A new technique is devised to mitigate the errors-in-variables bias in linear regression. The procedure mimics a 2-stage least squares procedure where an auxiliary regression which generates a better behaved predictor variable is derived. The generated variable is then used as a substitute for...

This paper proposes a new framework for estimating instrumental variable (IV) quantile models. The first part of our proposal can be cast as a mixed integer linear program (MILP), which allows us to capitalize on recent progress in mixed integer optimization. The computational advantage of the...