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The Value Of Enso Information To Agriculture: Consideration Of Event Strength And Trade

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  • Chen, Chi-Chung
  • McCarl, Bruce A.

Abstract

The agricultural value of El Nino-Southern Oscillation (ENSO) phase knowledge is measured in a value-of-information framework using economic models. We examine the value of considering the full distribution of ENSO phase strength effects as opposed to average ENSO phase strength effects, as well as the implications of considering ENSO impacts on the rest of the world (ROW). A stochastic U.S. agricultural sector model linked with a global trade model is used to assess the value of ENSO phase information. When the full distribution of ENSO phase strength is considered, the value of phase information increases twofold with respect to the average ENSO effects.

Suggested Citation

  • Chen, Chi-Chung & McCarl, Bruce A., 2000. "The Value Of Enso Information To Agriculture: Consideration Of Event Strength And Trade," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-18, December.
    • Handle: RePEc:ags:jlaare:30887
    DOI: 10.22004/ag.econ.30887
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    References listed on IDEAS

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    Cited by:

    1. Lan-Fen Chu & Michael McAleer & Chi-Chung Chen, 2012. "How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?," Journal of Reviews on Global Economics, Lifescience Global, vol. 1, pages 1-12.
    2. Elizabeth Kopits & Alex L. Marten & Ann Wolverton, 2013. "Moving Forward with Incorporating "Catastrophic" Climate Change into Policy Analysis," NCEE Working Paper Series 201301, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Jan 2013.
    3. Uwe A. Schneider & Bruce A. McCarl, 2006. "Appraising agricultural greenhouse gas mitigation potentials: effects of alternative assumptions," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 277-287, November.
    4. Schneider, Uwe A. & McCarl, Bruce A., 2005. "Implications of a Carbon-Based Energy Tax for U.S. Agriculture," Agricultural and Resource Economics Review, Cambridge University Press, vol. 34(2), pages 265-279, October.
    5. Kung, Chih-Chun, 2019. "A stochastic evaluation of economic and environmental effects of Taiwan's biofuel development under climate change," Energy, Elsevier, vol. 167(C), pages 1051-1064.
    6. Yaling Li & Fujin Yi & Yanjun Wang & Richard Gudaj, 2019. "The Value of El Niño-Southern Oscillation Forecasts to China’s Agriculture," Sustainability, MDPI, vol. 11(15), pages 1-23, August.
    7. Elbakidze, Levan & McCarl, Bruce A., 2006. "Animal Disease Pre-Event Preparedness versus Post-Event Response: When Is It Economic to Protect?," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 38(2), pages 327-336, August.
    8. Massimo Peri, 2017. "Climate variability and the volatility of global maize and soybean prices," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(4), pages 673-683, August.
    9. Kung, Chih-Chun & Wu, Tao, 2021. "Influence of water allocation on bioenergy production under climate change: A stochastic mathematical programming approach," Energy, Elsevier, vol. 231(C).
    10. Zhu, Yichen & Ghoshray, Atanu, 2021. "Climate Anomalies and Its Impact on U.S. Corn and Soybean Prices," 2021 Conference, August 17-31, 2021, Virtual 315271, International Association of Agricultural Economists.
    11. Davinson Stev Abril‐Salcedo & Luis Fernando Melo‐Velandia & Daniel Parra‐Amado, 2020. "Nonlinear relationship between the weather phenomenon El niño and Colombian food prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1059-1086, October.
    12. Kung, Chih-Chun & Zhang, Ning & Choi, Yongrok & Xiong, Kai & Yu, Jiangli, 2019. "Effectiveness of crop residuals in ethanol and pyrolysis-based electricity production: A stochastic analysis under uncertain climate impacts," Energy Policy, Elsevier, vol. 125(C), pages 267-276.
    13. 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.
    14. Chi-Chung Chen & Bruce McCarl & Ching-Cheng Chang, 2012. "Climate change, sea level rise and rice: global market implications," Climatic Change, Springer, vol. 110(3), pages 543-560, February.
    15. Heng-Chi Lee & Bruce McCarl & Uwe Schneider & Chi-Chung Chen, 2007. "Leakage and Comparative Advantage Implications of Agricultural Participation in Greenhouse Gas Emission Mitigation," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 12(4), pages 471-494, May.
    16. Villoria, Nelson B. & Delgado, Michael, 2017. "Worldwide Crop Supply Responses to El Niño Southern Oscillation," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258564, Agricultural and Applied Economics Association.
    17. 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).
    18. Rubas, Debra J. & Mjelde, James W. & Love, H. Alan, 2003. "Wheat Trade And The Adoption Of Enso-Based Forecasts: Different Scenarios," 2003 Annual meeting, July 27-30, Montreal, Canada 22160, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Chu, L. & McAleer, M.J. & Chen, C-C., 2009. "How Volatile is ENSO?," Econometric Institute Research Papers EI 2009-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Ubilava, David & Orlowski, Jan, 2016. "The Predictive Content of Climate Anomalies for Agricultural Production: Does ENSO Really Matter?," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236281, Agricultural and Applied Economics Association.
    21. Peri, Massimo, 2015. "Cliamte Variability and Agricultural Price volatility: the case of corn and soybeans," 2015 Conference, August 9-14, 2015, Milan, Italy 212623, International Association of Agricultural Economists.
    22. 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.
    23. 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.

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