On finite sample performance of confidence intervals methods for willingness to pay measures
Edoardo Marcucci () and
Luisa Scaccia ()
Transportation Research Part A: Policy and Practice, 2015, vol. 82, issue C, 169-192
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.
Keywords: Confidence interval; Willingness to pay; Choice modeling; Elasticity; Standard error (search for similar items in EconPapers)
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