IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v100y2018i5p906-915.html
   My bibliography  Save this article

Why Do Previous Choices Matter for Hospital Demand? Decomposing Switching Costs from Unobserved Preferences

Author

Listed:
  • Devesh Raval

    (Federal Trade Commission)

  • Ted Rosenbaum

    (Federal Trade Commission)

Abstract

Using data on women’s choice of hospital for childbirth in Florida, we find that women return to the same hospital approximately 70% of the time. We separate explanations of switching costs and unobserved preference heterogeneity using a panel data fixed effects estimator and find that switching costs account for approximately 40% of the demand effects of a lagged dependent variable. The welfare effects of excluding a hospital from a payer’s network are smaller in the short run but higher in the long run, given our estimates of switching costs, and the dynamic effects of entry on competition are significantly smaller.

Suggested Citation

  • Devesh Raval & Ted Rosenbaum, 2018. "Why Do Previous Choices Matter for Hospital Demand? Decomposing Switching Costs from Unobserved Preferences," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 906-915, December.
    • Handle: RePEc:tpr:restat:v:100:y:2018:i:5:p:906-915
    as

    Download full text from publisher

    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/rest_a_00741
    Download Restriction: Access to PDF is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hill, Elaine L. & Slusky, David J.G. & Ginther, Donna K., 2019. "Reproductive health care in Catholic-owned hospitals," Journal of Health Economics, Elsevier, vol. 65(C), pages 48-62.
    2. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2020. "Inference on Semiparametric Multinomial Response Models," Discussion Papers Series 627, School of Economics, University of Queensland, Australia.
    3. Sá, Luís & Straume, Odd Rune, 2021. "Quality provision in hospital markets with demand inertia: The role of patient expectations," Journal of Health Economics, Elsevier, vol. 80(C).
    4. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2019. "Inference on Semiparametric Multinomial Response Models," Boston College Working Papers in Economics 980, Boston College Department of Economics.
    5. Dahl, Gordon B. & Forbes, Silke J., 2023. "Doctor switching costs," Journal of Public Economics, Elsevier, vol. 221(C).
    6. Devesh Raval & Ted Rosenbaum & Nathan E. Wilson, 2022. "Using disaster‐induced closures to evaluate discrete choice models of hospital demand," RAND Journal of Economics, RAND Corporation, vol. 53(3), pages 561-589, September.
    7. Devesh Raval & Ted Rosenbaum, 2021. "Why is Distance Important for Hospital Choice? Separating Home Bias From Transport Costs," Journal of Industrial Economics, Wiley Blackwell, vol. 69(2), pages 338-368, June.
    8. Shakeeb Khan & Maria Ponomareva & Elie Tamer, 2019. "Identification of Dynamic Panel Binary Response Models," Boston College Working Papers in Economics 979, Boston College Department of Economics.
    9. Bisceglia, Michele & Cellini, Roberto & Siciliani, Luigi & Straume, Odd Rune, 2020. "Optimal dynamic volume-based price regulation," International Journal of Industrial Organization, Elsevier, vol. 73(C).
    10. Abigail Ferguson & Nellie Lew & Michael Lipsitz & Devesh Raval, 2023. "Economics at the FTC: Spatial Demand, Veterinary Hospital Mergers, Rulemaking, and Noncompete Agreements," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 63(4), pages 435-465, December.
    11. Raval, Devesh & Rosenbaum, Ted & Wilson, Nathan E., 2021. "How do machine learning algorithms perform in predicting hospital choices? evidence from changing environments," Journal of Health Economics, Elsevier, vol. 78(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tpr:restat:v:100:y:2018:i:5:p:906-915. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kelly McDougall (email available below). General contact details of provider: https://direct.mit.edu/journals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.