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Using a Hicksian approach to cost-benefit analysis in discrete choice: An empirical analysis of a transportation corridor simulation model

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  • Hau, Timothy D.
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    Abstract

    The general equilibrium effects of alternative transportation policy proposals are analyzed using a multi-modal, benefit-cost model of demand and supply within a discrete choice framework. Using the expenditure function as an empirical construct yields Hicksian consumer's surplus measures, which are usually not directly observable. Despite the absence of data on the complete budget and only mode choice data, the procedure we use to prove the stochastic analog of Roy's Identity identifies the entire indirect utility function, and hence the explicit expenditure function. The model is applied to a corridor simulation model of Interstate 580 of the San Francisco Bay Area. Travel demand is calibrated using multinomial logit on a sample of work-trip commuters. Detailed modal costs are estimated and entered as parameters of the demand model. The Scarf algorithm equilibrates the analytic disaggregated demand model and a parallel analytic supply model. Our forecast is based on a synthetic sample of households generated by an efficient program that uses census data. The benefits of policy alternatives, such as marginal (resource) cost pricing are computed and discussed.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 21 (1987)
    Issue (Month): 5 (October)
    Pages: 339-357

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    Handle: RePEc:eee:transb:v:21:y:1987:i:5:p:339-357

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    Cited by:
    1. Batley, Richard & Nicolás Ibáñez, J., 2013. "On the path independence conditions for discrete-continuous demand," Journal of choice modelling, Elsevier, vol. 7(C), pages 13-23.
    2. Zanakis, Stelios H. & Mandakovic, Tomislav & Gupta, Sushil K. & Sahay, Sundeep & Hong, Sungwan, 1995. "A review of program evaluation and fund allocation methods within the service and government sectors," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 59-79, March.

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