The main advantage of the randomized controlled trial (RCT) is the random assignment of treatment that prevents selection by prognosis. Nevertheless, only few RCTs can be performed given their high cost and the difficulties in conducting such studies. Therefore, several analytical methods for removing the effects of selection bias in observational studies have been proposed. The first aim of th...

Subspace estimation plays an important role in, for example, sensor array signal processing. Recursive methods for subspace tracking with application to non-stationary environments , have also drawn considerable interest. In this paper, Instrumental Variable (IV) extensions of the recently developed Projection Approximation Subspace Tracking (PAST) algorithm are presented. The IV-approach is mo...

The ability to allow for flexible forms of unobserved heterogeneity is an essential ingredient in modern microeconometrics. In this paper we extend the application of instrumental variable (IV) methods to a wide class of problems in which multiple values of unobservable variables can be associated with particular combinations of observed endogenous and exogenous variables. In our Generalized In...

The ability to allow for flexible forms of unobserved heterogeneity is an essential ingredient in modern microeconometrics. In this paper we extend the application of instrumental variable (IV) methods to a wide class of problems in which multiple values of unobservable variables can be associated with particular combinations of observed endogenous and exogenous variables. In our Generalized In...

Quantile regression is an increasingly important tool that estimates the conditional quantiles of a response Y given a vector of regressors D. It usefully generalizes Laplace’s median regression and can be used to measure the effect of covariates not only in the center of a distribution, but also in the upper and lower tails. For the linear quantile model defined by Y = D′γ(U) where D′γ(U) is s...