2013 Session: 391

• Hybrid Models of Random Utility Maximization and Random Regret Minimization: Results from Two Empirical Studies
  Abstract: This paper shows how the co-existence of different decision rules can be accommodated in hybrid discrete choice-models. Specifically, the paper presents a generic hybrid model specification that allows for some attributes being processed using conventional linear-additive utility-maximization based rules, while others are being processed using regret-minimization based rules. We show that on two revealed and stated choice datasets hybrid models outperform – in terms of model fit – choice models where all attributes are assumed to be processed by means of one and the same decision rule. However, on our data differences between models are very small. Implications, in terms of marginal Willingness-to-Pay measures (WtP), are derived for the different hybrid model-specifications and applied in the context of the two datasets. It is found that in the context of our data hybrid WtP-measures differ substantially from conventional utility-based WtP-measures, and that the hybrid WtP-specifications allow for a richer, because choice set-specific, interpretation of the trade-offs that people make.
  Authors: Chorus, Caspar; Rose, John Matthew; Hensher, David A.
  Authors: Chorus, Caspar; Rose, John Matthew; Hensher, David A.
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-0085
• When Explanatory Variables Are Unobserved: Example of Latent Income
  Abstract: Income is recognised as a key variable influencing consumer behaviour, most notably in terms of a strong link with cost sensitivity. This is supported by a large body of empirical evidence using choice modelling techniques. Unfortunately, income information as available in most datasets used for modelling is affected by a number of issues; (1) it is measured as a categorical rather than as a continuous variable, (2) many respondents fail to provide income information, (3) the reported income is potentially correlated with other unobserved factors, and (4) there is scope for deliberate under or overstating of income by respondents. In the present paper, we propose to deal with these issues by replacing reported income with a latent income variable in the choice models, which at the same time is also used to explain the stated income in a measurement model. The proposed structure has a number of theoretical advantages. In comparison with using stated income, we should deal with some of the measurement error and bias issues. In comparison with using imputation of missing values, our model draws not just on data on stated income for those respondents without missing information, but the simultaneous estimation with the choice model means that the observed choices also inform the latent income variable. Two empirical applications using stated and revealed preference data illustrate the good performance of the method in practice.
  Authors: Hess, Stephane; Daly, Andrew; Dumont, Jeffrey; Sanko, Nobuhiro
  Authors: Hess, Stephane; Daly, Andrew; Dumont, Jeffrey; Sanko, Nobuhiro
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-2426
• Estimating Nested Logit Models with Censored Data
  Abstract: In this paper, we introduce a methodology for estimating parameters of a nested logit model when decision makers who choose one of the alternatives are systematically excluded from the sample data that is used to estimate the model (i.e., censored). Unlike existing methods for estimating discrete choice model parameters with censored data, which require exogenous information beyond the specification of the model to be estimated and the available sampled observations, the proposed method requires no additional outside information. We demonstrate empirically that this approach is able to recover not only generic model parameters that apply to common attributes of all alternatives, but also parameters for alternative specific constants and variables associated with both observed and censored alternatives. While the standard errors of the estimated parameters are larger than those of models estimated with uncensored data, censored data methods still hold great potential for applications where uncensored data is expensive or impossible to collect.
  Authors: Newman, Jeffrey; Ferguson, Mark; Garrow, Laurie A.
  Authors: Newman, Jeffrey; Ferguson, Mark; Garrow, Laurie A.
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-3340
• A New Estimation Approach for the Multiple Discrete-Continuous Probit (MDCP) Choice Model
  Abstract: This paper develops a blueprint to apply Bhat’s (2011) Maximum Approximate Composite Marginal Likelihood (MACML) inference approach for the estimation of multiple discrete-continuous probit (MDCP) models. A simulation exercise is undertaken to evaluate the ability of the proposed approach to recover parameters from a cross-sectional MDCP model. The results show that the MACML approach does very well in recovering parameters, as well as appears to accurately capture the curvature of the Hessian of the log-likelihood function. The paper also demonstrates the application of the proposed approach through a study of individuals’ recreational choice among alternative destination locations and the number of trips to each recreational destination location, using data drawn from the 2004-2005 Michigan statewide household travel survey.
  Authors: Bhat, Chandra R.; Castro, Marisol; Khan, Mubassira
  Authors: Bhat, Chandra R.; Castro, Marisol; Khan, Mubassira
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-3828
• Hybrid Models of Random Utility Maximization and Random Regret Minimization: Results from Two Empirical Studies
  Authors: Chorus, Caspar
  Authors: Chorus, Caspar
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-0085
• When Explanatory Variables Are Unobserved: Example of Latent Income
  Authors: Hess, Stephane
  Authors: Hess, Stephane
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-2426
• A New Estimation Approach for the Multiple Discrete-Continuous Probit (MDCP) Choice Model
  Authors: Castro, Marisol
  Authors: Castro, Marisol
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 391
  Paper Number: 13-3828