Implementing an Improved Test of Matrix Rank in Stata

TL;DR

This paper introduces a Stata command, bootranktest, that implements an improved matrix rank test for instrumental variable models, using bootstrap methods to better control Type I error and handle dependent data.

Contribution

The paper develops and provides a new Stata command for an enhanced matrix rank test that improves error control and accommodates dependent data structures.

Findings

Bootstrap-based test controls Type I error more effectively.

The command handles temporal and cluster dependence.

Provides both two-step and analytic test options.

Abstract

We develop a Stata command, bootranktest, for implementing the matrix rank test of Chen and Fang (2019) in linear instrumental variable regression models. Existing rank tests employ critical values that may be too small, and hence may not even be first order valid in the sense that they may fail to control the Type I error. By appealing to the bootstrap, they devise a test that overcomes the deficiency of existing tests. The command bootranktest implements the two-step version of their test, and also the analytic version if chosen. The command also accommodates data with temporal and cluster dependence.