Solving for Market Equilibrium using Random Coefficient Random Utility Models
In this paper we develop a likelihood based approach for estimating the joint equilibrium parameter distribution in random coefficient-random utility models. Under this demand specification and a profit maximizing supply specification, the equilibrium distribution of prices and quantities has an intractable likelihood function that cannot be directly analyzed. We solve this problem by adding a small, stochastic error to our demand and pricing equations. We then simulate the equilibrium parameter distributions using Markov Chain Monte Carlo simulation on this complex, nonlinear model. We show how to incorporate unobserved quality characteristics via instrumental variables and estimate a market equilibrium model for the U.S. automobile market. We compare estimation results and corresponding elasticities of our joint system to those from an instrumental-variables estimation of a logit specification and those of a random-coefficient random utility specification of demand only. The joint system provides significantly better estimation results both in terms of parameter values and in terms of substitution patterns. We conclude by discussing methodological extensions to include demographic information that has proven beneficial in other random coefficient applications.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||01 Apr 2001|
|Date of revision:|
|Contact details of provider:|| Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sce:scecf1:256. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.