand for Cotton: A Time-Varying Parameter Model," MPRA Paper 70911, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:70911
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/70911/1/MPRA_paper_70911.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Capps Jr., Oral & Bessler, David A. & Davis, George C. & Nichols, John P., 1996. "Economic Evaluation of the Cotton Checkoff Program," Economic Evaluation of Commodity Promotion Programs in the Current Legal and Political Environment, October 7-8, 1996, Monterey, California 279664, Regional Research Projects > NECC-63: Research Committee on Commodity Promotion.
    2. Zhang, Ping & Fletcher, Stanley M. & Ethridge, Don E., 1994. "Interfiber Competition in Textile Mills Over Time," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 26(1), pages 173-182, July.
    3. Parrott, Scott D. & McIntosh, Christopher S., 1996. "Nonconstant Price Expectations and Acreage Response: The Case of Cotton Production in Georgia," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 28(1), pages 203-210, July.
    4. Julian M. Alston & James A. Chalfant, 1991. "Unstable Models from Incorrect Forms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(4), pages 1171-1181.
    5. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-184, January.
    6. Zhang, Ping & Fletcher, Stanley M. & Ethridge, Don E., 1994. "Interfiber Competition In Textile Mills Over Time," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 26(01), pages 1-10, July.
    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. Marseli, Oussama & Epperson, James E., 2002. "An Analysis Of Domestic And Export Demand For U.S. Cotton," Faculty Series 16709, University of Georgia, Department of Agricultural and Applied Economics.

    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. Kym Anderson & Ernesto Valenzuela & Lee Ann Jackson, 2008. "Recent and Prospective Adoption of Genetically Modified Cotton: A Global Computable General Equilibrium Analysis of Economic Impacts," Economic Development and Cultural Change, University of Chicago Press, vol. 56(2), pages 265-296, January.
    2. Kym Anderson & Ernesto Valenzuela & Lee Ann Jackson, 2007. "Recent and Prospective Adoption of Genetically Modified Cotton: A Global CGE Analysis of Economic Impacts," Centre for International Economic Studies Working Papers 2007-07, University of Adelaide, Centre for International Economic Studies.
    3. Stephen Macdonald & Suwen Pan & Darren Hudson & Francis Tuan, 2014. "Toward a consumer economy in China: implications of changing wage policies for U.S. cotton exports," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 513-524, July.
    4. Tribble, Camille M. & Mcintosh, Christopher S. & Wetzstein, Michael E., 1999. "Georgia Cotton Acreage Response to the Boll Weevil Eradication Program," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 31(3), pages 499-506, December.
    5. Olawale Awe O. & Adedayo Adepoju A., 2018. "Modified Recursive Bayesian Algorithm For Estimating Time-Varying Parameters In Dynamic Linear Models," Statistics in Transition New Series, Statistics Poland, vol. 19(2), pages 258-293, June.
    6. Marfatia, Hardik A., 2015. "Monetary policy's time-varying impact on the US bond markets: Role of financial stress and risks," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 103-123.
    7. Mandler, Martin, 2007. "The Taylor rule and interest rate uncertainty in the U.S. 1955-2006," MPRA Paper 2340, University Library of Munich, Germany.
    8. Jean‐Pascal Bassino & Jean‐Pierre Dormois, 2010. "Rainfall, The Méline Tariff, And Wheat Production In Mediterranean France, 1885–1914," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 50(1), pages 23-38, March.
    9. Min, Chung-ki, 1998. "A Gibbs sampling approach to estimation and prediction of time-varying-parameter models," Computational Statistics & Data Analysis, Elsevier, vol. 27(2), pages 171-194, April.
    10. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    11. N. Groenewold & P. Fraser, 1999. "Forecasting Beta: How well does the 'five year rule of thumb' do?," Economics Discussion / Working Papers 99-01, The University of Western Australia, Department of Economics.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    13. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    14. repec:spo:wpmain:info:hdl:2441/1461 is not listed on IDEAS
    15. Mooney, Sian & Antle, John M. & Capalbo, Susan Marie & Paustian, Keith H., 2003. "Incorporating Uncertainty In Integrated Assessment Modeling," 2003 Annual meeting, July 27-30, Montreal, Canada 22225, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    17. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137, National Bureau of Economic Research, Inc.
    18. Aurélien Goutsmedt & Erich Pinzon-Fuchs & Matthieu Renault & Francesco Sergi, 2015. "Criticizing the Lucas Critique: Macroeconometricians' Response to Robert Lucas," Post-Print halshs-01179114, HAL.
    19. San Miguel, Fernando & Ryan, Mandy & Scott, Anthony, 2002. "Are preferences stable? The case of health care," Journal of Economic Behavior & Organization, Elsevier, vol. 48(1), pages 1-14, May.
    20. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    21. Raimundo Soto, "undated". "Nonlinearities in the Demand for money: A Neural Network Approach," ILADES-UAH Working Papers inv107, Universidad Alberto Hurtado/School of Economics and Business.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

    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:pra:mprapa:70911. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.