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Hybrid choice models: the identification problem

In: Handbook of Choice Modelling

Author

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  • Akshay Vij
  • Joan L. Walker

Abstract

Choice modelling is an increasingly important technique for forecasting and valuation, with applications in fields such as transportation, health and environmental economics. For this reason it has attracted attention from leading academics and practitioners and methods have advanced substantially in recent years. This Handbook, composed of contributions from senior figures in the field, summarises the essential analytical techniques and discusses the key current research issues. It will be of interest to academics, students and practitioners in a wide range of areas.

Suggested Citation

  • Akshay Vij & Joan L. Walker, 2014. "Hybrid choice models: the identification problem," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 22, pages 519-564, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:14820_22
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    References listed on IDEAS

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    1. Ricardo Daziano & Denis Bolduc, 2013. "Covariance, identification, and finite-sample performance of the MSL and Bayes estimators of a logit model with latent attributes," Transportation, Springer, vol. 40(3), pages 647-670, May.
    2. Terence Reilly & Robert M. O'Brien, 1996. "Identification of Confirmatory Factor Analysis Models of Arbitrary Complexity," Sociological Methods & Research, , vol. 24(4), pages 473-491, May.
    3. Terence Reilly, 1995. "A Necessary and Sufficient Condition for Identification of Confirmatory Factor Analysis Models of Factor Complexity One," Sociological Methods & Research, , vol. 23(4), pages 421-441, May.
    4. Chiou, Lesley & Walker, Joan L., 2007. "Masking identification of discrete choice models under simulation methods," Journal of Econometrics, Elsevier, vol. 141(2), pages 683-703, December.
    5. Bolduc, Denis, 1999. "A practical technique to estimate multinomial probit models in transportation," Transportation Research Part B: Methodological, Elsevier, vol. 33(1), pages 63-79, February.
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    Cited by:

    1. Hwang, Jinuk & Kim, Seheon, 2023. "Autonomous vehicle transportation service for people with disabilities: Policy recommendations based on the evidence from hybrid choice model," Journal of Transport Geography, Elsevier, vol. 106(C).
    2. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    3. Kassahun, Habtamu Tilahun & Swait, Joffre & Jacobsen, Jette Bredahl, 2021. "Distortions in willingness-to-pay for public goods induced by endemic distrust in institutions," Journal of choice modelling, Elsevier, vol. 39(C).
    4. Barrientos, Manuel & Lavin, Felipe Vasquez & Ponce Oliva, Roberto D., 2020. "Assessing the Incorporation of Latent Variables in the Estimation of the Value of a Statistical Life," EfD Discussion Paper 20-22, Environment for Development, University of Gothenburg.
    5. Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
    6. Nikiforiadis, Andreas & Paschalidis, Evangelos & Stamatiadis, Nikiforos & Paloka, Ntonata & Tsekoura, Eleni & Basbas, Socrates, 2023. "E-scooters and other mode trip chaining: Preferences and attitudes of university students," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    7. Márquez, Luis & Pico, Ricardo & Cantillo, Víctor, 2018. "Understanding captive user behavior in the competition between BRT and motorcycle taxis," Transport Policy, Elsevier, vol. 61(C), pages 1-9.
    8. Lehmann, Nico & Sloot, Daniel & Ardone, Armin & Fichtner, Wolf, 2022. "Willingness to pay for regional electricity generation – A question of green values and regional product beliefs?," Energy Economics, Elsevier, vol. 110(C).
    9. Lehmann, Nico & Sloot, Daniel & Schüle, Christopher & Ardone, Armin & Fichtner, Wolf, 2023. "The motivational drivers behind consumer preferences for regional electricity – Results of a choice experiment in Southern Germany," Energy Economics, Elsevier, vol. 120(C).
    10. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    11. Márquez, Luis & Alfonso A, Julieth V. & Poveda, Juan C., 2019. "In-vehicle crowding: Integrating tangible attributes, attitudes, and perceptions in a choice context between BRT and metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 452-465.
    12. Soto, Jose J. & Márquez, Luis & Macea, Luis F., 2018. "Accounting for attitudes on parking choice: An integrated choice and latent variable approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 65-77.
    13. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    14. Dekker, Thijs & Hess, Stephane & Arentze, Theo & Chorus, Caspar, 2014. "Incorporating needs-satisfaction in a discrete choice model of leisure activities," Journal of Transport Geography, Elsevier, vol. 38(C), pages 66-74.
    15. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    16. Hélène Bouscasse, 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers hal-01795630, HAL.
    17. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
    18. Schmid, Basil & Axhausen, Kay W., 2019. "In-store or online shopping of search and experience goods: A hybrid choice approach," Journal of choice modelling, Elsevier, vol. 31(C), pages 156-180.
    19. Hess, Stephane & Spitz, Greg & Bradley, Mark & Coogan, Matt, 2018. "Analysis of mode choice for intercity travel: Application of a hybrid choice model to two distinct US corridors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 547-567.
    20. Manca, Francesco & Sivakumar, Aruna & Daina, Nicolò & Axsen, Jonn & Polak, John W, 2020. "Modelling the influence of peers’ attitudes on choice behaviour: Theory and empirical application on electric vehicle preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 278-298.

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