gEconpy.model.model.stationary_covariance_matrix

gEconpy.model.model.stationary_covariance_matrix(model, T=None, R=None, shock_std_dict=None, shock_cov_matrix=None, shock_std=None, return_df=True, **solve_model_kwargs)

Compute the stationary covariance matrix of the solved system.

Solution is found by solving the associated discrete lyapunov equation.

In order to construct the shock covariance matrix, exactly one of shock_dict, shock_cov_matrix, or shock_std should be provided.

Parameters:

model: Model

DSGE Model assoicated with T and R

T: np.ndarray, optional

Transition matrix of the solved system. If None, this will be computed using the model’s solve_model method.

R: np.ndarray

Selection matrix of the solved system. If None, this will be computed using the model’s solve_model method.

shock_std_dict: dict, optional

A dictionary of shock sizes to be used to compute the stationary covariance matrix.

shock_cov_matrix: array, optional

An (n_shocks, n_shocks) covariance matrix describing the exogenous shocks

shock_std: float, optional

Standard deviation of all model shocks.

return_df: bool

If True, return the covariance matrix as a DataFrame

**solve_model_kwargs

Arguments forwarded to the solve_model method. Ignored if T and R are provided.

Returns:

Sigma: np.ndarray | pd.DataFrame

Stationary covariance matrix of the linearized model. Datatype depends on the variable of the return_df argument.