Instrument Relevance in Multivariate Linear Models: A Simple Measure / John Shea.
Material type:
- Hardcopy version available to institutional subscribers
Item type | Home library | Collection | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Working Paper | Biblioteca Digital | Colección NBER | nber t0193 (Browse shelf(Opens below)) | Not For Loan |
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.
Hardcopy version available to institutional subscribers
System requirements: Adobe [Acrobat] Reader required for PDF files.
Mode of access: World Wide Web.
Print version record
There are no comments on this title.