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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
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Handle: RePEc:bla:jregsc:v:62:y:2022:i:1:p:57-80