fwildclusterboot v0.12 (CRAN release)

fwildclusterboot 0.12

This is the first CRAN release since version 0.9. It comes with a set of new features, but also potentially breaking changes. This section summarizes all developments since version 0.9.

Potentially breaking changes:

• boottest()'s function argument boot_algo has been renamed to engine
• the setBoottest_boot_algo() function was renamed to setBoottest_engine()

Bug fixes and internal changes

• When a multi-parameter hypothesis of the form R beta = r was tested, the heteroskedastic wild bootstrap would nevertheless always test
  "beta_k = 0" vs "beta_k != 0", with "beta_k = param". I am sorry for that bug!
• The Matrix.utils has been removed from CRAN - it has been replaced by custom functions for internal use.

New features and Improvements

• A new function argument has been added - bootstrap_type. In combination with the impose_null function argument, it allows to choose between different cluster bootstrap types - WCx11, WCx13, WCx31, WCx33. For more details on these methods, see the working paper by MacKinnon, Nielsen & Webb (2022). Currently, these new bootstrap types only compute p-values. Adding support for confidence intervals is work in progress.
• A boot_aggregate() method now supports the aggregation of coefficients in staggered difference-in-differences following the methods by Sun & Abraham (2021, Journal of Econometrics) in combination with the sunab() function from fixest. Essentially, boot_aggregate() is a copy of aggregate.fixest: the only difference is that inference is powered by a wild bootstrap.
• The heteroskedastic bootstrap is now significantly faster, and WCR21 and WCR31 versions are now supported (i.e. HC2 and HC3 'imposed' on the bootstrap dgp.)