IDEAS home Printed from https://ideas.repec.org/p/ags/aaea01/20502.html
   My bibliography  Save this paper

Panel Data Double-Hurdle Model: An Application To Dairy Advertising

Author

Listed:
  • Dong, Diansheng
  • Chung, Chanjin
  • Kaiser, Harry M.

Abstract

In this study, we extend to panel data structures the double-hurdle model typically used in cross-sectional data. 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 purchase, we find 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

  • Dong, Diansheng & Chung, Chanjin & Kaiser, Harry M., 2001. "Panel Data Double-Hurdle Model: An Application To Dairy Advertising," 2001 Annual meeting, August 5-8, Chicago, IL 20502, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea01:20502
    as

    Download full text from publisher

    File URL: http://ageconsearch.umn.edu/record/20502/files/sp01do01.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August.
    2. 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.
    3. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    4. 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.
    5. Diansheng Dong & Brian W. Gould, 2000. "Quality versus quantity in Mexican household poultry and pork purchases," Agribusiness, John Wiley & Sons, Ltd., vol. 16(3), pages 333-355.
    6. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    7. Steven T. Yen & Andrew M. Jones, 1997. "Household Consumption of Cheese: An Inverse Hyperbolic Sine Double-Hurdle Model with Dependent Errors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 246-251.
    8. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
    9. Keane, Michael P, 1997. "Modeling Heterogeneity and State Dependence in Consumer Choice Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 310-327, July.
    10. Jones, Andrew M, 1989. "A Double-Hurdle Model of Cigarette Consumption," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(1), pages 23-39, Jan.-Mar..
    11. Gould, Brian W. & Dong, Diansheng, 2000. "The Decision Of When To Buy A Frequently Purchased Good: A Multi-Period Probit Model," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 2), pages 1-17, December.
    12. 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.
    13. Vella, Francis & Verbeek, Marno, 1999. "Two-step estimation of panel data models with censored endogenous variables and selection bias," Journal of Econometrics, Elsevier, vol. 90(2), pages 239-263, June.
    14. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    15. Hajivassiliou, Vassilis A., 1987. "The external debt repayments problems of LDC's : An econometric model based on panel data," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 205-230.
    16. 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.
    17. Blundell, Richard & Meghir, Costas, 1987. "Bivariate alternatives to the Tobit model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 179-200.
    18. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
    19. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
    20. Breslaw, Jon A, 1994. "Evaluation of Multivariate Normal Probability Integrals Using a Low Variance Simulator," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 673-682, November.
    21. Diansheng Dong & J.S. Shonkwiler & Oral Capps, 1998. "Estimation of Demand Functions Using Cross-Sectional Household Data: The Problem Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 466-473.
    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. Maynard, Leigh J. & Hartell, Jason G. & Meyer, A. Lee & Hao, Jianqiang, 2004. "An experimental approach to valuing new differentiated products," Agricultural Economics, Blackwell, vol. 31(2-3), pages 317-325, December.
    2. Beltran, Jesusa C. & Pannell, David J. & Doole, Graeme J. & White, Benedict, 2011. "Factors that affect the use of herbicides in Philippine rice farming systems," Working Papers 108769, University of Western Australia, School of Agricultural and Resource Economics.

    More about this item

    Keywords

    Marketing;

    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:aaea01:20502. 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: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaeaaea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.