Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56033 
Year of Publication: 
2012
Series/Report no.: 
ZEW Discussion Papers No. 12-017
Publisher: 
Zentrum für Europäische Wirtschaftsforschung (ZEW), Mannheim
Abstract: 
In this paper we use Bayes estimates of a multinomial probit model with fully flexible substitution patterns to forecast consumer response to ultra-low-emission vehicles. In this empirical application of the probit Gibbs sampler, we use stated-preference data on vehicle choice from a Germany-wide survey of potential light-duty-vehicle buyers using computer-assisted personal interviewing. We show that Bayesian estimation of a multinomial probit model with a full covariance matrix is feasible for this medium-scale problem. Using the posterior distribution of the parameters of the vehicle choice model as well as the GHK simulator we derive the choice probabilities of the different alternatives. We first show that the Bayes point estimates of the market shares reproduce the observed values. Then, we define a base scenario of vehicle attributes that aims at representing an average of the current vehicle choice situation in Germany. Consumer response to qualitative changes in the base scenario is subsequently studied. In particular, we analyze the effect of increasing the network of service stations for charging electric vehicles as well as for refueling hydrogen. The result is the posterior distribution of the choice probabilities that represent adoption of the energy-effcient technologies.
Subjects: 
Discrete choice models
Bayesian econometrics
Low emission vehicles
Charging infrastructure
JEL: 
C25
D12
Q42
Document Type: 
Working Paper

Files in This Item:
File
Size
462.84 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.