Distinguishing taste variation from error structure in discrete choice data

By Joffre Swait, A. Bernardino. 2000

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Correlation and scale in mixed logit models (2017, background): “Scale heterogeneity has become a widely discussed topic in recent years (see e.g. Fiebig et al., 2010; Swait and Bernardino, 2000).”
Empirical Identification in the Mixed Logit Model: Analysing the Effect of Data Richness (2008, background): “Several studies (Munizaga and Alvarez 2001, 2005; Hensher and Greene 2003; Bhat and Castelar 2002; Swait and Bernardino 2000; Hensher 1998) have investigated the difficulty of distinguishing different substitution patterns in a ML, referring mainly to the scale problem.”
Can scale and coefficient heterogeneity be separated in random coefficients models? (2012, result): “…relative sensitivities (which would arise if all heterogeneity was caused by scale differences) may be more common than previously thought and that differences in estimated utility parameters are primarily the result of scale differences (see e.g. Swait and Bernardino, 2000; Fiebig et al., 2010).”