Creates covariance matrix for the estimators

        Parameters
        ----------
        method : str
            Estimation method

        Returns
        ----------
        A Covariance Matrix

def estimator_cov(self,method):
        """ Creates covariance matrix for the estimators

        Parameters
        ----------
        method : str
            Estimation method

        Returns
        ----------
        A Covariance Matrix
        """         
        
        Y = np.array([reg[self.lags:] for reg in self.data])    
        Z = self._create_Z(Y)
        if method == 'OLS':
            sigma = self.ols_covariance()
        else:           
            sigma = self.custom_covariance(self.latent_variables.get_z_values())
        return np.kron(np.linalg.inv(np.dot(Z,np.transpose(Z))), sigma)