IDEAS home Printed from https://ideas.repec.org/p/ags/ucdavw/11997.html
   My bibliography  Save this paper

The Market Effect of a Food Scare: The Case of Genetically Modified StarLink Corn

Author

Listed:
  • Carter, Colin A.
  • Smith, Aaron D.

Abstract

Genetic modification of crops has revolutionized food production, but it remains controversial due to food safety concerns. A recent food safety scare provides a natural experiment on the market's willingness to accept an increase in perceived risk from genetically modified (GM) food. We analyze the market impact of contamination of the U.S. food-corn supply by a GM variety called StarLink. We find that the contamination led to a 6.8 percent discount in corn prices and that the suppression of prices lasted for at least a year.

Suggested Citation

  • Carter, Colin A. & Smith, Aaron D., 2004. "The Market Effect of a Food Scare: The Case of Genetically Modified StarLink Corn," Working Papers 11997, University of California, Davis, Department of Agricultural and Resource Economics.
  • Handle: RePEc:ags:ucdavw:11997
    DOI: 10.22004/ag.econ.11997
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/11997/files/wp040012.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.11997?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. Erik Dohlman & Thomas Hall & Agapi Somwaru, 2002. "Regulatory Events and Biotech Firm Share Prices," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 24(1), pages 108-122.
    2. Shogren, Jason F. & Seung Y. Shin & Dermot J. Hayes & James B. Kliebenstein, 1994. "Resolving Differences in Willingness to Pay and Willingness to Accept," American Economic Review, American Economic Association, vol. 84(1), pages 255-270, March.
    3. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    4. William Lin & Gregory K. Price & Edward W. Allen, 2003. "StarLink: Impacts on the U.S. corn market and world trade," Agribusiness, John Wiley & Sons, Ltd., vol. 19(4), pages 473-488.
    5. Williams, Jeffrey, 1987. "Futures Markets: A Consequences of Risk Aversion or Transactions Costs?," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1000-1023, October.
    6. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    7. Barry K. Goodwin & Nicholas E. Piggott, 2001. "Spatial Market Integration in the Presence of Threshold Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 302-317.
    8. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
    9. Lence, Sergio H. & Hayes, Dermot J., 2001. "Response to an Asymmetric Demand for Attributes: An Application to the Market for Genetically Modified Crops," MATRIC Working Paper Series 18699, Iowa State University, Midwest Agribusiness Trade Research and Information Center.
    10. Jayson L. Lusk, 2003. "Effects of Cheap Talk on Consumer Willingness-to-Pay for Golden Rice," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 840-856.
    11. John Connor, 2001. "“Our Customers Are Our Enemies”: The Lysine Cartel of 1992–1995," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 18(1), pages 5-21, February.
    12. Clive W.J. Granger, 2004. "Time Series Analysis, Cointegration, and Applications," American Economic Review, American Economic Association, vol. 94(3), pages 421-425, June.
    13. Hansen, Peter Reinhard, 2003. "Structural changes in the cointegrated vector autoregressive model," Journal of Econometrics, Elsevier, vol. 114(2), pages 261-295, June.
    14. Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996. "Optimal changepoint tests for normal linear regression," Journal of Econometrics, Elsevier, vol. 70(1), pages 9-38, January.
    15. Hansen, Bruce E, 2002. "Tests for Parameter Instability in Regressions with I(1) Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 45-59, January.
    16. Chalfant, James A & Alston, Julian M, 1988. "Accounting for Changes in Tastes," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 391-410, April.
    17. A. Craig MacKinlay, 1997. "Event Studies in Economics and Finance," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 13-39, March.
    18. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    19. Spencer Henson & Mario Mazzocchi, 2002. "Impact of Bovine Spongiform Encephalopathy on Agribusiness in the United Kingdom: Results of an Event Study of Equity Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 370-386.
    20. Michael R. Thomsen & Andrew M. McKenzie, 2001. "Market Incentives for Safe Foods: An Examination of Shareholder Losses from Meat and Poultry Recalls," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 526-538.
    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. David Ubilava, 2012. "Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 28(1), pages 29-41, January.
    2. David Ubilava, 2012. "El Niño, La Niña, and world coffee price dynamics," Agricultural Economics, International Association of Agricultural Economists, vol. 43(1), pages 17-26, January.
    3. Ubilava, David & Helmers, Claes Gustav, 2011. "The ENSO Impact on Predicting World Cocoa Prices," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103528, Agricultural and Applied Economics Association.
    4. Almánzar, Miguel & Torero, Máximo & Grebmer, Klaus von, 2013. "Futures Commodities Prices and Media Coverage," Discussion Papers 149414, University of Bonn, Center for Development Research (ZEF).
    5. Magnier, Alexandre & Konduru, Srinivasa & Kalaitzandonakes, Nicholas G., 2009. "Market and Welfare Effects of Trade Disruptions from Unapproved Biotech Crops," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49592, Agricultural and Applied Economics Association.
    6. Zhen, Chen, 2009. "Long-Run Effects From Consumer Reaction To The Spread Of Foodborne Pathogens: The Case Of E. Coli Contamination Of Beef At Jack In The Box Restaurants," 2009 Conference, August 16-22, 2009, Beijing, China 51341, International Association of Agricultural Economists.
    7. Wyn Morgan & John Cotter & Kevin Dowd, 2012. "Extreme Measures of Agricultural Financial Risk," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(1), pages 65-82, February.
    8. Detre, Joshua D. & Gunderson, Michael A., 2011. "The Triple Bottom Line: What is the Impact on the Returns to Agribusiness?," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 14(4), pages 1-14, November.
    9. Resende Filho, Moises de Andrade & Buhr, Brian L., 2006. "Economic Evidence of Willingness to Pay for the National Animal Identification System in the US," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25342, International Association of Agricultural Economists.

    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. Colin A. Carter & Aaron Smith, 2007. "Estimating the Market Effect of a Food Scare: The Case of Genetically Modified StarLink Corn," The Review of Economics and Statistics, MIT Press, vol. 89(3), pages 522-533, August.
    2. Miller, Stephen M. & Martins, Luis Filipe & Gupta, Rangan, 2019. "A Time-Varying Approach Of The Us Welfare Cost Of Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 775-797, March.
    3. repec:ipg:wpaper:2014-474 is not listed on IDEAS
    4. Eiji Kurozumi & Yoichi Arai, 2007. "Efficient estimation and inference in cointegrating regressions with structural change," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(4), pages 545-575, July.
    5. Irz, Xavier & Mazzocchi, Mario & Réquillart, Vincent & Soler, Louis-Georges, 2015. "Research in Food Economics: past trends and new challenges," Revue d'Etudes en Agriculture et Environnement, Editions NecPlus, vol. 96(01), pages 187-237, March.
    6. Boetel, Brenda L. & Liu, Donald J., 2008. "Incorporating Structural Changes in Agricultural and Food Price Analysis: An Application to the U.S. Beef and Pork Sectors," Working Papers 44076, University of Minnesota, The Food Industry Center.
    7. Tarlok Singh, 2017. "Are Current Account Deficits in the OECD Countries Sustainable? Robust Evidence from Time-Series Estimators," The International Trade Journal, Taylor & Francis Journals, vol. 31(1), pages 29-64, January.
    8. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.
    9. Vicente Esteve, 2004. "Política fiscal y productividad del trabajo en la economía española: un análisis de series temporales," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 3-29, June.
    10. Lukáš ČECHURA & Tereza TAUSSIGOVÁ, 2013. "Avian influenza and structural change in the Czech poultry industry," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 59(1), pages 38-47.
    11. Maki, Daiki, 2012. "Tests for cointegration allowing for an unknown number of breaks," Economic Modelling, Elsevier, vol. 29(5), pages 2011-2015.
    12. Lise Pichette, 2000. "Les effets réels du cours des actions sur la consommation," Staff Working Papers 00-21, Bank of Canada.
    13. Maria Heracleous & Andreas Koutris & Aris Spanos, 2006. "Testing for Structural Breaks and other forms of Non-stationarity: a Misspecification Perspective," Computing in Economics and Finance 2006 493, Society for Computational Economics.
    14. Singh, Prakash & Pandey, Manoj K., 2009. "Structural break, stability and demand for money in India," MPRA Paper 15425, University Library of Munich, Germany.
    15. Nguyen, Tien-Trung & Wu, Yang-Che & Ke, Mei-Chu & Liao, Tung Liang, 2022. "Can direct government intervention save the stock market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 271-284.
    16. John M. Maheu & Stephen Gordon, 2008. "Learning, forecasting and structural breaks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 553-583.
    17. Wilton Bernardino & João B. Amaral & Nelson L. Paes & Raydonal Ospina & José L. Távora, 2022. "A statistical investigation of a stock valuation model," SN Business & Economics, Springer, vol. 2(8), pages 1-25, August.
    18. Bertrand Groslambert & Raphaël Chiappini & Olivier Bruno, 2015. "Bank Output Calculation in the Case of France: What Do New Methods Tell About the Financial Intermediation Services in the Aftermath of the Crisis?," GREDEG Working Papers 2015-32, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    19. Esra N. Kılcı & Burcu Kıran Baygın, 2019. "Analysis of the Relationship between Real Effective Exchange Rate, Common Equity Tier 1 Ratio and Return on Equity: Evidence from Turkey," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 7(2), pages 319-332, December.
    20. Martin T. Bohl & Alexander Pütz & Pierre L. Siklos & Christoph Sulewski, 2018. "Information Transmission under Increasing Political Tension – Evidence for the Berlin Produce Exchange 1887-1896," CQE Working Papers 7618, Center for Quantitative Economics (CQE), University of Muenster.
    21. Kim, Dukpa & Oka, Tatsushi & Estrada, Francisco & Perron, Pierre, 2020. "Inference related to common breaks in a multivariate system with joined segmented trends with applications to global and hemispheric temperatures," Journal of Econometrics, Elsevier, vol. 214(1), pages 130-152.

    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:ucdavw:11997. 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/daucdus.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.