Headline Estimation with Multiple Research Designs

Vod Vilfort

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arXiv · 2609.01943

Headline Estimation with Multiple Research Designs

Vod Vilfort

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Abstract

To study a scalar parameter, a researcher may consider multiple research designs. Based on the evidence across designs, the researcher may wish to formulate a headline estimate of the parameter. I examine how to choose this headline when it is unclear which design is most appropriate for studying the parameter. I model this setting by assuming that (i) exactly one of the designs is valid for the parameter and (ii) the researcher has ambiguity about which design is valid, represented by a class of priors over the candidate designs. To account for ambiguity, I propose reporting the headline estimate that minimizes the worst-case posterior risk over the class of priors. In three applications, I show cases where accounting for ambiguity materially affects the quantitative conclusion and cases where an existing headline is already close to optimal.

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Vod Vilfort. 2026-09-01. Headline Estimation with Multiple Research Designs. https://arxiv.org/abs/2609.01943

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