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Estimating Dynamic Demand for Airlines

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  • Diego, Escobari

Abstract

This paper uses an original panel dataset with posted prices and sales to estimate a dynamic demand. We find that consumers become more price sensitive as time to departure nears which is consistent with having lower valuations. This result provides empirical support to a key theoretical implication in Deneckere and Peck [Deneckere, R., Peck, J., 2012. Dynamic competition with random demand and costless search: A theory of price posting. Econometrica 80, 1185-1247] --- high-valuation consumers purchase earlier. We also find that the number of active consumers increases closer to departure.

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  • Diego, Escobari, 2014. "Estimating Dynamic Demand for Airlines," MPRA Paper 55408, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:55408
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Yaghoub Abdi & Xiaoni Li & Xavier Càmara-Turull, 2023. "Firm value in the airline industry: perspectives on the impact of sustainability and Covid-19," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-24, December.
    2. Shao, Shuai & Kauermann, Göran & Smith, Michael Stanley, 2020. "Whether, when and which: Modelling advanced seat reservations by airline passengers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 490-514.
    3. Chiou, Yu-Chiun & Liu, Chia-Hsin, 2016. "Advance purchase behaviors of air tickets," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 62-69.
    4. Escobari, Diego, 2017. "Airport, airline and departure time choice and substitution patterns: An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 198-210.
    5. Rolim, Paula S.W. & Bettini, Humberto F.A.J. & Oliveira, Alessandro V.M., 2016. "Estimating the impact of airport privatization on airline demand: AÂ regression-based event study," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 31-41.
    6. Mumbower, Stacey & Garrow, Laurie A. & Newman, Jeffrey P., 2015. "Investigating airline customers’ premium coach seat purchases and implications for optimal pricing strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 73(C), pages 53-69.
    7. Luttmann, Alexander & Gaggero, Alberto A, 2022. "How does COVID-19 affect intertemporal price dispersion? Evidence from the airline industry," MPRA Paper 111797, University Library of Munich, Germany.
    8. Tangjian Wei & Feng Shi & Guangming Xu, 2019. "Estimation of Time-Varying Passenger Demand for High Speed Rail System," Complexity, Hindawi, vol. 2019, pages 1-24, March.
    9. Escobari, Diego & Serrano, Alejandro, 2015. "Reducing Asymmetric Information in Venture Capital Backed IPOs," MPRA Paper 68140, University Library of Munich, Germany.
    10. Chiou, Yu-Chiun & Liu, Chia-Hsin, 2016. "Advance purchase behaviors of air passengers: A continuous logit model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 474-484.
    11. Kaukin, Andrey (Каукин, Андрей), 2018. "Diagnosis of the Growth Model of the Russian Air Transportation Market: Bottlenecks and Directions of Development [Диагностика Модели Роста Российского Рынка Авиаперевозок: Узкие Места И Направлени," Working Papers 061830, Russian Presidential Academy of National Economy and Public Administration.

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    More about this item

    Keywords

    Dynamic demand; Consumers' valuations; Advance purchases; Airlines;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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