We propose an instrumental variables method for inference in high-dimensional structural equations with endogenous regressors. The number of regressors K can be much larger than the sample size. A key ingredient is sparsity, i.e., the vector of coefficients has many zeros, or approximate...

This article gives the asymptotic properties of multivariate k-nearest neighbor regression estimators for dependent variables belonging to Rd, d 1. The results derived here permit to provide consistent forecasts, and confidence intervals for time series An illustration of the method is given...

We propose a wild bootstrap procedure for linear regression models estimated by instrumental variables. Like other bootstrap procedures that we have proposed elsewhere, it uses efficient estimates of the reduced-form equation(s). Unlike them, it takes account of possible heteroskedasticity of...