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Abstract Details

Activity Number: 83
Type: Invited
Date/Time: Sunday, July 30, 2017 : 8:30 PM to 10:30 PM
Sponsor: Business and Economic Statistics Section
Abstract #323248
Title: IMs for IVs: An Inferential Model Approach to Instrumental Variable Regression
Author(s): Nicholas Aaron Syring* and Ryan Martin
Companies: NCSU and NCSU
Keywords: instrumental variables ; inferential model
Abstract:

Instrumental variables is an approach used to estimate regression parameters when covariates are correlated with errors. Applications of instrumental variables are common in econometrics among other fields where the method is regarded as helping to uncover causal relationships between covariates and a response. Statistically, the method succeeds in producing a consistent point estimator of the regression coefficients. However, standard interval estimates for the regression coefficients are unreliable. We present a new technique, using inferential models, to provide valid inference in instrumental variables regression.


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