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Using disaster‐induced closures to evaluate discrete choice models of hospital demand

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  • Devesh Raval
  • Ted Rosenbaum
  • Nathan E. Wilson

Abstract

Although diversion ratios are important inputs to merger evaluation, there is little evidence about how accurately discrete choice models predict diversions. Using a series of natural disasters that unexpectedly closed hospitals, we compare observed post‐disaster diversion ratios to those predicted from pre‐disaster data using standard models of hospital demand. We find that all standard models consistently underpredict large diversions. Both unobserved heterogeneity in preferences over travel and post‐disaster changes to physician practice patterns can explain some of the underprediction of large diversions. We find a significant improvement using models with a random coefficient on distance.

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  • 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.
    • Handle: RePEc:bla:randje:v:53:y:2022:i:3:p:561-589
    DOI: 10.1111/1756-2171.12421
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    1. 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.

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