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Addressing Preference Heterogeneity, Multiple Scales and Attribute Attendance with a Correlated Finite Mixing Model of Tap Water Choice

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Abstract

Unobserved heterogeneity of error scale in choice models is a recent extension of the better investigated issue of heterogeneity of taste intensity. It is achieved by fitting choice panel data with specifications that simultaneously handle inter-personal variation in scale and taste. The aim is to separate differences in preference intensities across respondents from differences in the degree of consistency in choice behaviour, or ‘preference discrimination’, while accounting for correlation between the two. Another recent substantive issue in choice data analysis is attribute non-attendance. We develop a finite mixing model to address simultaneously the three issues above. We empirically prove the concept on stated preference data related to tap water attributes in a study for industry regulation.

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Notes

  1. One can easily check that the joint membership probability for scale-preference class \(c,s\) is not the product of the marginal probabilities for membership to scale class and preference class whenever \(\delta _{cs} \ne 0\). For example, with two classes for preference and two for scale and plugging in values of \(\uptheta _{1}= 0.2,\,\upomega _{1}= 0.3,\,\uptheta _{2}= 0,\, \upomega _{2}= 0,\,\delta _{1,1}=0.5\) we obtain \(\hbox {Pr}(n\in c=1,s=1) = 0.2146\), while \(\hbox {Pr}(n\in s=1) \times \hbox { Pr}(n \in c=1)=0.2416\), which clearly violates independence because the joint probability is different from the product of the marginal.

  2. http://statisticalinnovations.com/technicalsupport/UG.html?tab=1#TabbedPanels1.

  3. The main municipalities that belong to the so called “leather district” are Arzignano, Chiampo, Lonigo, Montebello, Montecchio Maggiore, Montorso, Trissino and Zermeghedo. They are all part of the province of Vicenza.

  4. Design statistics can be obtained upon request from the corresponding author. There has been mounting evidence that design choice is not neutral to the inducement of attribute non-attendance behaviour (Yao et al. 2014). However, we are satisfied that our choice of design allows us to retrieve the data generating processes (DGP) of interest in this study. This was ascertained with a small-scale Monte Carlo study based on this design and on the DGP of relevance here.

  5. In order to evaluate the accuracy of the estimator in our application we generated 10 sets of pseudo-panel responses using the matrix of experimentally designed data and a sample of the same size as our real data. The data generating process (DGP) used the convergence values for our best estimation results with five preference and two scale classes. The ten estimates obtained from the simulated responses were sufficiently close to the DGP to reassure us of the accuracy of the estimator. Results are available upon request from the corresponding author.

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Authors and Affiliations

  1. Department of Land, Environment, Agriculture and Forestry, Agripolis, Via dell’Università 16, 35020, Legnaro, PD, Italy

    Mara Thiene

  2. Department of Economics, Waikato Management School, Room 2.13, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand

    Riccardo Scarpa

  3. Institute for Choice, The University of South Australia, Level 13, 140 Arthur St., North Sydney, NSW, 2060, Australia

    Jordan J. Louviere

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  1. Mara Thiene
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  2. Riccardo Scarpa
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  3. Jordan J. Louviere
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Correspondence to Mara Thiene.

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Thiene, M., Scarpa, R. & Louviere, J.J. Addressing Preference Heterogeneity, Multiple Scales and Attribute Attendance with a Correlated Finite Mixing Model of Tap Water Choice. Environ Resource Econ 62, 637–656 (2015). https://doi.org/10.1007/s10640-014-9838-0

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