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A new closed form multiple discrete-continuous extreme value (MDCEV) choice model with multiple linear constraints

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  • Mondal, Aupal
  • Bhat, Chandra R.

Abstract

Traditional multiple-discrete continuous choice models that have been formulated and applied in recent years consider a single linear resource constraint, which, when combined with consumer preferences, determines the optimal consumption point. However, in reality, consumers may face multiple resource constraints, such as those associated with time, money, and storage capacity. Ignoring such multiple constraints and instead using a single constraint can, and in general will, lead to poor data fit and inconsistent preference estimation, which can then have a serious negative downstream effect on forecasting and welfare/policy analysis. Unlike earlier attempts to address this multiple constraint situation, we formulate a new multiple-constraint (MC) multiple discrete continuous extreme value (MDCEV) model (or the MC-MDCEV model) that retains a closed-form probability structure and is as simple to estimate as the MDCEV model with one constraint. We achieve this by assuming a type-I extreme value distribution for the error term in its minimization form in the baseline utility preference of each good rather than a maximization form as in Bhat's (2005; 2008) original MDCEV formulation. The statistical foundation of the proposed model is based on the fact that the difference between a minimal type-I extreme value random variable with scale σ and the weighted sum of the exponential of standardized minimal type-I extreme value random variables (scaled up by σ) leads to an apparently new multivariate distribution that has an elegant and closed-form survival distribution function. Results from a simulation experiment show that our proposed model substantially outperforms single-constraint models; the results also highlight the serious mis-estimation that is likely to occur if only a subset of active constraints is used. The proposed model is applied to a case of week-long activity participation where individuals are assumed to maximize their utility from time-use subject to time and money budgets.It is hoped that our proposed simple closed-form multi-constraint MDCEV model will contribute to a new direction of application possibilities and to new research into situations where consumers face multiple constraints within a multiple discrete-continuous choice context.

Suggested Citation

  • Mondal, Aupal & Bhat, Chandra R., 2021. "A new closed form multiple discrete-continuous extreme value (MDCEV) choice model with multiple linear constraints," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 42-66.
  • Handle: RePEc:eee:transb:v:147:y:2021:i:c:p:42-66
    DOI: 10.1016/j.trb.2021.03.005
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    References listed on IDEAS

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    1. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
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    4. Calastri, Chiara & Giergiczny, Marek & Zedrosser, Andreas & Hess, Stephane, 2023. "Modelling activity patterns of wild animals - An application of the multiple discrete-continuous extreme value (MDCEV) model," Journal of choice modelling, Elsevier, vol. 47(C).
    5. Bhat, Chandra R., 2022. "A new closed-form two-stage budgeting-based multiple discrete-continuous model," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 162-192.
    6. Saxena, Shobhit & Pinjari, Abdul Rawoof & Bhat, Chandra R., 2022. "Multiple discrete-continuous choice models with additively separable utility functions and linear utility on outside good: Model properties and characterization of demand functions," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 526-557.

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