robust2sls

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.

Last 30 days

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.