Journal of Economic Perspectives
ISSN 0895-3309 (Print) | ISSN 1944-7965 (Online)
In Praise of the Bayesian Bootstrap
Journal of Economic Perspectives
(pp. 137–58)
(Complimentary)
Abstract
The key takeaways from this article will be the following: (i) Anytime you can bootstrap, you should! (ii) Use the Bayesian bootstrap instead of the nonparametric bootstrap. (iii) If the bootstrap distribution looks different from the "theoretical" (usually, normal) distribution, don't (only) report a point estimate and standard error. (iv) Instead (or in addition), report the bootstrap distribution with a plot if you have space for it or an interval if you don't. (v) Give the Bayesian bootstrap a Bayesian interpretation. (vi) You can use a bootstrap even with (multiway) clustering.
Visual Abstract
Citation
Andrews, Isaiah, Sarah Moon, and Jesse M. Shapiro. 2026. "In Praise of the Bayesian Bootstrap." Journal of Economic Perspectives 40 (4): 137–58. DOI: 10.1257/jep.20261514Additional Materials
JEL Classification
- C11 Bayesian Analysis: General
- C14 Semiparametric and Nonparametric Methods: General
- C15 Statistical Simulation Methods: General
- C21 Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
- D72 Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
- D81 Criteria for Decision-Making under Risk and Uncertainty