Highlights Reliable WTP measures are fundamental in transportation economics. The finite sample distribution of WTP estimator is not known. A systematic comparison of all the existing methods for WTP confidence intervals. Monte Carlo study within a multinomial logit model. Guidelines for choosing, under different conditions, an appropriate method.
Abstract This paper systematically compares finite sample performances of methods to build confidence intervals for willingness to pay measures in a choice modeling context. It contributes to the field by also considering methods developed in other research fields. Various scenarios are evaluated under an extensive Monte Carlo study. Results show that the commonly used Delta method, producing symmetric intervals around the point estimate, often fails to account for skewness in the estimated willingness to pay distribution. Both the Fieller method and the likelihood ratio test inversion method produce more realistic confidence intervals for small samples. Some bootstrap methods also perform reasonably well, in terms of effective coverage. Finally, empirical data are used to illustrate an application of the methods considered.
On finite sample performance of confidence intervals methods for willingness to pay measures
Transportation Research Part A: Policy and Practice ; 82 ; 169-192
2015-09-02
24 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Confidence intervals of willingness-to-pay for random coefficient logit models
Online Contents | 2013
|Evaluation of the Confidence Intervals
Springer Verlag | 2018
|