The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units
Open accessAbstract
This paper examines the synthetic control method in contrast to commonly used difference‐in‐differences (DiD) estimation, in the context of a re‐evaluation of a pay‐for‐performance (P4P) initiative, the Advancing Quality scheme. The synthetic control method aims to estimate treatment effects by constructing a weighted combination of control units, which represents what the treated group would have experienced in the absence of receiving the treatment. While DiD estimation assumes that the effects of unobserved confounders are constant over time, the synthetic control method allows for these effects to change over time, by re‐weighting the control group so that it has similar pre‐intervention characteristics to the treated group. We extend the synthetic control approach to a setting of evaluation of a health policy where there are multiple treated units. We re‐analyse a recent study evaluating the effects of a hospital P4P scheme on risk‐adjusted hospital mortality. In contrast to the original DiD analysis, the synthetic control method reports that, for the incentivised conditions, the P4P scheme did not significantly reduce mortality and that there is a statistically significant increase in mortality for non‐incentivised conditions. This result was robust to alternative specifications of the synthetic control method. © 2015 The Authors. Health Economics published by John Wiley & Sons Ltd.
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Comparative Politics and the Synthetic Control Method
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Cited by
Designing Difference in Difference Studies: Best Practices for Public Health Policy Research
Wing, C., Simon, K., & Bello-Gomez, R. A. (2018) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040617-013507 · Cited by 1,470
Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects
Abadie, A. (2021) · Journal of Economic Literature · doi:10.1257/jel.20191450 · Cited by 1,486
Craig, P., Katikireddi, S. V., Leyland, A., & Popham, F. (2017) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-031816-044327 · Cited by 570
Skivington, K., Matthews, L., Simpson, S. A., Craig, P., Baird, J., Blazeby, J. M., Boyd, K. A., Craig, N., French, D. P., McIntosh, E., et al. (2021) · Health Technology Assessment · doi:10.3310/hta25570 · Cited by 522
Synthetic controls with staggered adoption.
Ben-Michael, E., Feller, A., & Rothstein, J. (2022) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/rssb.12448 · Cited by 120
Metadata
- Authors
- Kreif, N., Grieve, R., Hangartner, D., Turner, A. J., Nikolova, S., & Sutton, M.
- Venue
- Health Economics
- Publisher
- Wiley
- Published
- 2015-10-07
- Volume
- 25
- Issue
- 12
- Pages
- 1514-1528
- ISSN
- 1057-9230 (ISSN-L)
- 1099-1050
- OpenAlex
- W2114492847
- Cited by
- 301
- References
- 46
- FWCI
- 14.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Kreif, N., Grieve, R., Hangartner, D., Turner, A. J., Nikolova, S., & Sutton, M. (2016). Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units. Health Economics. https://doi.org/10.1002/hec.3258
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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