Instrument Relevance in Multivariate Linear Models: A Simple Measure / John Shea.

By:

Shea, John

Contributor(s):

National Bureau of Economic Research

Material type: Text

TextSeries: Technical Working Paper Series (National Bureau of Economic Research) ; no. t0193.Publication details: Cambridge, Mass. National Bureau of Economic Research 1996.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: 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.

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March 1996.

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.