nep-dcm New Economics Papers
on Discrete Choice Models
Issue of 2013‒08‒10
five papers chosen by
Edoardo Marcucci
Universita' di Roma Tre

  1. Using elicitation mechanisms to estimate the demand for nutritious maize: Evidence from experiments in rural Ghana By Banerji, A.; Chowdhury, Shyamal K.; de Groote, Hugo; Meenakshi, Jonnalagadda V.; Haleegoah, Joyce; Ewoo, Manfred
  2. Incremental Accessibility Benefits and HOT Lane Subscription Choice By Andrew Owen; David Levinson
  3. Which Station? Access Trips and Bike Share Route Choice By Jessica Schoner; David Levinson
  4. A survival analysis-based choice set formation approach for single-destination choice using GPS travel data By Arthur (Yan) Huang; David Levinson
  5. Mixed Data Kernel Copulas By Jeffrey S. Racine

  1. By: Banerji, A.; Chowdhury, Shyamal K.; de Groote, Hugo; Meenakshi, Jonnalagadda V.; Haleegoah, Joyce; Ewoo, Manfred
    Abstract: In this paper we assess (a) consumers’ willingness to pay (WTP) for a recently developed variety of maize that is high in provitamin A in the context of a public health intervention and (b) the performance of three elicitation mechanisms in estimating WTP in a field experiment in Ghana. The mechanisms that we used for elicitation are the Becker-DeGroot-Marschak (BDM) mechanism, kth price auction, and choice experiment. The basic design of the experiment involved random allocation of consumers to one of three elicitation methods. This was augmented to include treatment arms to address the effect of (1) participation fees and (2) nutrition information on WTP.
    Keywords: Ghana, West Africa, Africa south of Sahara, Africa, Biofortification, maize, Provitamin A, Vitamin A, demand
    Date: 2013
  2. By: Andrew Owen; David Levinson (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)
    Abstract: This paper presents the results of an investigation into the factors contributing to toll lane subscription choice using data from the MnPASS HOT lane system operated by the Minnesota Department of Transportation. A binomial logit model is estimated which predicts the likelihood that a household will have a subscription to the MnPASS system based on aggregate characteristics of the surrounding area. Variables in this model include demographic factors as well as an estimate of the incremental accessibility benefit provided by the MnPASS system. This benefit is estimated using detailed accessibility calculations. The model achieves a pseudo-r-squared value of 0.634, and analysis of the results suggest that incremental accessibility benefits play a statistically and practically significant role in determining how likely households are to hold a toll lane subscription.
    Keywords: road pricing, travel behavior, subscription choice, HOT lanes, accessibility
    JEL: O18 R48
    Date: 2013
  3. By: Jessica Schoner; David Levinson (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)
    Abstract: Bike share systems are an emerging technology in the United States and worldwide, but little is known about how people integrate bike share trip segments into their daily travel. Through this research, we attempt to fill this knowledge gap by studying how people navigate from place to place using the Nice Ride Minnesota bike share system in Minneapolis and St. Paul. We develop a theoretical model for bike share station choice inspired by research on transit route choice literature. We then model people’s choice of origin station using a conditional logit model to evaluate their sensitivity to time spent walking, deviation from the shortest path, and a set of station amenity and neighborhood control variables. As expected, people prefer to use stations that do not require long detours out of the way to access. However, commuters and non-work travelers differ in how they value the walking portion of their trip, and what station amenities and neighborhood features increase a station’s utility. The results from this study will be important for planners who need a better understanding of bike share user behavior in order to design or optimize their system. The findings also provide a strong foundation for future study about comprehensive route choice analysis of this new bicycling technology.
    Keywords: destination choice, station choice, bicycling, bike sharing
    JEL: R41 R42
    Date: 2013
  4. By: Arthur (Yan) Huang; David Levinson (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)
    Abstract: WThis research investigates how land use and road network structure influence home-based single-destination choice in the context of trip chains, using the in-vehicle GPS travel data in the Minneapolis-St. Paul Metropolitan area. We propose a new choice set formation approach which combines survival analysis and random selection. Our empirical findings reveal that: (1) Accessibility and diversity of services at the destination influences individuals’ destination choice. (2) Route-specific network measures such as turn index, speed discontinuity, and trip chains’ travel time saving ratio also display statistically significant effects on destination choice. Our approach contributes to methodologies in modeling destination choice. The results improve our understanding on travel behavior and have implications on transportation and land use planning.
    Keywords: destination choice, GPS, accessibility, non-work travel
    JEL: R14 R41 R42
    Date: 2013
  5. By: Jeffrey S. Racine
    Abstract: A number of approaches towards the kernel estimation of copula have appeared in the literature. Most existing approaches use a manifestation of the copula that requires kernel density estimation of bounded variates lying on a d-dimensional unit hypercube. This gives rise to a number of issues as it requires special treatment of the boundary and possible modifications to bandwidth selection routines, among others. Furthermore, existing kernel-based approaches are restricted to continuous date types only, though there is a growing interest in copula estimation with discrete marginals (see e.g. Smith & Khaled (2012) for a Bayesian approach). We demonstrate that using a simple inversion method (cf Nelsen (2006), Fermanian & Scaillet (2003)) can sidestep boundary issues while admitting mixed data types directly thereby extending the reach of kernel copula estimators. Bandwidth selection proceeds by the recently proposed method of Li & Racine (2013). Furthermore, there is no curse-of-dimensionality for the kernel-based copula estimator (though there is for the copula density estimator, as is the case for existing kernel copula density methods).
    Date: 2013–08

This nep-dcm issue is ©2013 by Edoardo Marcucci. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.