Instrument Relevance in Multivariate Linear Models: A Simple Measure
John Shea ()
No 193, NBER Technical Working Papers from National Bureau of Economic Research, Inc
The correlation between instruments and explanatory variables is a key determinant of the performance of the instrumental variables estimator. The R-squared from regressing the explanatory variable on the instrument vector is a useful measure of relevance in univariate models, but can be misleading when there are multiple endogenous variables. This paper proposes a computationally simple partial R- squared measure of instrument relevance for multivariate models.
JEL-codes: C20 C30 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23) Track citations by RSS feed
Published as Review of Economics and Statistics, Vol. 79, no. 2 (May 1997): 348-352.
Downloads: (external link)
Journal Article: Instrument Relevance in Multivariate Linear Models: A Simple Measure (1997)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberte:0193
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in NBER Technical Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().