A Semiparametric Discrete Choice Model: An Application to Hospital Mergers

26 Pages Posted: 28 Aug 2017

See all articles by Devesh Raval

Devesh Raval

Federal Trade Commission Bureau of Economics

Ted Rosenbaum

Federal Trade Commission Bureau of Economics

Steven Tenn

Charles River Associates

Date Written: October 2017

Abstract

We propose a computationally simple semiparametric discrete choice estimator to model rich consumer heterogeneity. We assume groups of observably similar consumers have similar preferences, but allow preferences to vary freely across these groups. Model flexibility is easily adjusted by setting a single tuning parameter; we suggest a cross‐validation method to do so. We analyze the model's properties in the context of hospital mergers, both analytically and via a Monte Carlo analysis. The model performs well for policy relevant substitution and welfare measures, even if misspecified, when the tuning parameter is set within the neighborhood of the value chosen by cross validation.

JEL Classification: C14, D12, I11, L41

Suggested Citation

Raval, Devesh and Rosenbaum, Ted and Tenn, Steven, A Semiparametric Discrete Choice Model: An Application to Hospital Mergers (October 2017). Economic Inquiry, Vol. 55, Issue 4, pp. 1919-1944, 2017. Available at SSRN: https://ssrn.com/abstract=3026754 or http://dx.doi.org/10.1111/ecin.12454

Devesh Raval (Contact Author)

Federal Trade Commission Bureau of Economics ( email )

600 Pennsylvania Ave NW
Washington, DC 20580
United States

Ted Rosenbaum

Federal Trade Commission Bureau of Economics ( email )

600 Pennsylvania Ave NW
Washington, DC 20580
United States

Steven Tenn

Charles River Associates ( email )

1201 F Street, NW, Suite 700
Washington, DC 20004-1229
United States
202-662-3806 (Phone)
202-662-3910 (Fax)

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