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Dynamic pricing and asymmetries in retail gasoline markets: What can they tell us about price stickiness?

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  • Douglas, Christopher C.
  • Herrera, Ana María

Abstract

Theoretical explanations for price stickiness used in businesses cycle models are diverse (e.g., information processing delays, rational inattention and fair pricing), with each theory resulting in a different implication for inflation dynamics. Using an autoregressive conditional binomial model and a data set consisting of daily observations of price and cost for 15 Philadelphia retail gasoline stations, we test which of these theories is most consistent with the observed pattern of price adjustment. Our findings of time dependence, asymmetry and the role of cost volatility are consistent with a combination of fairness considerations and rational inattention by producers.

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  • Douglas, Christopher C. & Herrera, Ana María, 2014. "Dynamic pricing and asymmetries in retail gasoline markets: What can they tell us about price stickiness?," Economics Letters, Elsevier, vol. 122(2), pages 247-252.
    • Handle: RePEc:eee:ecolet:v:122:y:2014:i:2:p:247-252
    DOI: 10.1016/j.econlet.2013.11.025
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    References listed on IDEAS

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    7. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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