IDEAS home Printed from https://ideas.repec.org/p/ags/cudarb/122115.html
   My bibliography  Save this paper

Modeling the Household Purchasing Process Using a Panel Data Tobit Model

Author

Listed:
  • Dong, Diansheng
  • Schmit, Todd M.
  • Kaiser, Harry M.

Abstract

A panel data Tobit model is developed to examine the household purchase process for a frequently purchased commodity. The proposed model accounts not only for censoring or sample selectivity, but also the temporal dependence of the purchasing process using household panel data. The flexible error structure in the model accounts for both state dependence and household heterogeneity. Empirical findings show that purchase habits of milk persist across households over time, and most of them come from the household heterogeneity in preferences. Results also show that advertising increases the purchase quantity and purchase frequency simultaneously.

Suggested Citation

  • Dong, Diansheng & Schmit, Todd M. & Kaiser, Harry M., 2003. "Modeling the Household Purchasing Process Using a Panel Data Tobit Model," Research Bulletins 122115, Cornell University, Department of Applied Economics and Management.
    • Handle: RePEc:ags:cudarb:122115
    DOI: 10.22004/ag.econ.122115
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/122115/files/Cornell_Dyson_rb0307.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.122115?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. 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. 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.
    3. 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.
    4. Deaton, Angus, 1987. "Estimation of own- and cross-price elasticities from household survey data," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 7-30.
    5. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. 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. 25(2), pages 1-17, December.
    3. 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.
    4. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
    5. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    6. Ziegler, Andreas, 2001. "Simulated z-tests in multinomial probit models," ZEW Discussion Papers 01-53, ZEW - Leibniz Centre for European Economic Research.
    7. Andreas Ziegler, 2010. "Individual Characteristics and Stated Preferences for Alternative Energy Sources and Propulsion Technologies in Vehicles: A Discrete Choice Analysis," CER-ETH Economics working paper series 10/125, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    8. Inkmann, Joachim, 2000. "Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators," Journal of Econometrics, Elsevier, vol. 97(2), pages 227-259, August.
    9. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.
    10. Chintagunta, Pradeep & Kyriazidou, Ekaterini & Perktold, Josef, 2001. "Panel data analysis of household brand choices," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 111-153, July.
    11. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    12. Ziegler Andreas, 2010. "Z-Tests in Multinomial Probit Models under Simulated Maximum Likelihood Estimation: Some Small Sample Properties," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(5), pages 630-652, October.
    13. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    14. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    15. Ziegler, Andreas, 2002. "Simulated Classical Tests in the Multiperiod Multinomial Probit Model," ZEW Discussion Papers 02-38, ZEW - Leibniz Centre for European Economic Research.
    16. 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.
    17. Zhang, Xiao & Boscardin, W. John & Belin, Thomas R., 2008. "Bayesian analysis of multivariate nominal measures using multivariate multinomial probit models," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3697-3708, March.
    18. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    19. Maruyama, Shiko, 2014. "Estimation of finite sequential games," Journal of Econometrics, Elsevier, vol. 178(2), pages 716-726.
    20. Inkmann, Joachim, 1997. "Circumventing multiple integration: A comparison of GMM and SML estimators for the panel probit model," Discussion Papers, Series II 339, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".

    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:cudarb:122115. 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/dacorus.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.