IDEAS home Printed from https://ideas.repec.org/p/cdl/econwp/qt1900p96t.html
   My bibliography  Save this paper

Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier

Author

Listed:
  • Revelt, David
  • Train, Kenneth

Abstract

David Revelt and Kenneth Train. JEL#: C25, D12, L94. Keywords: energy suppliers, mixed logit, taste parameters In a discrete choice situation, information about the tastes of each sampled customer is inferred from estimates of the distribution of tastes in the population. First, maximum likelihood procedures are used to estimate the distribution of tastes in the population using the pooled data for all sampled customers. Then, the distribution of tastes of each sampled customer is derived conditional on the observed data for that customer and the estimated population distribution of tastes (accounting for uncertainty in the population estimates.) We apply the method to data on residential customers' choice among energy suppliers in conjoint-type experiments. The estimated distribution of tastes provides practical information that is useful for suppliers in designing their offers. The conditioning for individual customers is found to differentiate customers effectively for marketing purposes and to improve considerably the predictions in new situations. May 2000
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Revelt, David & Train, Kenneth, 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Department of Economics, Working Paper Series qt1900p96t, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  • Handle: RePEc:cdl:econwp:qt1900p96t
    as

    Download full text from publisher

    File URL: http://www.escholarship.org/uc/item/1900p96t.pdf;origin=repeccitec
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Lee, Lung-Fei, 1992. "On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Cambridge University Press, vol. 8(04), pages 518-552, December.
    3. Denis Bolduc & Bernard Fortin & Stephen Gordon, 1997. "Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques," International Regional Science Review, , vol. 20(1-2), pages 77-101, April.
    4. Bhat, Chandra R., 1998. "Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 495-507, September.
    5. Neeraj Arora & Greg M. Allenby & James L. Ginter, 1998. "A Hierarchical Bayes Model of Primary and Secondary Demand," Marketing Science, INFORMS, pages 29-44.
    6. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    7. 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.
    8. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    9. Algers, S. & Bergstrom, P. & Dahlberg, M. & Dillen, J.L., 1998. "Mixed Logit Estimation of the Value of Travel Time," Papers 1998:15, Uppsala - Working Paper Series.
    10. Griffiths, William E., 1971. "Estimation Of Actual Response Coefficients In The Hildreth-Houck Random Coefficient Model," Staff Papers 14275, University of Minnesota, Department of Applied Economics.
    11. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    12. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    13. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    14. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
    15. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    energy suppliers; mixed logit; taste parameters; Business; Social and Behavioral Sciences; Energy Policy; Infrastructure; Science and Technology Policy;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    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:cdl:econwp:qt1900p96t. 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: (Lisa Schiff). General contact details of provider: http://edirc.repec.org/data/ibbrkus.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.