Revolutionizing Estimation and Inference for Program Evaluation Using Bayesian Methods

Lauren Vollmer, Mariel Finucane and Randall Brown

Mathematica Policy Research Reports from Mathematica Policy Research

Abstract: Policy makers seek to replace the “thumbs up–thumbs down†of conventional hypothesis testing with statements about the probability that program effects on key outcomes exceed policy-relevant thresholds.

Keywords: economic evaluation; design and evaluation of programs and policies; quasi-experimental design; methodology (if appropriate); Bayesian; primary care (search for similar items in EconPapers)
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0193841X18815817 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mpr:mprres:97bd3209760441babdd1683ae8a24895

Access Statistics for this paper

More papers in Mathematica Policy Research Reports from Mathematica Policy Research Mathematica Policy Research P.O. Box 2393 Princeton, NJ 08543-2393 Attn: Communications. Contact information at EDIRC.
Bibliographic data for series maintained by Joanne Pfleiderer () and Cindy George ( this e-mail address is bad, please contact ).