This paper systematically compares methods to build confidence intervals for willingness to pay measures in a discrete choice context. It contributes to the literature by including methods developed in other research fields. Monte Carlo simulations are used to assess the performance of all the methods considered. The various scenarios evaluated reveal a certain skewness in the estimated willingness to pay distribution. This should be reflected in the confidence intervals. Results show that the commonly used Delta method, producing symmetric intervals around the point estimate, often fails to account for such a skewness. Both the Fieller method and the likelihood ratio test inversion method produce more realistic confidence intervals. Some bootstrap methods also perform reasonably well. Finally, empirical data are used to illustrate an application of the methods considered

Willingness to pay confidence interval estimation methods. Comparisons and extensions

SCACCIA, LUISA
2014-01-01

Abstract

This paper systematically compares methods to build confidence intervals for willingness to pay measures in a discrete choice context. It contributes to the literature by including methods developed in other research fields. Monte Carlo simulations are used to assess the performance of all the methods considered. The various scenarios evaluated reveal a certain skewness in the estimated willingness to pay distribution. This should be reflected in the confidence intervals. Results show that the commonly used Delta method, producing symmetric intervals around the point estimate, often fails to account for such a skewness. Both the Fieller method and the likelihood ratio test inversion method produce more realistic confidence intervals. Some bootstrap methods also perform reasonably well. Finally, empirical data are used to illustrate an application of the methods considered
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11393/238643
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