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Consumers and experts: an econometric analysis of the demand for water heaters

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  • Robert Bartels
  • Denzil Fiebig
  • Arthur Soest

Abstract

Consumers can accumulate product information on the basis of a combination of searching, product advertising and expert advice.Examples of experts who provide product information include doctors advising patients on treatments, motor mechanics diagnosing car problems and recommending repairs, accountants recommending investment strategies, and plumbers making recommendations on alternative water heaters.In each of these examples, the transactions involve the sale of goods and services where the seller is at the same time an expert providing advice on the amount and type of product or service to be purchased.In the case of water heaters, the plumber advising a consumer on their choice of water heater will most likely also install the appliance.Because of the information asymmetry there is potentially a strategic element in the transmission of information from expert to consumer.This paper reports on an econometric investigation of the factors that determine the choices made by consumers and the recommendations made by plumbers and the extent to which plumbers act in the best interests of their customers.The empirical work is made possible by the availability of stated preference data generated by designed experiments involving separate samples of Australian consumers and plumbers.We find some evidence that plumbers have higher preferences than consumers for heater characteristics that increase their profit margin.
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  • Robert Bartels & Denzil Fiebig & Arthur Soest, 2006. "Consumers and experts: an econometric analysis of the demand for water heaters," Empirical Economics, Springer, vol. 31(2), pages 369-391, June.
    • Handle: RePEc:spr:empeco:v:31:y:2006:i:2:p:369-391
    DOI: 10.1007/s00181-006-0052-y
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    4. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    5. Wasi, Nada & Carson, Richard T., 2013. "The influence of rebate programs on the demand for water heaters: The case of New South Wales," Energy Economics, Elsevier, vol. 40(C), pages 645-656.
    6. Arouna, Aminou & Adegbola, Patrice Y. & Raphael, Babatunde & Diagne, Aliou, 2015. "Contract farming preferences by smallholder rice producers in Africa: a stated choice model using mixed logic," 2015 Conference, August 9-14, 2015, Milan, Italy 210957, International Association of Agricultural Economists.
    7. Emily Lancsar & Denzil G. Fiebig & Arne Risa Hole, 2017. "Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software," PharmacoEconomics, Springer, vol. 35(7), pages 697-716, July.
    8. Noemi Munkacsi & Krushna Mahapatra, 2019. "Communication and Household Adoption of Heating Products in Hungary," Energies, MDPI, vol. 12(2), pages 1-22, January.
    9. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    10. Higgins, Andrew & McNamara, Cheryl & Foliente, Greg, 2014. "Modelling future uptake of solar photo-voltaics and water heaters under different government incentives," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 142-155.
    11. Cristiano Franceschinis & Riccardo Scarpa & Mara Thiene & John Rose & Michele Moretto & Raffaele Cavalli, 2016. "Exploring the Spatial Heterogeneity of Individual Preferences for Ambient Heating Systems," Energies, MDPI, vol. 9(6), pages 1-19, May.
    12. Chandra R. Bhat & Patrícia S. Lavieri, 2018. "A new mixed MNP model accommodating a variety of dependent non-normal coefficient distributions," Theory and Decision, Springer, vol. 84(2), pages 239-275, March.
    13. Jose Blandon & Spencer Henson & Towhidul Islam, 2009. "Marketing preferences of small-scale farmers in the context of new agrifood systems: a stated choice model," Agribusiness, John Wiley & Sons, Ltd., vol. 25(2), pages 251-267.
    14. Paleti, Rajesh & Bhat, Chandra R., 2013. "The composite marginal likelihood (CML) estimation of panel ordered-response models," Journal of choice modelling, Elsevier, vol. 7(C), pages 24-43.
    15. Fiebig, D.G. & Viney, R. & Haas, M. & Knox, S. & Street, D. & Weisberg, E. & Bateson, D., 2015. "Complexity and doctor choices when discussing contraceptives," Health, Econometrics and Data Group (HEDG) Working Papers 15/14, HEDG, c/o Department of Economics, University of York.

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    More about this item

    Keywords

    Appliance choice; Stated preference data; Mixed logit; C35; L84;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • L84 - Industrial Organization - - Industry Studies: Services - - - Personal, Professional, and Business Services

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