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The Impact of Process Innovation on Prices: Evidence from Automated Fuel Retailing in The Netherlands

Author

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  • Adriaan R. Soetevent

    () (University of Groningen)

  • Tadas Bruzikas

    () (University of Groningen)

Abstract

In the last decade, many European countries have seen a sharp increase in the number of automated fueling stations. We study the effect of this process innovation on prices at stations that are automated and their competitors using a difference-in-differences matching strategy. Our estimates show that prices at automated stations drop by 1.0 to 2.1% immediately after conversion and stabilize at this lower level. We find no indication of competitive spillover effects to neighboring sites at the conventional significance levels. Other than previous studies, our estimates do not reveal a difference in impact between early and later adopters of automation.

Suggested Citation

  • Adriaan R. Soetevent & Tadas Bruzikas, 2017. "The Impact of Process Innovation on Prices: Evidence from Automated Fuel Retailing in The Netherlands," Tinbergen Institute Discussion Papers 17-045/VII, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20170045
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    References listed on IDEAS

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    1. Pim Heijnen & Marco A. Haan & Adriaan R. Soetevent, 2015. "Screening for collusion: a spatial statistics approach," Journal of Economic Geography, Oxford University Press, vol. 15(2), pages 417-448.
    2. Juan Esteban Carranza & Robert Clark & Jean-Fran├žois Houde, 2015. "Price Controls and Market Structure: Evidence from Gasoline Retail Markets," Journal of Industrial Economics, Wiley Blackwell, vol. 63(1), pages 152-198, March.
    3. Emek Basker, 2012. "Raising the Barcode Scanner: Technology and Productivity in the Retail Sector," NBER Chapters,in: Standards, Patents and Innovations National Bureau of Economic Research, Inc.
    4. repec:bla:jemstr:v:26:y:2017:i:4:p:876-896 is not listed on IDEAS
    5. Caitlin Knowles Myers & Grace Close & Laurice Fox & John William Meyer & Madeline Niemi, 2011. "Retail Redlining: Are Gasoline Prices Higher In Poor And Minority Neighborhoods?," Economic Inquiry, Western Economic Association International, vol. 49(3), pages 795-809, July.
    6. Emek Basker & Lucia Foster & Shawn Klimek, 2017. "Customer-employee substitution: Evidence from gasoline stations," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 26(4), pages 876-896, December.
    7. Ambarish Chandra & Mariano Tappata, 2011. "Consumer search and dynamic price dispersion: an application to gasoline markets," RAND Journal of Economics, RAND Corporation, vol. 42(4), pages 681-704, December.
    8. Ron Adner & Daniel Levinthal, 2001. "Demand Heterogeneity and Technology Evolution: Implications for Product and Process Innovation," Management Science, INFORMS, vol. 47(5), pages 611-628, May.
    9. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    10. Adriaan R. Soetevent & Marco A. Haan & Pim Heijnen, 2008. "Do Auctions and Forced Divestitures increase Competition?," Tinbergen Institute Discussion Papers 08-117/1, Tinbergen Institute, revised 02 Aug 2011.
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    More about this item

    Keywords

    technology adoption; retail gasoline; pricing; competition;

    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
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

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