Copula-based direct utility models for correlated choice alternatives

Chul Kim (), Duk Bin Jun () and Sungho Park ()
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Chul Kim: Baruch College
Duk Bin Jun: Korea Advanced Institute of Science & Technology
Sungho Park: Seoul National University

Quantitative Marketing and Economics (QME), 2022, vol. 20, issue 1, No 3, 69-99

Abstract: Abstract We propose a general framework of copula-based direct utility models and suggest two approaches (Gaussian and FGM approaches) that can accommodate correlations among unobserved utilities. We investigate how and in which directions the biases in parameter estimates of direct utility models occur when error correlations are ignored. Furthermore, we provide practical guidance to empirical researchers by examining strengths and weaknesses of the two suggested approaches. We find that the Gaussian copula approach is flexible but computationally demanding. On the other hand, the proposed FGM copula approach substantially reduces computational complexity, while fully utilizing the maximum range of correlations that is theoretically attainable by the generalized FGM copulas. We apply the proposed approaches to various contexts including grocery scanner panel, experimental, and conjoint datasets and demonstrate that overlooking the correlations may bias managerial metrics and result in suboptimal decisions (e.g., optimal package configuration, monetary equivalents of attribute levels).

Keywords: Copula; Direct utility models; Multiple-discrete/continuous choice; Gaussian copula; FGM copula (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11129-022-09249-2

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