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Demand Estimation in the Presence of Revenue Management

Author

Listed:
  • X. D'HAULTFOEUILLE

    (Insee)

  • P. FEVRIER

    (Insee)

  • L. WILNER

    (Insee)

Abstract

Yield management has become a standard tool in several industries to increase the profits of firms facing demand uncertainty or consumers heterogeneity. But this technique also raises econometric problems in the estimation of demand models. Quantity-based management, in particular, is the source of both an endogeneity and a right-censoring problem. Disposing of macro data only and ignoring these issues leads to an aggregation bias. We develop a structural model of demand in the presence of quantity-based management. We show that the price elasticity is identified in this model provided that (i) we observe two subpopulations that face different prices but are not separated in the yield management policy, (ii) the highest prices and quantities sold at these prices are observed, (iii) the highest prices vary with time or across markets. We apply our method to the French railroad industry, using disaggregated data on trips between Paris and big cities on the period 2007-2009. Our estimates of the price-elasticity are consistent with a rather responsive demand, from 1.7 to 2 in economy class and from 1.3 to 1.5 in business class.

Suggested Citation

  • X. D'Haultfoeuille & P. Fevrier & L. Wilner, 2012. "Demand Estimation in the Presence of Revenue Management," Documents de Travail de l'Insee - INSEE Working Papers g2012-13, Institut National de la Statistique et des Etudes Economiques.
    • Handle: RePEc:nse:doctra:g2012-13
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    File URL: https://www.bnsp.insee.fr/ark:/12148/bc6p06zr596/f1.pdf
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    References listed on IDEAS

    as
    1. S. L. Brumelle & J. I. McGill, 1993. "Airline Seat Allocation with Multiple Nested Fare Classes," Operations Research, INFORMS, vol. 41(1), pages 127-137, February.
    2. John Rust & Sungjin Cho, 2018. "Optimal Dynamic Hotel Pricing," 2018 Meeting Papers 179, Society for Economic Dynamics.
    3. Wardman, Mark, 1997. "Inter-urban rail demand, elasticities and competition in Great Britain: Evidence from direct demand models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 33(1), pages 15-28, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    revenue management; demand estimation; price-elasticity; railways transportation;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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