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For stratified propensity scores, considered as a parametric model, we derive explicit formulas for the efficiency gain from knowing how the covariate space is split. Based on these, we find that the efficiency gain decreases as the partition of the stratification becomes finer. For general parametric models, where it is hard to obtain explicit representations of efficiency bounds, we propose a novel framework that enables us to see whether knowing a parametric model is valuable in terms of efficiency even when it is high dimensional. In addition to the intuitive fact that knowing the parametric model does not help much if it is sufficiently flexible, we discover that the efficiency gain can be nearly zero even though the parametric assumption significantly restricts the space of possible propensity scores.<\/jats:p>","DOI":"10.1093\/biomet\/asae034","type":"journal-article","created":{"date-parts":[[2024,7,6]],"date-time":"2024-07-06T08:03:46Z","timestamp":1720253026000},"source":"Crossref","is-referenced-by-count":0,"title":["Semiparametric efficiency gains from parametric restrictions on propensity scores"],"prefix":"10.1093","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9253-9764","authenticated-orcid":false,"given":"Haruki","family":"Kono","sequence":"first","affiliation":[{"name":"Department of Economics, Massachusetts Institute of Technology , 50 Memorial Drive , Cambridge, Massachusetts 02139,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,7,5]]},"reference":[{"year":"2024","author":"Bai","key":"2025012017184361100_asae034-B1"},{"volume-title":"Efficient and Adaptive Estimation for Semiparametric Models","year":"1993","author":"Bickel","key":"2025012017184361100_asae034-B2"},{"key":"2025012017184361100_asae034-B3","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.3982\/QE1150","article-title":"Inference under covariate-adaptive randomization with multiple treatments","volume":"10","author":"Bugni","year":"2019","journal-title":"Quant. 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