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Allowing for complementarity and rich substitution patterns in multiple discrete–continuous models

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  • Bhat, Chandra R.
  • Castro, Marisol
  • Pinjari, Abdul Rawoof

Abstract

Many consumer choice situations are characterized by the simultaneous demand for multiple alternatives that are imperfect substitutes for one another, along with a continuous quantity dimension for each chosen alternative. To model such multiple discrete–continuous choices, most multiple discrete–continuous models in the literature use an additively-separable utility function, with the assumption that the marginal utility of one good is independent of the consumption of another good. In this paper, we develop model formulations for multiple discrete–continuous choices that accommodate rich substitution structures and complementarity effects in the consumption patterns, and demonstrate an application of the model to transportation-related expenditures using data drawn from the 2002 Consumer Expenditure (CEX) Survey.

Suggested Citation

  • Bhat, Chandra R. & Castro, Marisol & Pinjari, Abdul Rawoof, 2015. "Allowing for complementarity and rich substitution patterns in multiple discrete–continuous models," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 59-77.
    • Handle: RePEc:eee:transb:v:81:y:2015:i:p1:p:59-77
    DOI: 10.1016/j.trb.2015.08.009
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    Cited by:

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    2. Pellegrini, Andrea & Pinjari, Abdul Rawoof & Maggi, Rico, 2021. "A multiple discrete continuous model of time use that accommodates non-additively separable utility functions along with time and monetary budget constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 37-53.
    3. Neill, Clinton L. & Lahne, Jacob, 2022. "Matching reality: A basket and expenditure based choice experiment with sensory preferences," Journal of choice modelling, Elsevier, vol. 44(C).
    4. Palma, David & Hess, Stephane, 2022. "Extending the Multiple Discrete Continuous (MDC) modelling framework to consider complementarity, substitution, and an unobserved budget," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 13-35.
    5. Saxena, Shobhit & Pinjari, Abdul Rawoof & Paleti, Rajesh, 2022. "A multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP): Modelling framework for episode-level activity participation and time-use analysis," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 259-283.
    6. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.
    7. 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.
    8. Bonnet, Céline & Richards, Timothy J., 2016. "Models of Consumer Demand for Differentiated Products," TSE Working Papers 16-741, Toulouse School of Economics (TSE).
    9. Kidokoro, Yukihiro, 2016. "A micro foundation for discrete choice models with multiple categories of goods," Journal of choice modelling, Elsevier, vol. 19(C), pages 54-72.
    10. Astroza, Sebastian & Guarda, Pablo & Carrasco, Juan Antonio, 2022. "Modeling the relationship between food purchasing, transport, and health outcomes: Evidence from Concepcion, Chile," Journal of choice modelling, Elsevier, vol. 42(C).
    11. Andrea Pellegrini & Igor Sarman & Rico Maggi, 2021. "Understanding tourists’ expenditure patterns: a stochastic frontier approach within the framework of multiple discrete–continuous choices," Transportation, Springer, vol. 48(2), pages 931-951, April.
    12. Pinjari, Abdul Rawoof & Bhat, Chandra, 2021. "Computationally efficient forecasting procedures for Kuhn-Tucker consumer demand model systems: Application to residential energy consumption analysis," Journal of choice modelling, Elsevier, vol. 39(C).
    13. 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.
    14. Wen Lin, 2023. "The effect of product quantity on willingness to pay: A meta‐regression analysis of beef valuation studies," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 646-663, July.
    15. Sanghak Lee & Sunghoon Kim & Sungho Park, 2022. "A sequential choice model for multiple discrete demand," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 141-178, June.
    16. Saxena, Shobhit & Pinjari, Abdul Rawoof & Roy, Ananya & Paleti, Rajesh, 2021. "Multiple discrete-continuous choice models with bounds on consumptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 237-265.
    17. 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.

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