IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v121y2013i4p689-700.html
   My bibliography  Save this article

The effect of El Niño Southern Oscillation on U.S. corn production and downside risk

Author

Listed:
  • Jesse Tack
  • David Ubilava

Abstract

ENSO teleconnections imply anomalous weather conditions, causing yield shortages, price fluctuations, and civil unrest. We estimate ENSO’s effect on U.S. county-level corn yield distributions and find that temperature and precipitation alone are not sufficient to summarize the effect of global climate on agriculture. We find that acreage-weighted aggregate impacts mask considerable spatial heterogeneity at the county-level for the mean, variance, and downside risk of corn yields. Impacts for mean yields range from − 24 to 33 % for El Niño and − 25 to 36 % for La Niña, with the geographical center of losses shifting from the Eastern to Western corn belt. ENSO’s effect on the variance of crop yields is highly localized and is not representative of a variance-preserving shift. We also find that downside risk impacts are large and spatially correlated across counties. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, vol. 121(4), pages 689-700, December.
    • Handle: RePEc:spr:climat:v:121:y:2013:i:4:p:689-700
    DOI: 10.1007/s10584-013-0918-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10584-013-0918-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10584-013-0918-x?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
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Paul Gallagher, 1987. "U.S. Soybean Yields: Estimation and Forecasting with Nonsymmetric Disturbances," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(4), pages 796-803.
    2. Gallagher, Paul W., 1987. "U.S. Soybean Yields: Estimation and Forecasting with Non-Symmetric Disturbances," Staff General Research Papers Archive 10779, Iowa State University, Department of Economics.
    3. Bruce J. Sherrick & Fabio C. Zanini & Gary D. Schnitkey & Scott H. Irwin, 2004. "Crop Insurance Valuation under Alternative Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 406-419.
    4. David A. Hennessy, 2009. "Crop Yield Skewness Under Law of the Minimum Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 197-208.
    5. Moschini, Giancarlo & Hennessy, David A., 2001. "Uncertainty, risk aversion, and risk management for agricultural producers," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 2, pages 88-153, Elsevier.
    6. Hennessy, David A., 2009. "Crop Yield Skewness and the Normal Distribution," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-19, April.
    7. Xiaodong Du & David A. Hennessy & Cindy L. Yu, 2012. "Testing Day's Conjecture that More Nitrogen Decreases Crop Yield Skewness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 225-237.
    8. Chavas, Jean-Paul & Holt, Matthew T, 1996. "Economic Behavior under Uncertainty: A Joint Analysis of Risk Preferences and Technology," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 329-335, May.
    9. Yongxin Zhang & Yun Qian & Valérie Dulière & Eric Salathé & L. Leung, 2012. "ENSO anomalies over the Western United States: present and future patterns in regional climate simulations," Climatic Change, Springer, vol. 110(1), pages 315-346, January.
    10. Ubilava, David & holt, Matt, 2013. "El Ni~no southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 1-25.
    11. Martin Wittenberg, 2010. "An introduction to maximum entropy and minimum cross-entropy estimation using Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 315-330, September.
    12. Hall, Anthony D. & Skalin, Joakim & Teräsvirta, Timo, 1998. "A nonlinear time series model of El Niño," SSE/EFI Working Paper Series in Economics and Finance 263, Stockholm School of Economics.
    13. Barry K. Goodwin, 2001. "Problems with Market Insurance in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 643-649.
    14. Alan P. Ker & Keith Coble, 2003. "Modeling Conditional Yield Densities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 291-304.
    15. Charles B. Moss & J. S. Shonkwiler, 1993. "Estimating Yield Distributions with a Stochastic Trend and Nonnormal Errors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1056-1062.
    16. Ardian Harri & Keith H. Coble & Alan P. Ker & Barry J. Goodwin, 2011. "Relaxing Heteroscedasticity Assumptions in Area-Yield Crop Insurance Rating," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 703-713.
    17. 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.
    18. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    19. Allan D. Brunner, 2002. "El Niño and World Primary Commodity Prices: Warm Water or Hot Air?," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 176-183, February.
    20. Denis Nadolnyak & Dmitry Vedenov & James Novak, 2008. "Information Value of Climate-Based Yield Forecasts in Selecting Optimal Crop Insurance Coverage," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(5), pages 1248-1255.
    21. john M. Antle, 2010. "Asymmetry, Partial Moments, and Production Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1294-1309.
    22. Jesse Tack & Ardian Harri & Keith Coble, 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1037-1054.
    23. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    24. Salvatore Di Falco & Jean-Paul Chavas, 2006. "Crop genetic diversity, farm productivity and the management of environmental risk in rainfed agriculture," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 33(3), pages 289-314, September.
    25. Carl H. Nelson & Paul V. Preckel, 1989. "The Conditional Beta Distribution as a Stochastic Production Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 370-378.
    26. Dalton, Michael G., 2001. "El Nino, Expectations, and Fishing Effort in Monterey Bay, California," Journal of Environmental Economics and Management, Elsevier, vol. 42(3), pages 336-359, November.
    27. Kelly, David L. & Kolstad, Charles D. & Mitchell, Glenn T., 2005. "Adjustment costs from environmental change," Journal of Environmental Economics and Management, Elsevier, vol. 50(3), pages 468-495, November.
    28. Bellemare, Marc F., 2011. "Rising food prices, food price volatility, and political unrest," MPRA Paper 31888, University Library of Munich, Germany.
    29. Salvatore Di Falco & Jean-Paul Chavas, 2007. "On Crop Biodiversity, Risk Exposure, and Food Security in the Highlands of Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(3), pages 599-611.
    30. Samuel Bazzi, Christopher Blattman, 2011. "Economic Shocks and Conflict: The (Absence of?) Evidence from Commodity Price- Working Paper 274," Working Papers 274, Center for Global Development.
    31. Solomon M. Hsiang & Kyle C. Meng & Mark A. Cane, 2011. "Civil conflicts are associated with the global climate," Nature, Nature, vol. 476(7361), pages 438-441, August.
    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. 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.
    2. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    3. Andrea Bastianin & Alessandro Lanza & Matteo Manera, 2018. "Economic impacts of El Niño southern oscillation: evidence from the Colombian coffee market," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 623-633, September.
    4. 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.
    5. Hildegart Ahumada & Magdalena Cornejo, 2019. "How econometrics can help us understand the effects of climate change on crop yields: the case of soybeans," School of Government Working Papers wp_gob_2019_2, Universidad Torcuato Di Tella.
    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. Sinha Roy,Sutirtha & Van Der Weide,Roy, 2022. "Poverty in India Has Declined over the Last Decade But Not As Much As Previously Thought," Policy Research Working Paper Series 9994, The World Bank.
    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. Hildegart Ahumada & Magdalena Cornejo, 2019. "How econometrics can help us understand the effects of climate change on crop yields: the case of soybeans," School of Government Working Papers 201902, Universidad Torcuato Di Tella.
    10. A. Ford Ramsey & Barry K. Goodwin, 2019. "Value-at-Risk and Models of Dependence in the U.S. Federal Crop Insurance Program," JRFM, MDPI, vol. 12(2), pages 1-21, April.
    11. 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.
    12. Jesse Tack & Andrew Barkley & Lawton Nalley, 2014. "Heterogeneous effects of warming and drought on selected wheat variety yields," Climatic Change, Springer, vol. 125(3), pages 489-500, August.
    13. Patalee, M.A. Buddhika & Tonsor, Glynn T., 2021. "Impact of weather on cow-calf industry locations and production in the United States," Agricultural Systems, Elsevier, vol. 193(C).
    14. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    15. Jesse Tack & Keith Coble & Barry Barnett, 2018. "Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 635-647, September.

    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. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    2. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.
    3. Jesse Tack & Ardian Harri & Keith Coble, 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1037-1054.
    4. Yu, Tian, 2011. "Three essays on weather and crop yield," ISU General Staff Papers 201101010800002976, Iowa State University, Department of Economics.
    5. Agarwal, Sandip Kumar, 2017. "Subjective beliefs and decision making under uncertainty in the field," ISU General Staff Papers 201701010800006248, Iowa State University, Department of Economics.
    6. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    7. Jesse Tack & Andrew Barkley & Lawton Nalley, 2014. "Heterogeneous effects of warming and drought on selected wheat variety yields," Climatic Change, Springer, vol. 125(3), pages 489-500, August.
    8. Tor N. Tolhurst & Alan P. Ker, 2015. "On Technological Change in Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 137-158.
    9. Gerlt, Scott & Thompson, Wyatt & Miller, Douglas, 2014. "Exploiting the Relationship between Farm-Level Yields and County-Level Yields for Applied Analysis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-18.
    10. A Ford Ramsey, 2020. "Probability Distributions of Crop Yields: A Bayesian Spatial Quantile Regression Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 220-239, January.
    11. Ker, Alan. P & Tolhurst, Tor & Liu, Yong, 2015. "Rating Area-yield Crop Insurance Contracts Using Bayesian Model Averaging and Mixture Models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205211, Agricultural and Applied Economics Association.
    12. repec:ags:aaea22:335759 is not listed on IDEAS
    13. Du, Xiaodong & Dong, Fengxia, 2024. "Climate Change and Dynamics of Crop Yield Distribution," 2024 Annual Meeting, July 28-30, New Orleans, LA 343786, Agricultural and Applied Economics Association.
    14. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," 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. 83(3), pages 1605-1634, September.
    15. Hennessy, David A., 2009. "Crop Yield Skewness and the Normal Distribution," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-19, April.
    16. Sheng, Di & Lambert, Dayton M. & Hellwinckel, Chad, 2016. "A Copula-based Approach to Simulate Climate Impacts on Yield: Some Preliminary Findings," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230006, Southern Agricultural Economics Association.
    17. Woodard, Joshua D. & Chiu Verteramo, Leslie & Miller, Alyssa P., 2015. "Adaptation of U.S. Agricultural Production to Drought and Climate Change," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205903, Agricultural and Applied Economics Association.
    18. Xiaodong Du & Cindy L. Yu & David A. Hennessy & Ruiqing Miao, 2015. "Geography of crop yield skewness," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 463-473, July.
    19. Li, Lisha, 2015. "Three essays on crop yield, crop insurance and climate change," ISU General Staff Papers 201501010800005371, Iowa State University, Department of Economics.
    20. Li, Shuang & Ker, Alan P., 2013. "An Assessment of the Canadian Federal-Provincial Crop Production Insurance Program under Future Climate Change Scenarios in Ontario," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151213, Agricultural and Applied Economics Association.
    21. Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogério Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná State," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(1), January.

    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:spr:climat:v:121:y:2013:i:4:p:689-700. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.