Advanced Search
MyIDEAS: Login

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

Contents:

Author Info

  • 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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.tandfonline.com/doi/abs/10.1080/0003684042000229505
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 36 (2004)
Issue (Month): 8 ()
Pages: 769-779

as in new window
Handle: RePEc:taf:applec:v:36:y:2004:i:8:p:769-779

Contact details of provider:
Web page: http://www.tandfonline.com/RAEC20

Order Information:
Web: http://www.tandfonline.com/pricing/journal/RAEC20

Related research

Keywords:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. V.A. Hajivassiliou & P. A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Econometrics 9311002, EconWPA.
  2. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 103-116 National Bureau of Economic Research, Inc.
  3. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
  4. Blundell, Richard & Meghir, Costas, 1987. "Bivariate alternatives to the Tobit model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 179-200.
  5. Erdem, Tulin & Keane, Michael P. & Sun, Baohong, 1998. "Missing price and coupon availability data in scanner panels: Correcting for the self-selection bias in choice model parameters," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 177-196, November.
  6. Vassilis A. Hajivassiliou & Daniel L. McFadden, 1998. "The Method of Simulated Scores for the Estimation of LDV Models," Econometrica, Econometric Society, vol. 66(4), pages 863-896, July.
  7. John F. Geweke & Michael P. Keane & David E. Runkle, 1994. "Statistical inference in the multinomial multiperiod probit model," Staff Report 177, Federal Reserve Bank of Minneapolis.
  8. Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
  9. Vassilis A. Hajivassiliou & Daniel McFadden, 1990. "The Method of Simulated Scores for the Estimation of LDV Models with an Application to External Debt Crisis," Cowles Foundation Discussion Papers 967, Cowles Foundation for Research in Economics, Yale University.
  10. McDonald, John F & Moffitt, Robert A, 1980. "The Uses of Tobit Analysis," The Review of Economics and Statistics, MIT Press, vol. 62(2), pages 318-21, May.
  11. Garcia, Jaume & Labeaga, Jose M, 1996. "Alternative Approaches to Modelling Zero Expenditure: An Application to Spanish Demand for Tobacco," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 489-506, August.
  12. Deaton, Angus & Irish, Margaret, 1984. "Statistical models for zero expenditures in household budgets," Journal of Public Economics, Elsevier, vol. 23(1-2), pages 59-80.
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 in new window

Cited by:
  1. Christoph Engel & Peter G. Moffat, 2012. "Estimation of the House Money Effect Using Hurdle Models," Working Paper Series of the Max Planck Institute for Research on Collective Goods 2012_13, Max Planck Institute for Research on Collective Goods.
  2. 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.
  3. 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.
  4. 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).
  5. 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.
  6. 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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:taf:applec:v:36:y:2004:i:8:p:769-779. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.