inst/readme.md

In s3alfisc/wildboottestjlr: Fast Wild Cluster Bootstrap Inference in R via WildBootTests.jl and JuliaConnectoR

Tests in wildboottestjlr

Tests are implemented via the tinytest package and are triggered to run on github actions with every commit of a development version (with three-digit labels, e.g. 0.1.1).

Note that these unit tests might run for a long time (around 30 minutes).

External Tests: Testing wildboottestjlr against other implementations of the wild cluster bootstrap

• In test_ols_fwildclusterboot.R the wild cluster bootstrap for OLS in wildboottestjlr is tested against the fwildclusterboot package. This test suit is divided in two parts: first, the bootstrap implementations are tested "stochastically" for large B. Second, the tests check if the t-stats computed in fwildclusterboot and wildboottestjlr are exactly identical. Third, a set of tests uses the fact that in the enumeration case, both bootstrap implementation use the same weights matrix and therefore, the resulting inferential parameters should be exactly identical.

• In test_iv.R, wildboottestjlr's IV method is tested against the Stata implementation of the wild cluster bootstrap, boottest. This is still to be done.

• In test_waldtest_deterministic.R, we check if the non-bootstrapped F-statistics computed in wildboottestjlr() are identical to F-statistics calculated via the fixest::wald() function.

Internal Tests: Does it matter if the bootstrap is applied to objects of type lm, feols or felm?

As fwildclusterboot and wildboottestjlr share the same preprocessing, this is outsourced to the fwildclusterboot testing suite.

s3alfisc/wildboottestjlr documentation built on June 16, 2022, 7:40 a.m.