Measurement error in US regional economic data
Craig Carpenter,
Anders Van Sandt and
Scott Loveridge
Journal of Regional Science, 2022, vol. 62, issue 1, 57-80
Abstract:
Estimates of publicly suppressed and unrevised regional economic data produce error and potentially bias statistical inference. This article estimates measurement error in suppressed cell estimated data sets (SCEDs) relative to unsuppressed federal administrative data. In a cross section, coefficient estimates based on relatively aggregated SCEDs are attenuated by about 31%, increasing to 50% in panel data. Coefficient estimates based on less‐aggregated SCEDs are not generally reliable. A review of the limited options for identification emphasizes both the systemic limitations suppression places on research inference and the value of retrospective revisions in confidential data, highlighting the importance of confidential data access and use.
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://doi.org/10.1111/jors.12551
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:bla:jregsc:v:62:y:2022:i:1:p:57-80
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0022-4146
Access Statistics for this article
Journal of Regional Science is currently edited by Marlon G. Boarnet, Matthew Kahn and Mark D. Partridge
More articles in Journal of Regional Science from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().