robust2sls - Outlier Robust Two-Stage Least Squares Inference and Testing
An implementation of easy tools for outlier robust
inference in two-stage least squares (2SLS) models. The user
specifies a reference distribution against which observations
are classified as outliers or not. After removing the outliers,
adjusted standard errors are automatically provided.
Furthermore, several statistical tests for the false outlier
detection rate can be calculated. The outlier removing
algorithm can be iterated a fixed number of times or until the
procedure converges. The algorithms and robust inference are
described in more detail in Jiao (2019)
<https://drive.google.com/file/d/1qPxDJnLlzLqdk94X9wwVASptf1MPpI2w/view>.
