Modifying willingness to pay estimates where respondents mis-report their preferences
Kelvin Balcombe, Alastair Bailey, Ali Chalak, Iain Fraser
Abstract
Kelvin Balcombe, Alastair Bailey, Ali Chalak, Iain Fraser
Abstract
The likelihood for the Logit model is modified, so as to take account of uncertainty associated with mis-reporting in stated preference experiments estimating willingness to pay (WTP). Monte Carlo results demonstrate the bias imparted to estimates where there is mis-reporting. The approach is applied to a data set examining consumer preferences for food produced employing a nonpesticide technology. Our modified approach leads to WTP that are substantially downwardly revised.
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The likelihood for the Logit model is modified, so as to take account of uncertainty associated with mis-reporting in stated preference experiments estimating willingness to pay (WTP). Monte Carlo results demonstrate the bias imparted to estimates where there is mis-reporting. The approach is applied to a data set examining consumer preferences for food produced employing a nonpesticide technology. Our modified approach leads to WTP that are substantially downwardly revised.
Key concepts: Willingness to pay, Econometrics, Mixed logit, Preference, Economics, Logit, Set (abstract data type), Monte Carlo method