Generalized extreme value (GEV)-based error structures for multiple discrete-continuous choice models

Abdul Rawoof Pinjari

Transportation Research Part B: Methodological, 2011, vol. 45, issue 3, 474-489

Abstract: This paper formally derives the class of multiple discrete-continuous generalized extreme value (MDCGEV) models, a general class of multiple discrete-continuous choice models based on generalized extreme value (GEV) error specifications. Specifically, the paper proves the existence of, and derives the general form of, closed-form consumption probability expressions for multiple discrete-continuous choice models with GEV-based error structures. In addition to deriving the general form, the paper derives a compact and readily usable form of consumption probability expressions that can be used to estimate multiple discrete-continuous choice models with general cross-nested error structures. The cross-nested version of the MDCGEV model is applied to analyze household annual expenditure patterns in various transportation-related expenses using data from a Consumer Expenditure Survey in the United States. Model estimation results and predictive log-likelihood based validation tests indicate the superiority of the cross-nested model over the mutually exclusively nested and non-nested model specifications. Further, the cross-nested model was amenable to the accommodation of socio-demographic heterogeneity in inter-alternative covariance across decision-makers through a parameterization of the allocation parameters.

Keywords: Discrete-continuous; models; Kuhn-Tucker; (KT); demand; systems; Multiple; discreteness; MDCEV; GEV; Cross-nested; error; structure (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (22)

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