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Bayesian Estimation of Willingness‐to‐pay Where Respondents Mis‐report Their Preferences *
Author(s) -
Balcombe K.,
Bailey A.,
Chalak A.,
Fraser I.
Publication year - 2007
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2006.00198.x
Subject(s) - willingness to pay , econometrics , mixed logit , bayesian probability , economics , logit , discrete choice , preference , estimation , bayesian inference , set (abstract data type) , hausman test , statistics , logistic regression , panel data , mathematics , fixed effects model , microeconomics , computer science , management , programming language
We introduce a modified conditional logit model that takes account of uncertainty associated with mis‐reporting in revealed preference experiments estimating willingness‐to‐pay (WTP). Like Hausman et al . [ Journal of Econometrics (1988) Vol. 87, pp. 239–269], our model captures the extent and direction of uncertainty by respondents. Using a Bayesian methodology, we apply our model to a choice modelling (CM) data set examining UK consumer preferences for non‐pesticide food. We compare the results of our model with the Hausman model. WTP estimates are produced for different groups of consumers and we find that modified estimates of WTP, that take account of mis‐reporting, are substantially revised downwards. We find a significant proportion of respondents mis‐reporting in favour of the non‐pesticide option. Finally, with this data set, Bayes factors suggest that our model is preferred to the Hausman model.