Confidence intervals in regressions with estimated factors and idiosyncratic components

Jack Fosten

Economics Letters, 2017, vol. 157, issue C, 71-74

Abstract: This paper shows that HAC standard errors must be adjusted when constructing confidence intervals in regressions involving both the factors and idiosyncratic components estimated from a big dataset. This result is in contrast to the seminal result of Bai and Ng (2006) where the assumption that T∕N→0 is sufficient to eliminate the effect of estimation error, where T and N are the time-series and cross-sectional dimensions. Simulations show vast improvements in the coverage rates of the adjusted confidence intervals over the unadjusted ones.

Keywords: Factor model; Idiosyncratic component; Inference; Confidence intervals (search for similar items in EconPapers)
JEL-codes: C12 C22 C52 C53 C55 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:157:y:2017:i:c:p:71-74

DOI: 10.1016/j.econlet.2017.05.034

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