Estimating Commutersâ€™ â€œValue of Timeâ€ with Noisy Data: a Multiple Imputation Approach
AbstractWe estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. We do so, however, in an empirical setting where several key observations are missing. To overcome this, we apply Rubinâ€™s Multiple Imputation Method to generate consistent estimates and valid statistical inferences. We also compare these estimates to those produced in a "single imputation" scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. Our results show the importance of properly accounting for errors in the imputation process, and they also show that value of time savings varies greatly according to motorist characteristics.
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Bibliographic InfoPaper provided by University of California Transportation Center in its series University of California Transportation Center, Working Papers with number qt6s78c7rt.
Date of creation: 24 Nov 2004
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value of time; congestion pricing; heterogeneous consumers; product differentiation; missing data; multiple imputation; Social and Behavioral Sciences;
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