Short and Simple Confidence Intervals When the Directions of Some Effects are Known

Philipp Ketz and Adam McCloskey
Additional contact information
Philipp Ketz: Paris School of Economics - CNRS
Adam McCloskey: University of Colorado, Boulder

The Review of Economics and Statistics, 2025, vol. 107, issue 3, 820-834

Abstract: We introduce adaptive confidence intervals on a parameter of interest in the presence of nuisance parameters, such as coefficients on control variables, with known signs. Our confidence intervals are trivial to compute and can provide significant length reductions relative to standard ones when the nuisance parameters are small. At the same time, they entail minimal length increases at any parameter values. We apply our confidence intervals to the linear regression model, prove their uniform validity, and illustrate their length properties in an empirical application to a factorial design field experiment and a Monte Carlo study calibrated to the empirical application.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1162/rest_a_01297
Access to PDF is restricted to subscribers.

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:tpr:restat:v:107:y:2025:i:3:p:820-834

Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535

Access Statistics for this article

The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu

More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by The MIT Press ().