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Modelling milk purchasing behaviour with a panel data double-hurdle model

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  • Diansheng Dong
  • Chanjin Chung
  • Harry Kaiser

Abstract

In this study, the double-hurdle model typically used in cross-sectional data is extended to panel data structures. The new double-hurdle model can account not only for the censored nature of commodity purchases, but also for the dynamics of the purchase process. In this model, a flexible error structure is assumed to account for state dependence and household-specific heterogeneity. In the empirical application for milk purchases, it is found that generic advertising increases the probability of market participation as well as the purchase quantity and incidence. Temporal dependence is also found in both purchase and participation equations.

Suggested Citation

  • Diansheng Dong & Chanjin Chung & Harry Kaiser, 2004. "Modelling milk purchasing behaviour with a panel data double-hurdle model," Applied Economics, Taylor & Francis Journals, vol. 36(8), pages 769-779.
    • Handle: RePEc:taf:applec:v:36:y:2004:i:8:p:769-779
    DOI: 10.1080/0003684042000229505
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    2. Stephens, Emma C. & Barrett, Christopher B., 2006. "Missing credit markets and commodity marketing behavior," 2006 Annual meeting, July 23-26, Long Beach, CA 21347, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Sandro Ambuehl, 2017. "An Offer You Can't Refuse? Testing Undue Inducement," CESifo Working Paper Series 6296, CESifo.
    4. Yoko KONISHI, 2017. "On the Role of Skill, Quality, and Environmental Factors on Customer Behavior of the Beauty Industry," Discussion papers 17035, Research Institute of Economy, Trade and Industry (RIETI).
    5. Stewart, Hayden & Kuchler, Fred & Dong, Diansheng & Cessna, Jerry, 2021. "Examining the Decline in U.S. Per Capita Consumption of Fluid Cow’s Milk, 2003–18," Economic Research Report 327183, United States Department of Agriculture, Economic Research Service.
    6. Jonas, A. & Roosen, J., . "Eine zweistufige Nachfrageschätzung für Milch: Biomilch, Handelsmarken und Herstellermarken," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 41.
    7. Feng Zhang & Chung L. Huang & Biing-Hwan Lin & James E. Epperson, 2008. "Modeling fresh organic produce consumption with scanner data: a generalized double hurdle model approach," Agribusiness, John Wiley & Sons, Ltd., vol. 24(4), pages 510-522.
    8. Christoph Engel & Peter G. Moffat, 2012. "Estimation of the House Money Effect Using Hurdle Models," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2012_13, Max Planck Institute for Research on Collective Goods.
    9. Bardazzi, Rossella & Pazienza, Maria Grazia, 2018. "Ageing and private transport fuel expenditure: Do generations matter?," Energy Policy, Elsevier, vol. 117(C), pages 396-405.
    10. Pedro A. Alviola & Oral Capps, 2010. "Household demand analysis of organic and conventional fluid milk in the United States based on the 2004 Nielsen Homescan panel," Agribusiness, John Wiley & Sons, Ltd., vol. 26(3), pages 369-388.
    11. Stewart, Hayden & Kuchler, Fred & Dong, Diansheng & Cessna, Jerry, "undated". "Examining the Decline in U.S. Per Capita Consumption of Fluid Cow’s Milk, 2003–18," USDA Miscellaneous 316500, United States Department of Agriculture.
    12. Astrid Jonas & Jutta Roosen, 2008. "Demand for milk labels in Germany: organic milk, conventional brands, and retail labels," Agribusiness, John Wiley & Sons, Ltd., vol. 24(2), pages 192-206.
    13. Davis, Chris & Blayney, Don & Yen, Steven & Cooper, Joseph C., 2009. "An analysis of at-home demand for ice cream in the United States," MPRA Paper 24782, University Library of Munich, Germany.

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