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

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  • David Revelt and Kenneth Train.

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

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Paper provided by University of California at Berkeley in its series Economics Working Papers with number E00-274.

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Date of creation: 01 May 2000
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Handle: RePEc:ucb:calbwp:e00-274

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Cited by:
  1. Hensher, David A. & Li, Zheng, 2010. "Accounting for differences in modelled estimates of RP, SP and RP/SP direct petrol price elasticities for car mode choice: A warning," Transport Policy, Elsevier, vol. 17(3), pages 191-195, May.
  2. Gaudecker, H.M. von & Soest, A.H.O. van & Wengstrom, E., 2011. "Heterogeneity in risky choice behavior in a broad population," Open Access publications from Tilburg University urn:nbn:nl:ui:12-3857699, Tilburg University.
  3. Masiero, Lorenzo & Rose, John M., 2013. "The role of the reference alternative in the specification of asymmetric discrete choice models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 83-92.
  4. Achtnicht, Martin, 2011. "Do environmental benefits matter? Evidence from a choice experiment among house owners in Germany," Ecological Economics, Elsevier, vol. 70(11), pages 2191-2200, September.
  5. David Hensher, 2006. "The Signs of the Times: Imposing a Globally Signed Condition on Willingness to Pay Distributions," Transportation, Springer, vol. 33(3), pages 205-222, 05.
  6. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
  7. David Hensher & John Rose, 2009. "Toll product preferences and implications for alternative payment options and going cashless," Transportation, Springer, vol. 36(2), pages 131-145, March.
  8. Francisco J. Más & Juan Luis Nicolau, 2006. "A New Marketing Segmentation Approach Based On Marginal Individual Utilities: Applying Crm Is Not A Chimera Anymore," Working Papers. Serie EC 2006-16, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  9. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
  10. Greene, William H. & Hensher, David A. & Rose, John, 2006. "Accounting for heterogeneity in the variance of unobserved effects in mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 75-92, January.
  11. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
  12. Hans-Martin Gaudecker & Arthur Soest & Erik Wengström, 2012. "Experts in experiments," Journal of Risk and Uncertainty, Springer, vol. 45(2), pages 159-190, October.
  13. Joseph Pancras, 2010. "A Framework to Determine the Value of Consumer Consideration Set Information for Firm Pricing Strategies," Computational Economics, Society for Computational Economics, vol. 35(3), pages 269-300, March.
  14. David Hensher & David Layton, 2010. "Parameter transfer of common-metric attributes in choice analysis: implications for willingness to pay," Transportation, Springer, vol. 37(3), pages 473-490, May.
  15. Hensher, David A., 2008. "Influence of vehicle occupancy on the valuation of car driver's travel time savings: Identifying important behavioural segments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 67-76, January.

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