The heteroscedasticity- and autocorrelation-consistent (HAC) covariance matrix estimator is supported, which consistently estimate the covariance matrix even when the heteroscedasticity and autocorrelation structure might be unknown or misspecified. Five types of kernel functions—Bartlett, Parzen, quadratic spectral, truncated, and Tukey-Hanning kernels—are supported. The bandwidth parameter can be estimated using the Andrews (1991) method, the Newey and West (1994) method, or a flexible equation based on sample size. The prewhitening feature and adjustment of degrees of freedom are supported. The well-known Newey-West estimator is also supported.

Multiple structural change tests proposed by Bai and Perron (1998) are supported. Specifically, these are the test of no break versus a fixed number of breaks ( test); the equal and unequal weighted versions of double maximum tests of no break versus an unknown number of breaks given some upper bound ( test and test); and the test of versus breaks ( test). The tests can be applied to both pure and partial structural change models. The p-value of each test, based on the simulation of the limiting distribution, and the confidence intervals of parameter estimators, including the break dates, are also provided. The constraints on the distribution of the errors and regressors across segments can be imposed. For estimating the covariance matrix the HAC estimator is supported.

The Shin cointegration tests with p-values are supported.

The p-values for the ERS optimal point unit root test, ERS DF-GLS unit root test, and KPSS unit root test are provided.

The status of ERS and Ng-Perron unit root tests changed from experimental to production.