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Limited Information Bayesian Analysis of a Simultaneous Equation with an Autocorrelated Error Term and its Application to the U.S. Gasoline Market

  • Stanislav Radchenko

    (University of North Carolina at Charlotte)

Using Markov Chain Monte Carlo algorithms within the limited information Bayesian framework, we estimate the parameters of the structural equation of interest and test weak exogeneity in a simultaneous equation model with white noise as well as autocorrelated error terms. A numerical example and an estimation of the supply and demand equations of the U.S. gasoline market show that if we ignore autocorrelation we obtain unreasonable posterior distributions of the parameters of interest. Also we find that the hypothesis of the asymmetric effect of the changes in oil price on the changes in gasoline price is rejected. Oil inventory has a significant negative effect on the gasoline price.

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File URL: http://econwpa.repec.org/eps/em/papers/0408/0408001.pdf
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Paper provided by EconWPA in its series Econometrics with number 0408001.

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Length: 41 pages
Date of creation: 02 Aug 2004
Date of revision:
Handle: RePEc:wpa:wuwpem:0408001
Note: Type of Document - pdf; pages: 41
Contact details of provider: Web page: http://econwpa.repec.org

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