'bartlett', bandwidth=None, force_int=True, diff=False, df_adjust=False)[source]

Estimate the cointegrating vector.

diffbool, default False

Use differenced data to estimate the residuals.

kernelstr, default “bartlett”

The string name of any of any known kernel-based long-run covariance estimators. Common choices are “bartlett” for the Bartlett kernel (Newey-West), “parzen” for the Parzen kernel and “quadratic-spectral” for the Quadratic Spectral kernel.

bandwidthint, default None

The bandwidth to use. If not provided, the optimal bandwidth is estimated from the data. Setting the bandwidth to 0 and using “unadjusted” produces the classic OLS covariance estimator. Setting the bandwidth to 0 and using “robust” produces White’s covariance estimator.

force_intbool, default False

Whether the force the estimated optimal bandwidth to be an integer.

df_adjustbool, default False

Whether the adjust the parameter covariance to account for the number of parameters estimated in the regression. If true, the parameter covariance estimator is multiplied by T/(T-k) where k is the number of regressors in the model.


The estimation results instance.

Return type