IDEAS home Printed from https://ideas.repec.org/p/ags/motrdp/29234.html
   My bibliography  Save this paper

Econometric-Process Models For Integrated Assessment Of Agricultural Production Systems

Author

Listed:
  • Antle, John M.
  • Capalbo, Susan Marie

Abstract

This paper develops the conceptual and empirical basis for a class of empirical economic production models that can be linked to site-specific bio-physical models for use in integrated assessment research. Site-specific data are used to estimate econometric production models, and these data and models are then incorporated into a simulation model that represents the decision making process of the farmer as a sequence of discrete or continuous land use and input use decisions. This discrete/continuous structure of the econometric process model is able to simulate decision making both within and outside the range of observed data in a way that is consistent with economic theory and with site-specific bio-physical constraints and processes. An econometric-process model of the dryland grain production system of the Northern Plains demonstrates the capabilities of this type of model.

Suggested Citation

  • Antle, John M. & Capalbo, Susan Marie, 2000. "Econometric-Process Models For Integrated Assessment Of Agricultural Production Systems," Research Discussion Papers 29234, Montana State University, Department of Agricultural Economics and Economics, Trade Research Center.
  • Handle: RePEc:ags:motrdp:29234
    as

    Download full text from publisher

    File URL: http://ageconsearch.umn.edu/record/29234/files/rdp40.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Just, Richard E & Antle, John M, 1990. "Interactions between Agricultural and Environmental Policies: A Conceptual Framework," American Economic Review, American Economic Association, vol. 80(2), pages 197-202, May.
    2. John M. Antle & Susan M. Capalbo, 2001. "Econometric-Process Models for Integrated Assessment of Agricultural Production Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 389-401.
    3. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    4. de Janvry, Alain & Fafchamps, M. & Sadoulet, Elisabeth, 1991. "Peasant Household Behavior with Missing Markets: Some Paradoxes Explain," CUDARE Working Papers 198579, University of California, Berkeley, Department of Agricultural and Resource Economics.
    5. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-771, September.
    6. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275, October.
    7. Robert K. Kaufmann & Seth E. Snell, 1997. "A Biophysical Model of Corn Yield: Integrating Climatic and Social Determinants," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 178-190.
    8. Richard E. Just & David Zilberman & Eithan Hochman, 1983. "Estimation of Multicrop Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(4), pages 770-780.
    9. Banerjee, Anurag N. & Magnus, Jan R., 2000. "On the sensitivity of the usual t- and F-tests to covariance misspecification," Journal of Econometrics, Elsevier, vol. 95(1), pages 157-176, March.
    10. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
    11. Beach, Robert H. & Thomson, Allison M. & McCarl, Bruce A., 2010. "Climate Change Impacts On Us Agriculture," 2010: Climate Change in World Agriculture: Mitigation, Adaptation, Trade and Food Security, June 2010, Stuttgart-Hohenheim, Germany 91393, International Agricultural Trade Research Consortium.
    12. Antle, John M. & Capalbo, Susan M. & Johnson, James B. & Miljkovic, Dragan, 1999. "The Kyoto Protocol: Economic Effects of Energy Prices on Northern Plains Dryland Grain Production," Agricultural and Resource Economics Review, Cambridge University Press, vol. 28(01), pages 96-105, April.
    13. Prato, Anthony A. & Fulcher, Christopher L. & Wu, Shunxiang & Ma, Jian, 1996. "Multiple-Objective Decision Making For Agroecosystem Management," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 0(Number 2), pages 1-13, October.
    14. Ian W. Hardie & Peter J. Parks, 1997. "Land Use with Heterogeneous Land Quality: An Application of an Area Base Model," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 299-310.
    15. Antle, John M. & Capalbo, Susan Marie & Mooney, Sian & Elliott, Edward T. & Paustian, Keith H., 2000. "Economics Of Agricultural Soil Carbon Sequestration In The Northern Plains," Research Discussion Papers 29239, Montana State University, Department of Agricultural Economics and Economics, Trade Research Center.
    16. Antle, John M. & Capalbo, Susan Marie & Crissman, Charles C., 1994. "Econometric Production Models With Endogenous Input Timing: An Application To Ecuadorian Potato Production," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 1), pages 1-18, July.
    17. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Production Economics;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation

    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:motrdp:29234. See general information about how to correct material in RePEc.

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

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.