IDEAS home Printed from https://ideas.repec.org/a/ags/aareaj/333858.html
   My bibliography  Save this article

In Vino ‘No’ Veritas: impacts of fraud on wine imports in China

Author

Listed:
  • Muhammad, Andrew
  • Countryman, Amanda M.

Abstract

China is one of the largest wine importing countries in the world and is poised for continued import growth in the future. Increased wine purchases throughout China have given rise to persistent fraud where fake wines are packaged and sold with counterfeit contents and labels. For exporting countries like France, counterfeit wines displace market share, damage foreign brand reputation, and cause distrust in consumers who are aware of counterfeiting problems throughout the country. We examine the impact of fraudulent wine events (as measured by negative media reports) on Chinese wine demand differentiated by supplying country. We employ the Rotterdam demand system and a switching regression procedure to estimate import demand and compare results across different media variable specifications. Results consistently show that negative reports disproportionately affect French wine regardless of how the media variable is specified. This is not surprising because most fraudulent events involve French wine counterfeits.

Suggested Citation

  • Muhammad, Andrew & Countryman, Amanda M., 2019. "In Vino ‘No’ Veritas: impacts of fraud on wine imports in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), October.
  • Handle: RePEc:ags:aareaj:333858
    DOI: 10.22004/ag.econ.333858
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/333858/files/ajar12333.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.333858?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Giancarlo Moschini & Karl D. Meilke, 1989. "Modeling the Pattern of Structural Change in U.S. Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 253-261.
    2. Andrew Muhammad & Amanda M. Leister & Lihong McPhail & Wei Chen, 2014. "The evolution of foreign wine demand in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(3), pages 392-408, July.
    3. Yadavalli, Anita & Jones, Keithly, 2014. "Does media influence consumer demand? The case of lean finely textured beef in the United States," Food Policy, Elsevier, vol. 49(P1), pages 219-227.
    4. Monia Ben Kaabia & Ana M. Angulo, 2001. "Health information and the demand for meat in Spain," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 28(4), pages 499-518, December.
    5. Kym Anderson & Glyn Wittwer, 2019. "Asia’s Evolving Role in Global Wine Markets," World Scientific Book Chapters, in: Kym Anderson (ed.), The International Economics of Wine, chapter 14, pages 347-377, World Scientific Publishing Co. Pte. Ltd..
    6. Verbeke, Wim & Ward, Ronald W., 2001. "A fresh meat almost ideal demand system incorporating negative TV press and advertising impact," Agricultural Economics, Blackwell, vol. 25(2-3), pages 359-374, September.
    7. Seale, James L., Jr. & Sparks, Amy L. & Buxton, Boyd M., 1992. "A Rotterdam Application To International Trade In Fresh Apples: A Differential Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 17(1), pages 1-12, July.
    8. Andrew Muhammad, 2011. "Wine demand in the United Kingdom and new world structural change: a source‐disaggregated analysis," Agribusiness, John Wiley & Sons, Ltd., vol. 27(1), pages 82-98, Winter.
    9. Holt, Charles C., 2004. "Author's retrospective on 'Forecasting seasonals and trends by exponentially weighted moving averages'," International Journal of Forecasting, Elsevier, vol. 20(1), pages 11-13.
    10. Richard E. Just, 2001. "Addressing the Changing Nature of Uncertainty in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(5), pages 1131-1153.
    11. James L. Seale & Mary A. Marchant & Alberto Basso, 2003. "Imports versus Domestic Production: A Demand System Analysis of the U.S. Red Wine Market," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(1), pages 187-202.
    12. J. M. Gil & B. Dhehibi & M. Ben Kaabia & A. M. Angulo, 2004. "Non-stationarity and the import demand for virgin olive oil in the European Union," Applied Economics, Taylor & Francis Journals, vol. 36(16), pages 1859-1869.
    13. Ohtani, Kazuhiro & Kakimoto, Sumio & Abe, Kenzo, 1990. "A gradual switching regression model with a flexible transition path," Economics Letters, Elsevier, vol. 32(1), pages 43-48, January.
    14. Hikaru Hanawa Peterson & Yun-Ju (Kelly) Chen, 2005. "The impact of BSE on Japanese retail meat demand," Agribusiness, John Wiley & Sons, Ltd., vol. 21(3), pages 313-327.
    15. Holt, Charles C., 2004. "Forecasting seasonals and trends by exponentially weighted moving averages," International Journal of Forecasting, Elsevier, vol. 20(1), pages 5-10.
    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. Luca Barbaglia & Christophe Croux & Ines Wilms, 2022. "Detecting Anti-dumping Circumvention: A Network Approach," Papers 2207.05394, arXiv.org.
    2. Ehmke, Mariah Dolsen & Bonanno, Alessandro & Boys, Kathryn & Smith, Trenton G., 2019. "Food fraud: economic insights into the dark side of incentives," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), October.

    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. Muhammad, Andrew & D’Souza, Anna & Amponsah, William, 2013. "Violence, Instability, and Trade: Evidence from Kenya’s Cut Flower Sector," World Development, Elsevier, vol. 51(C), pages 20-31.
    2. Yadavalli, Anita & Jones, Keithly, 2014. "Does media influence consumer demand? The case of lean finely textured beef in the United States," Food Policy, Elsevier, vol. 49(P1), pages 219-227.
    3. Muhammad, Andrew & Ngeleza, Guyslain, 2010. "Emergence of Sri Lanka in European fish trade," IFPRI discussion papers 978, International Food Policy Research Institute (IFPRI).
    4. Asche, Frank & Zhang, Dengjun, 2013. "Testing Structural Changes in the U.S. Whitefish Import Market: An Inverse Demand System Approach," Agricultural and Resource Economics Review, Cambridge University Press, vol. 42(3), pages 453-470, December.
    5. Rodrigo García Arancibia & Edith Depetris Guiguet, 2020. "Brazilian Import Demand of Dairy Products with Emphasis in the Mercosul Context [Demanda brasileira de importações de laticínios com ênfase no contexo do Mercosul]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 30(2), pages 551-577, May-Augus.
    6. Muhammad, Andrew & Leister, Amanda M. & McPhail, Lihong & Chen, Wei, 2014. "The evolution of foreign wine demand in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(3), July.
    7. Ariel Soto‐Caro & Feng Wu & Tian Xia & Zhengfei Guan, 2023. "Demand analysis with structural changes: Model and application to the US blueberry market," Agribusiness, John Wiley & Sons, Ltd., vol. 39(4), pages 1100-1116, October.
    8. Yuxin Zhang & Yifei Yang & Xiaosi Li & Zijing Yuan & Yuki Todo & Haichuan Yang, 2023. "A Dendritic Neuron Model Optimized by Meta-Heuristics with a Power-Law-Distributed Population Interaction Network for Financial Time-Series Forecasting," Mathematics, MDPI, vol. 11(5), pages 1-20, March.
    9. Simona Mikšíková & David Ulčák & František Kuda, 2022. "Analysis of Malfunctions in Selected Parking Systems in the Czech Republic," Sustainability, MDPI, vol. 14(3), pages 1-10, February.
    10. Vesna Karadzic & Bojan Pejovic, 2021. "Inflation Forecasting in the Western Balkans and EU: A Comparison of Holt-Winters, ARIMA and NNAR Models," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 517-517.
    11. Liu, Che & Sun, Bo & Zhang, Chenghui & Li, Fan, 2020. "A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine," Applied Energy, Elsevier, vol. 275(C).
    12. Gardner, Everette Shaw & Acar, Yavuz, 2016. "The forecastability quotient reconsidered," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1208-1211.
    13. Hossein Yousefi & Mohammad Hasan Ghodusinejad & Armin Ghodrati, 2022. "Multi-Criteria Future Energy System Planning and Analysis for Hot Arid Areas of Iran," Energies, MDPI, vol. 15(24), pages 1-25, December.
    14. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    15. Dyna Heng & Anna Ivanova & Rodrigo Mariscal & Ms. Uma Ramakrishnan & Joyce Wong, 2016. "Advancing Financial Development in Latin America and the Caribbean," IMF Working Papers 2016/081, International Monetary Fund.
    16. Lazos, Dimitris & Sproul, Alistair B. & Kay, Merlinde, 2014. "Optimisation of energy management in commercial buildings with weather forecasting inputs: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 587-603.
    17. Muhammad, Andrew & Jones, Keithly G., 2009. "An Assessment of Dynamic Behavior in the U.S. Catfish Market: An Application of the Generalized Dynamic Rotterdam Model," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(3), pages 1-14, December.
    18. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
    19. Kim, Yochan & Park, Jinkyun & Jung, Wondea, 2017. "A quantitative measure of fitness for duty and work processes for human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 595-601.
    20. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).

    More about this item

    Keywords

    International Relations/Trade;

    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:aareaj:333858. 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/aaresea.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.