IDEAS home Printed from https://ideas.repec.org/p/ags/nzar13/160199.html

Decadal Climate Variability: Economic Implications In Agriculture And Water In The Missouri River Basin

Author

Listed:
  • Fernandez, Mario Andres

Abstract

Economic research on decadal climate variability (DCV) is scarce. DCV refers to ocean-related climate influences of duration from seven to twenty years. The DCV phenomena and their phases are associated with variations in crop and water yields. This paper examines the value of DCV information in the Missouri river basin using a mathematical programming model. The analysis shows the value of a perfect forecast is about 5.2 billion dollars, though 86% of this value can be obtained by a less perfect forecast based on already available data. Results show differential responses in major crops acreage and water usage.

Suggested Citation

  • Fernandez, Mario Andres, 2013. "Decadal Climate Variability: Economic Implications In Agriculture And Water In The Missouri River Basin," 2013 Conference, August 28-30, 2013, Christchurch, New Zealand 160199, New Zealand Agricultural and Resource Economics Society.
    • Handle: RePEc:ags:nzar13:160199
    DOI: 10.22004/ag.econ.160199
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/160199/files/Fernandez%202013%20final.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.160199?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. Chi‐Chung Chen & Ching‐Cheng Chang, 2005. "The impact of weather on crop yield distribution in Taiwan: some new evidence from panel data models and implications for crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 33(s3), pages 503-511, November.
    2. Hayri Önal & Bruce A. McCarl, 1991. "Exact Aggregation in Mathematical Programming Sector Models," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 39(2), pages 319-334, July.
    3. Emilio Cerdá Tena & Sonia Quiroga Gómez, 2011. "Economic value of weather forecasting: the role of risk aversion," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 130-149, July.
    4. W. Botzen & J. Bergh & L. Bouwer, 2010. "Climate change and increased risk for the insurance sector: a global perspective and an assessment for the Netherlands," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 52(3), pages 577-598, March.
    5. Hansen, James W., 2002. "Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges," Agricultural Systems, Elsevier, vol. 74(3), pages 309-330, December.
    6. Hill, Harvey S.J. & Mjelde, James W., 2002. "Challenges and Opportunities Provided by Seasonal Climate Forecasts: A Literature Review," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 34(3), pages 603-632, December.
    7. Richard M. Adams & Kelly J. Bryant & Bruce A. Mccarl & David M. Legler & James O'Brien & Andrew Solow & Rodney Weiher, 1995. "Value Of Improved Long‐Range Weather Information," Contemporary Economic Policy, Western Economic Association International, vol. 13(3), pages 10-19, July.
    8. Daniel Fajardo & Bruce A. McCarl & Robert L. Thompson, 1981. "A Multicommodity Analysis of Trade Policy Effects: The Case of Nicaraguan Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 63(1), pages 23-31.
    9. Hill, Harvey S.J. & Mjelde, James W., 2002. "Challenges And Opportunities Provided By Seasonal Climate Forecasts: A Literature Review," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 34(3), pages 1-30, December.
    10. Bruce A. McCarl, 1982. "Cropping Activities in Agricultural Sector Models: A Methodological Proposal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 64(4), pages 768-772.
    11. David R. Bell & Ronald C. Griffin, 2011. "Urban Water Demand with Periodic Error Correction," Land Economics, University of Wisconsin Press, vol. 87(3), pages 528-544.
    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. Mario Andres Fernandez & Pei Huang & Bruce McCarl & Vikram Mehta, 2016. "Value of decadal climate variability information for agriculture in the Missouri River basin," Climatic Change, Springer, vol. 139(3), pages 517-533, December.
    2. Huang, Pei & McCarl, Bruce A., 2014. "Estimating Decadal Climate Variability Effects on Crop Yields: A Bayesian Hierarchical Approach," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169828, Agricultural and Applied 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. McCarl, Bruce A., 1992. "Mathematical Programming For Resource Policy Appraisal Under Multiple Objectives," Working Papers 11888, Environmental and Natural Resources Policy Training Project.
    2. Ashley R. Coles & Christopher A. Scott, 2009. "Vulnerability and adaptation to climate change and variability in semi‐arid rural southeastern Arizona, USA," Natural Resources Forum, Blackwell Publishing, vol. 33(4), pages 297-309, November.
    3. Schmid, Erwin & Sinabell, Franz, 2005. "Using the Positive Mathematical Programming Method to Calibrate Linear Programming Models," Discussion Papers DP-10-2005, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    4. Attwood, J. D. & McCarl, B. & Chen, Chi-Chung & Eddleman, B. R. & Nayda, B. & Srinivasan, R., 2000. "Assessing regional impacts of change: linking economic and environmental models," Agricultural Systems, Elsevier, vol. 63(3), pages 147-159, March.
    5. Choi, Hyung Sik & Schneider, Uwe A. & Rasche, Livia & Cui, Junbo & Schmid, Erwin & Held, Hermann, 2015. "Potential effects of perfect seasonal climate forecasting on agricultural markets, welfare and land use: A case study of Spain," Agricultural Systems, Elsevier, vol. 133(C), pages 177-189.
    6. Rebecca Darbyshire & Jason Crean & Michael Cashen & Muhuddin Rajin Anwar & Kim M Broadfoot & Marja Simpson & David H Cobon & Christa Pudmenzky & Louis Kouadio & Shreevatsa Kodur, 2020. "Insights into the value of seasonal climate forecasts to agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1034-1058, October.
    7. Kooten, G. Cornelis van, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 149182, University of Victoria, Resource Economics and Policy.
    8. Onal, Hayri & Chen, Xiaoguang & Khanna, Madhu & Huang, Haixiao, 2009. "Mathematical Programming Modeling of Agricultural Supply Response," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49469, Agricultural and Applied Economics Association.
    9. Franz Sinabell & Martin Schönhart & Erwin Schmid, 2015. "Austrian Agriculture 2010-2050. Quantitative Effects of Climate Change Mitigation Measures – An Analysis of the Scenarios WEM, WAM and a Sensitivity Analysis of the Scenario WEM," WIFO Studies, WIFO, number 58400, June.
    10. Zaatra, Abderraouf & Kleftodimos, Georgios & Requier-Desjardins, Mélanie & Belhouchette, Hatem, 2025. "Economic valuation of groundwater over-exploitation in the Maghreb," Ecological Economics, Elsevier, vol. 230(C).
    11. Das, Prantika & Gundimeda, Haripriya, 2021. "Economic Evaluation of Achieving Biofuel Mandate through Advanced Biofuels in Developing Country: Case of India," 2021 Conference, August 17-31, 2021, Virtual 315355, International Association of Agricultural Economists.
    12. Farkas, Hannah & Linsenmeier, Manuel & Talevi, Marta & Avner, Paolo & Jafino, Bramka Arga & Sidibe, Moussa, 2025. "The Economic Value of Weather Forecasts : A Quantitative Systematic Literature Review," Policy Research Working Paper Series 11213, The World Bank.
    13. Aillery, Marcel P. & et al. [+7], 1996. "Salmon Recovery in the Pacific Northwest: Agricultural and other Economic Effects," Agricultural Economic Reports 308431, United States Department of Agriculture, Economic Research Service.
    14. Xuan Liu & Gerrit Cornelis van Kooten & Jun Duan, 2020. "Calibration of agricultural risk programming models using positive mathematical programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), pages 795-817, July.
    15. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2014. "Modelling Bi-lateral Forest Product Trade Flows: Experiencing Vertical and Horizontal Chain Optimization," Working Papers 197898, University of Victoria, Resource Economics and Policy.
    16. Frahan, Bruno Henry de, 2005. "PMP, Extensions and Alternative Methods: Introductory Review of the State of the Art," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24537, European Association of Agricultural Economists.
    17. Howitt, Richard E. & Mean, Phillippe, 1983. "A Positive Approach to Microeconomic Programming Models," Working Papers 225710, University of California, Davis, Department of Agricultural and Resource Economics.
    18. Nuñez, Hector M., 2016. "Biofuel Potential in Mexico: Land Use, Economic and Environmental Effects," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236067, Agricultural and Applied Economics Association.
    19. repec:phd:pjdevt:pjd_2009_vol__xxxvi_no__1-c is not listed on IDEAS
    20. Kung, Chih-Chun & Cao, Xiaoyong & Choi, Yongrok & Kung, Shan-Shan, 2019. "A stochastic analysis of cropland utilization and resource allocation under climate change," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    21. Schmid, Erwin & Sinabell, Franz, 2005. "Evaluation Of Decoupling Scenarios in a Rural Development Context: Results for Austria," 89th Seminar, February 2-5, 2005, Parma, Italy 239278, European Association of Agricultural Economists.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nzar13:160199. 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/nzareea.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.