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Organizational Structure and Pricing: Evidence from a Large U.S. Airline

Author

Listed:
  • Ali Hortaçsu

    (University of Chicago and NBER)

  • Olivia R. Natan

    (University of California, Berkeley)

  • Hayden Parsley

    (University of Texas, Austin)

  • Timothy Schwieg

    (University of Chicago, Booth)

  • Kevin R. Williams

    (Yale School of Management and NBER)

Abstract

We study how organizational boundaries affect pricing decisions using comprehensive data provided by a large U.S. airline. We show that contrary to prevailing theories of the firm, advanced pricing algorithms have multiple biases. To quantify the impacts of these biases, we estimate a structural demand model using sales and search data and recover the demand curves the firm believes it faces using forecasting data. In counterfactuals, we show that correcting biases introduced by organizational teams individually have little impact on market outcomes, but addressing all biases simultaneously leads to higher prices and increased dead-weight loss in the markets studied.

Suggested Citation

  • Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Working Papers 21-09, NET Institute.
  • Handle: RePEc:net:wpaper:2109
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    Cited by:

    1. Günter J. Hitsch & Sanjog Misra & Walter W. Zhang, 2024. "Heterogeneous treatment effects and optimal targeting policy evaluation," Quantitative Marketing and Economics (QME), Springer, vol. 22(2), pages 115-168, June.
    2. Victor Aguirregabiria & Francis Guiton, 2022. "Decentralized Decision-Making in Retail Chains: Evidence from Inventory Management," Working Papers tecipa-722, University of Toronto, Department of Economics.
    3. Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Incorporating Search and Sales Information in Demand Estimation," Cowles Foundation Discussion Papers 2313, Cowles Foundation for Research in Economics, Yale University.
    4. Robert Evan Sanders, 2024. "Dynamic Pricing and Organic Waste Bans: A Study of Grocery Retailers’ Incentives to Reduce Food Waste," Marketing Science, INFORMS, vol. 43(2), pages 289-316, March.
    5. James D. Dana Jr. & Kevin R. Williams, 2018. "This paper develops an oligopoly model in which firms first choose capacity and then compete in prices in a series of advance-purchase markets. We show the existence of multiple sales opportunities cr," Cowles Foundation Discussion Papers 2136R4, Cowles Foundation for Research in Economics, Yale University, revised Nov 2021.
    6. James D. Dana & Kevin R. Williams, 2022. "Intertemporal Price Discrimination in Sequential Quantity-Price Games," Marketing Science, INFORMS, vol. 41(5), pages 966-981, September.
    7. Michele Fioretti & Junnan He & Jorge Tamayo, 2024. "Prices and Concentration: A U-Shape? Theory and Evidence from Renewables," Working Papers hal-04631762, HAL.

    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation

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