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Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles

David Brownstone, David S Bunch and Kenneth Train

Department of Economics, Working Paper Series from Department of Economics, Institute for Business and Economic Research, UC Berkeley

Abstract: We compare multinomial logit and mixed logit models for data on California households' revealed and stated preferences for automobiles. The stated preference (SP) data elicited households' preferences among gasoline, electric, methanol, and compressed natural gas vehicles with various attributes. The mixed logit models provide improved fits over logit that are highly significant, and show large heterogeneity in respondents' preferences for alternative-fuel vehicles. The effects of including this heterogeneity are demonstrated in forecasting exercises. The alternative-fuel vehicle models presented here also highlight the advantages of merging SP and revealed preference (RP) data. RP data appear to be critical for obtaining realistic body-type choice and scaling information, but they are plagued by multicollinearity and difficulties with measuring vehicle attributes. SP data are critical for obtaining information about attributes not available in the marketplace, but pure SP models with these data give implausible forecasts.

Keywords: Social; and; Behavioral; Sciences (search for similar items in EconPapers)
Date: 1999-06-02
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles (2000) Downloads
Working Paper: Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles (1999) Downloads
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