<p>Dealing with endogenous regressors is a central challenge of applied research. The standard solution is to use instrumental variables that are assumed to be uncorrelated with unobservables. We instead assume (i) the correlation between the instrument and the error term has the same sign as the correlation between the endogenous regressor and the error term, and (ii) that the instrument is less correlated with the error term than is the endogenous regressor. Using these assumptions, we derive analytic bounds for the parameters. We demonstrate the method in two applications.</p>
Authors
Aviv Nevo
![Adam Rosen](/sites/default/files/styles/square_desktop/public/2022-07/Adam%20Rosen_0.png?itok=gamH7qxi)
Research Fellow Duke University
Adam is a Research Fellow associated with the Cemmap at the IFS and UCL and an Associate Professor of Economics at Duke University.
Working Paper details
- DOI
- 10.1920/wp.cem.2008.1608
- Publisher
- IFS
Suggested citation
Nevo, A and Rosen, A. (2008). Identification with imperfect instruments. London: IFS. Available at: https://ifs.org.uk/publications/identification-imperfect-instruments (accessed: 30 June 2024).
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