Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model

Abstract

Multiple-discrete continuous choice models 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 face multiple resource constraints such as those associated with time, money, and 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.In this paper, we extend the multiple-discrete continuous extreme value (MDCEV) model to accommodate multiple constraints. The formulation uses a flexible and general utility function form, and is applicable to the case of complete demand systems as well as incomplete demand systems. The proposed MC-MDCEV model is applied to time-use decisions, where individuals are assumed to maximize their utility from time-use in one or more activities subject to monetary and time availability constraints. The sample for the empirical exercise is generated by combining time-use information from the 2008 American Time Use Survey and expenditure records from the 2008 U.S. Consumer Expenditure Survey. The estimation results show that preferences can get severely mis-estimated, and the data fit can degrade substantially, when only a subset of active resource constraints is used.

Review of Discrete-continuous Models in Energy and Transportation

“…With the use of this neo-structure utility function Bhat and Sen [4] propose the same utility structure for vehicle type and mileage use and then by use of Lagrangian form and applying Kuhn-Tucker condition find the optimal solution. For further detail one can see Bhat and Sen [4], Bhat [14], Spissu et al [12], Castro et al [17]. Still this model follows the original model just the assumption of the model is improved to make it closer to reality.…”

Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary data

“…The family of MDCEV models initially developed by Bhat (2005) and subsequently extended in different directions (Bhat, 2008;Castro et al, 2012;Pinjari and Bhat, 2010b) represents the state of the art in modelling multiple discrete-continuous choices. Travel behaviour has been the main field of application of this modelling framework, for example in the study of the choice of vehicle type and mileage , vacationrelated decisions (Pinjari and Sivaraman, 2013) and to type and duration of activities (Bhat, 2005;Kapur and Bhat, 2007).…”

Income effects, cost damping and the value of time: theoretical properties embedded within practical travel choice models

“…Becker 1965;Oort 1969;Evans 1972), through to more recent works which have re-conceptualised and/or extended the maximisation problem (e.g. Jara-Díaz 2003; Castro et al 2012). Accordingly, we assume that an individual's 3 unconditional direct utility is a function of the quantity of goods consumed and the time spent in consuming these goods, subject to income, time and a 'time consumption' relationship between income and time.…”