Semiparametric correction for a sample selection bias in the presence of endogenous truncation is known to be much more difficult in the case of a binary selection variable than in the case of a continuous selection variable. This paper proposes a simple bandwidth-free semiparametric methodology...

The validity of the IV estimator relies on the orthogonality with respect to the random disturbance. However, in cases of endogenously truncated data as well as in other instances (e.g., censored data) which is very frequently the nature of data used in empirical research, there exists severe...

We show that when data are endogenously truncated the widely-used IV fails to render the relationship causal as well as introduces bias into the exogenous covariates. We offer a newly-introduced semiparametric biorthogonal wavelet-based JPEG IV estimator and its associated symmetry preserving...