Extended discrete choice models : integrated framework, flexible error structures, and latent variables

By Joan L. Walker. 2001

459 citations recorded by the source corpus.

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Citations in the corpus

Endogeneity in Residential Location Choice Models (2006, unknown): “An equivalent procedure to overcome this problem and increase efficiency could be pursued by estimating both steps simultaneously by using, for example, a latent-variable approach (14).”
Independent Mobility and Mode Choice for School Transportation: A Review and Framework for Future Research (2013, methodology): “attitudes can be studied as latent variables) (Walker, 2001), existing quantitative Independent Mobility and Mode Choice for School Transportation 25”
Can scale and coefficient heterogeneity be separated in random coefficients models? (2012, methodology): “Error components or models with random alternative specific constants have also been used to accommodate scale differences (see e.g. Walker, 2001; Brownstone et al., 2000), but the main interest has generally been on heteroscedasticity across alternatives, and even if the scale heterogeneity…”
Empirical Identification in the Mixed Logit Model: Analysing the Effect of Data Richness (2008, background): “On the other hand, we usually refer to an empirical identification problem when the model is estimable in principle (because it is theoretically identified) but the data cannot support it (Walker 2001).”
Allowing for intra-respondent variations in coefficients estimated on repeated choice data (2009, methodology): “Secondly, the model allows for a relaxation of the IID assumption of the MNL model, in what is typically referred to as the error components logit (ECL) model, discussed for example by Brownstone and Train (1999) and Walker (2001).”
Mixed Logit (or Logit Kernel) Model: Dispelling Misconceptions of Identification (2002, methodology): “The theoretical proofs are left to more technical papers that have been written in parallel, Ben-Akiva et al. (1) or Walker (2), heretofore referred to as the parallel papers.”
Estimation of discrete choice models: extending BIOGEME (2009, background): “Among them, hybrid choice models (Ben-Akivaet al. (2002), Walker (2001)) have received a considerable attention.”
Evaluating farmers’ likely participation in a payment programme for water quality protection in the UK uplands (2013, methodology): “Latent class model The latent class model (LCM) provides a more flexible method for capturing heterogeneity of preferences (Heckman and Singer 1984; Wedel and Kamakura 2000; Walker 2001; Boxall and Adamowicz 2002).”
Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently? (2009, methodology): “Such heteroscedasticity across alternatives is typically accommodated either in a heteroscedastic extreme value (HEV) model, as discussed by Bhat (1995) or through an appropriate ECL specification of the MMNL model, as discussed by Walker (2001).”
Integrated driving behavior modeling (2007, background): “The following conditions must hold for a normalization to be valid (Walker 2001):”
On the Treatment of Repeated Observations in Panel Data: Efficiency of Mixed Logit Parameter Estimates (2011, methodology): “The usual way to incorporate panel correlation under the pure error-components approach consists of adding an error component to (n-1) of the available alternatives, otherwise for identifiability reasons the model cannot be estimated (Walker, 2001).”
Willingness-to-Pay Estimation with Mixed Logit Models: Some New Evidence (2005, background): “Discussions on the stability and robustness of classically estimated parameters are available in the existing literature (Bhat, 2001; Garrido and Silva, 2004; Walker, 2001).”
Incorporating pro-environmental preferences towards green automobile technologies through a Bayesian hybrid choice model (2013, methodology): “…reflect individual tastes, needs, values, goals and capabilities that develop over time, and are affected by knowledge, experience and external factors, such as the socioeconomic characteristics of the decision-maker (Ajzen 2001); for a discussion related to transportation see Walker (2001).”