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Modelling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture

Sergio Colombo, Nick Hanley and Jordan Louviere

No 2008-28, Stirling Economics Discussion Papers from University of Stirling, Division of Economics

Abstract: Stated choice models based on the random utility framework are becoming increasingly popular in the applied economics literature. The need to account for respondents' preference heterogeneity in such models has motivated researchers in agricultural, environmental, health and transport economics to apply random parameter logit and latent class models. In most of the published literature these models incorporate heterogeneity in preferences through the systematic component of utility. An alternative approach is to investigate heterogeneity through the random component of utility, and covariance heterogeneity models are one means of doing this. In this paper we compare these alternative ways of incorporating preference heterogeneity in stated choice models and evaluate how the selection of approach affects welfare estimates in a given empirical application. We find that a Latent Class approach fits our data best but all the models perform well in terms of out-of-sample predictions. Finally, we discuss what criteria a researcher can use to decide which approach is most appropriate for a given data set.

Keywords: welfare measures; error component models; random parameter logit model; preference heterogeneity; latent class model; landscape values; agri-environmental policy; covariance heterogeneity model; choice experiments (search for similar items in EconPapers)
Date: 2008-12
New Economics Papers: this item is included in nep-agr, nep-dcm, nep-ecm, nep-exp and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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http://hdl.handle.net/1893/598

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Journal Article: Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture (2009) Downloads
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