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

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  • Brownston, David
  • Bunch, David S.
  • Train, Kenneth

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.

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Bibliographic Info

Paper provided by University of California Transportation Center in its series University of California Transportation Center, Working Papers with number qt7rf7s3nx.

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Date of creation: 02 Jun 1999
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Handle: RePEc:cdl:uctcwp:qt7rf7s3nx

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Keywords: Architecture;

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  1. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," University of California Transportation Center, Working Papers, University of California Transportation Center qt1j6814b3, University of California Transportation Center.
  2. Kenneth Train, . "Simulation Methods for Probit and Related Models Based on Convenient Error Partitioning," Working Papers, University of California at Berkeley, Econometrics Laboratory Software Archive _009, University of California at Berkeley, Econometrics Laboratory Software Archive.
  3. Lee, Lung-Fei, 1992. "On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 8(04), pages 518-552, December.
  4. Brownstone, David & Bunch, David S. & Golob, Thomas F. & Ren, Weiping, 1996. "A Transaction Choice Model for Forecasting Demand for Alternative-Fuel Vehicles," University of California Transportation Center, Working Papers, University of California Transportation Center qt0244r8g2, University of California Transportation Center.
  5. Brownstone, David & Bunch, David S & Golob, Thomas F & Ren, Weiping, 1996. "A Transactions Choice Model for Forecasting Demand for Alternative-Fuel Vehicles," University of California Transportation Center, Working Papers, University of California Transportation Center qt3sm7w9zk, University of California Transportation Center.
  6. Bunch, David S., 1988. "A comparison of algorithms for maximum likelihood estimation of choice models," Journal of Econometrics, Elsevier, Elsevier, vol. 38(1-2), pages 145-167.
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