Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/321717 
Year of Publication: 
2020
Citation: 
[Journal:] Bio-based and Applied Economics (BAE) [ISSN:] 2280-6172 [Volume:] 9 [Issue:] 3 [Year:] 2020 [Pages:] 305-324
Publisher: 
Firenze University Press, Florence
Abstract: 
This paper explores the potential usefulness and possible pitfalls of using integrated choice and latent variable models (hybrid choice models) on stated choice data to inform policy. Using a series of Monte-Carlo simulations, we consider how model selection depends on the strength of relationship between the latent variable and preferences and the strength of relationship between the latent variable and the indicator. Our findings show that integrated choice and latent variable models are difficult to estimate, even when the data generating process is known. Ultimately, we show that their use should be driven by the analyst's belief about the strength of correlations between preferences, the latent variable and indicator. We discuss the implications of our results for policy.
Subjects: 
Stated preferences
choice modelling
integrated choice and latent variables
hybrid choice model
JEL: 
C25
H41
Q51
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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