Comparing models of unobserved heterogeneity in environmental choice experiments

Choice experiments have become a widespread approach to non-market environmental valuation. Given the vast range of public opinions towards environmental management changes, it is desirable that analysis of discrete choice data accounts for the possibility of unobserved heterogeneity amongst the population. There is, however, no consensus about the best way to model individual heterogeneity. This paper presents four approaches to modelling heterogeneity that are increasingly used in the literature. Latent class, mixed logit, scaled multinomial logit and generalised mixed logit (GMXL) models are estimated using case study data for catchment environmental management in Australia. A GMXL model that accounts for preference and scale heterogeneity performs best. I evaluate the impacts of models on welfare estimates and discuss the merits of each modelling approach.


Issue Date:
Feb 10 2013
Publication Type:
Working or Discussion Paper
PURL Identifier:
http://purl.umn.edu/144447
Total Pages:
24
JEL Codes:
C01; Q51 and Q59
Series Statement:
Working Paper
1301




 Record created 2017-04-01, last modified 2017-08-27

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