Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study

Ben Gillen, Erik Snowberg and Leeat Yariv

Journal of Political Economy, 2019, vol. 127, issue 4, 1826 - 1863

Abstract: Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, attenuated estimated effects of elicited behaviors, and biased correlations between characteristics. We develop statistical techniques for handling experimental measurement error. These techniques are applied to data from the Caltech Cohort Study, which conducts repeated incentivized surveys of the Caltech student body. We replicate three classic experiments, demonstrating that results change substantially when measurement error is accounted for. Collectively, these results show that failing to properly account for measurement error may cause a field-wide bias leading scholars to identify "new" phenomena.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (197)

Downloads: (external link)
http://dx.doi.org/10.1086/701681 (application/pdf)
http://dx.doi.org/10.1086/701681 (text/html)
Access to the online full text or PDF requires a subscription.

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:ucp:jpolec:doi:10.1086/701681

Access Statistics for this article

More articles in Journal of Political Economy from University of Chicago Press
Bibliographic data for series maintained by Journals Division ().