arch.unitroot.cointegration.FullyModifiedOLS.fit

FullyModifiedOLS.fit(kernel='bartlett', bandwidth=None, force_int=True, diff=False, df_adjust=False)[source]

Estimate the cointegrating vector.

Parameters
  • diff (bool, default False) – Use differenced data to estimate the residuals.

  • kernel (str, 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.

  • bandwidth (int, 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_int (bool, default False) – Whether the force the estimated optimal bandwidth to be an integer.

  • df_adjust (bool, 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.

Returns

The estimation results instance.

Return type

CointegrationAnalysisResults