IDEAS home Printed from https://ideas.repec.org/a/oup/ajagec/v71y1989i1p158-166..html
   My bibliography  Save this article

Linear Approximation Using MOTAD and Separable Programming: Should It Be Done?

Author

Listed:
  • Bruce A. McCarl
  • Hayri Önal

Abstract

Linear approximation techniques have often been applied to nonlinear mathematical programming models for computational efficiency reasons. Price-endogenous agricultural sector models and risk models have found numerous applications. This article addresses the issue of approximation efficiency. Based on computational experience with a series of moderate and large-scale sector and risk models, it is concluded that direct nonlinear solution is more efficient than using linear approximations for sector and risk models having objective function nonlinearities. On the other hand, the experimental results indicate that approximation should continue in case of models with nonlinearities in their constraints.

Suggested Citation

  • Bruce A. McCarl & Hayri Önal, 1989. "Linear Approximation Using MOTAD and Separable Programming: Should It Be Done?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(1), pages 158-166.
    • Handle: RePEc:oup:ajagec:v:71:y:1989:i:1:p:158-166.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.2307/1241784
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Rosa, Franco, 2014. "Evaluation of risk in farm planning: a case study," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173126, Italian Association of Agricultural and Applied Economics (AIEAA).
    2. El-Shazly, Fawzy A. & Mansour, Mahmoud E. E. & Ahmed, Mousa A. & Shehata, Emad A., 2009. "التركيب المحصولى المصرى فى ظل المخاطرة والمتغيرات المحلية والدولية [Egyptian Cropping Pattern Under Risk and Varying Domestic and International Circumstances]," MPRA Paper 42634, University Library of Munich, Germany, revised 04 Oct 2009.
    3. L.D. Tamini & M. Doyon & M.M. Zan, 2014. "Investment behavior of Canadian Egg Producers: Analyzing the Impacts of Risk Aversion and Variability of Prices and Costs of Production," Cahiers de recherche CREATE 2014-2, CREATE.
    4. Nieuwoudt, W. L., 1992. "Agricultural Policy Research: Some Thoughts Concerning Methodology And Technology," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 31(01), March.
    5. Apland, Jeffrey & Hauer, Grant, 1993. "Discrete Stochastic Programming: Concepts, Examples And A Review Of Empirical Applications," Staff Papers 13793, University of Minnesota, Department of Applied Economics.
    6. Yang, Wanhong & Khanna, Madhu & Farnsworth, Richard & Onal, Hayri, 2003. "Integrating economic, environmental and GIS modeling to target cost effective land retirement in multiple watersheds," Ecological Economics, Elsevier, vol. 46(2), pages 249-267, September.
    7. Zhang, Jianzhong & Xu, Chengxian, 2010. "Inverse optimization for linearly constrained convex separable programming problems," European Journal of Operational Research, Elsevier, vol. 200(3), pages 671-679, February.
    8. Petrick, Martin & Ditges, C. Markus, 2000. "Risk in agriculture as impediment to rural lending: the case of North-Western Kazakhstan," IAMO Discussion Papers 24, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    9. Franco Rosa & Mario Taverna & Federico Nassivera & Luca Iseppi, 2019. "Farm/crop portfolio simulations under variable risk: a case study from Italy," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 7(1), pages 1-15, December.
    10. Doole, Graeme & Pannell, David J., 2011. "Evaluating environmental policies under uncertainty through application of robust nonlinear programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(4), pages 1-18.
    11. Ridier, Aude & Chaib, Karim & Roussy, Caroline, 2016. "A Dynamic Stochastic Programming model of crop rotation choice to test the adoption of long rotation under price and production risks," European Journal of Operational Research, Elsevier, vol. 252(1), pages 270-279.
    12. Lufumpa, Judith Nanyangwe, 1991. "Determination of optimal crop combinations on Zambian farms: incorporation of certainty and risk considerations in mathematical programming models," ISU General Staff Papers 1991010108000017625, Iowa State University, Department of Economics.
    13. Arata, Linda & Donati, Michele & Sckokai, Paolo & Arfini, Filippo, 2014. "Incorporating risk in a positive mathematical programming framework: a new methodological approach," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182659, European Association of Agricultural Economists.
    14. Ahodo, Kwadjo & Freckleton, Robert P. & Oglethorpe, David, 2015. "Investigation of factors affecting arable farming profit, crop complexity and risk under the single farm payment policy," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204231, Agricultural Economics Society.
    15. Herr, Galen G., 1989. "Two articles employing risk programming techniques to determine optimal enterprise combinations on southern Iowa farms," ISU General Staff Papers 1989010108000017597, Iowa State University, Department of Economics.

    More about this item

    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:oup:ajagec:v:71:y:1989:i:1:p:158-166.. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (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.