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Pricing used books on Amazon.com: a spatial approach to price dispersion

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  • Haoying Wang

Abstract

This paper estimates a spatial autoregressive (SAR) model of price dispersion using publicly available internet bookselling data. It uses a semiparametric adaptive estimator that does not require the usual Gaussian assumption of maximum likelihood (ML) estimators. The results suggest that both price competition and seller heterogeneity are key drivers of the observed price dispersion. The paper finds that sellers with large sales volume, newly established sellers and US mainland states-based sellers tend to price lower. The identified significant spatial interaction is evidence of spatial price competition. Controlling for everything else, a seller asks a lower price when large sellers charge relatively high prices, which is also evidence of price-based selling and undercutting.

Suggested Citation

  • Haoying Wang, 2018. "Pricing used books on Amazon.com: a spatial approach to price dispersion," Spatial Economic Analysis, Taylor & Francis Journals, vol. 13(1), pages 99-117, January.
    • Handle: RePEc:taf:specan:v:13:y:2018:i:1:p:99-117
    DOI: 10.1080/17421772.2017.1369147
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    References listed on IDEAS

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    3. Alisher Tleubayev & Tinoush Jamali Jaghdani & Linde Gotz & Miranda Svanidze, 2021. "The relationship between trade policies and macroeconomic adjustments in the Russian cheese market integration," Journal of New Economy, Ural State University of Economics, vol. 22(3), pages 44-68, October.

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