JSM 2011 Online Program

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Abstract Details

Activity Number: 666
Type: Contributed
Date/Time: Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
Sponsor: Section on Health Policy Statistics
Abstract - #302915
Title: A New Look at Synthetic Controls: An Application to California Hospital Data
Author(s): Emi Terasawa*+ and Sathyanarayan Anand
Companies: University of Pennsylvania and University of Pennsylvania
Address: Wharton School, Philadelphia, PA, 19104,
Keywords: synthetic ; controls ; matching ; optimization ; california ; hospital
Abstract:

Efforts examining effects of policy interventions or macroeconomic events often encounter issues finding suitable control groups to create the counterfactual. Such studies are usually observational with potential control groups consisting of heterogeneous geographic areas unaffected by the event being studied. By creating linear combinations of existing control units, Synthetic Controls (SCs) are claimed to provide better counterfactuals than traditional matching techniques. Currently, SCs are created by expensive optimization procedures that search over the space of linear combinations of controls. We remodel the problem of finding SCs as a high-dimensional regression problem. We use established variable selection and regularization techniques to narrow the search space and constrain coefficient magnitudes. We compare the speed and accuracy of the optimization procedure with our formulation on simulated data. Finally, as an application we investigate the effect of California's minimum nurse staffing law (AB394) on hospital services. SCs are constructed for CA hospitals using hospitals from the other 49 states, and we assess their comparative strengths against traditional matches.


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