Non-attendance to attributes in environmental choice analysis: a latent class specification

By D. Campbell, David A. Hensher, Riccardo Scarpa. 2011

231 citations recorded by the source corpus.

There is a growing literature on the design and use of stated choice experiments. Analysts have developed sophisticated ways of analysing such data, using a form of discrete choice model to identify the marginal (dis)utility associated with observed attributes linked to an alternative, as well as accounting for preference and scale heterogeneity. There is also a growing literature studying the attribute processing rules that respondents use as a way of simplifying the task of choosing. Using the latent class framework, we define classes based on rules that recognise the non-attendance to one or more attributes. These processing rules are postulated to be used in real markets as a form of cognitive rationalisation. The empirical study involves a choice amongst rural environmental landscape improvements in the Republic of Ireland. We estimate models and calculate a marginal willingness to pay (WTP) for four landscape improvements, and contrast it with the results from a model specification in which all attributes are assumed to be attended to with parameter preservation. We find that the marginal WTP is, on average, significantly higher when full attribute preservation specification is adopted, raising questions about the appropriateness of current practice that assume a fully compensatory attribute choice rule.

Subfields: Economics and Econometrics, Management, Monitoring, Policy and Law, Marketing

View Paper: https://www.semanticscholar.org/paper/396999772a85410dd4301695a457f56ddfbbb7fd

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Citations in the corpus

Contemporary Guidance for Stated Preference Studies (2017, background): “…1994; Kjaer et al. 2006), attribute nonattendance (Campbell, Hutchinson, and Scarpa 2008; Scarpa et al. 2009; Scarpa, Thiene, andHensher 2010; Campbell, Hensher, and Scarpa 2011; Hole 2011; Hensher, Rose, and Greene 2012; Hole, Kolstad, and Gyrd-Hansen 2013), omitted attributes (Petrin and…”
Stated and inferred attribute non-attendance in a design of designs approach (2014, methodology): “(2007) Mixed Logit Individual-level 0utility weights, expected maximum utility Higher WTP when accounting for ANA Campbell et al. (2008) MECLM Individual-level 0utility weights, parameterisation of the scale parameter based on attribute processing strategies Better model fit, lower WTP and different”
Inferring attribute non-attendance from stated choice data: implications for willingness to pay estimates and a warning for stated choice experiment design (2012, background): “Hess and Rose (2007), Hensher and Greene (2010) and Campbell et al. (2010) use a latent class framework as a way of capturing a probabilistic decision process, in which specific restrictions are imposed on the utility expressions for each class, to represent hypotheses of pre-defined attribute proce”
Attribute Processing, Heuristics, and Preference Construction in Choice Analysis (2009, background): “…(2008), Scarpa et al. (2009,2009a), Beharry and Scarpa (2008), Cantillo and Ortúzar (2005), Carlsson et al. (2008), Caussade et al. (2005) and Hensher et al. (2005, 2009), amongst others, are examples of a growing interest in the way that individuals evaluate a package of attributes…”
Food miles or carbon emissions? Exploring labelling preference for food transport footprint with a stated choice study (2013, methodology): “For such inference, we use ECLC models for panel data (Hess and Rose 2007; Scarpa et al. 2009; Campbell et al. 2011).”
It’s not that I don’t care, I just don’t care very much: confounding between attribute non-attendance and taste heterogeneity (2013, methodology): “This is reinforced by recent discussions in Hess and Hensher (2012), Campbell et al.”