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A Bayesian heterogeneous coefficients spatial autoregressive panel data model of retail fuel duopoly pricing

Author

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  • LeSage, James P.
  • Vance, Colin
  • Chih, Yao-Yu

Abstract

We apply a heterogenous coefficient spatial autoregressive panel model to explore competition/cooperation by duopoly pairs of German fueling stations in setting prices for diesel and e5 fuel. We rely on a Markov Chain Monte Carlo (MCMC) estimation methodology applied with non-informative priors, which produces estimates equivalent to those from (quasi-) maximum likelihood. We explore station-level pricing behavior using pairs of proximately situated fueling stations with no nearby neighbors. Our sample data represents average daily diesel and e5 fuel prices, and refinery cost information covering more than 487 days.

Suggested Citation

  • LeSage, James P. & Vance, Colin & Chih, Yao-Yu, 2017. "A Bayesian heterogeneous coefficients spatial autoregressive panel data model of retail fuel duopoly pricing," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 46-55.
  • Handle: RePEc:eee:regeco:v:62:y:2017:i:c:p:46-55
    DOI: 10.1016/j.regsciurbeco.2016.11.003
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    References listed on IDEAS

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    18. repec:spr:stemec:978-3-7908-2070-6 is not listed on IDEAS
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    More about this item

    Keywords

    Spatial panel data models; Markov Chain Monte Carlo; Spatial autoregressive model; Observation-level spatial interaction;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection

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