estimation.Feiv

estimation.Feiv(self, Y, X, endogvar, Z, weights, coefnames_x, coefnames_z, collin_tol, weights_name, weights_type, solver='np.linalg.solve')

Non user-facing class to estimate an IV model using a 2SLS estimator.

Inherits from the Feols class. Users should not directly instantiate this class, but rather use the feols() function. Note that no demeaning is performed in this class: demeaning is performed in the FixestMulti class (to allow for caching of demeaned variables for multiple estimation).

Parameters

Name	Type	Description	Default
Y	np.ndarray	Dependent variable, a two-dimensional np.array.	required
X	np.ndarray	Independent variables, a two-dimensional np.array.	required
endgvar	np.ndarray	Endogenous Indenpendent variables, a two-dimensional np.array.	required
Z	np.ndarray	Instruments, a two-dimensional np.array.	required
weights	np.ndarray	Weights, a one-dimensional np.array.	required
coefnames_x	list	Names of the coefficients of X.	required
coefnames_z	list	Names of the coefficients of Z.	required
collin_tol	float	Tolerance for collinearity check.	required
solver	str	Solver to use for the estimation. Alternative is ‘np.linalg.lstsq’.	'np.linalg.solve'
weights_name	Optional[str]	Name of the weights variable.	required
weights_type	Optional[str]	Type of the weights variable. Either “aweights” for analytic weights or “fweights” for frequency weights.	required

Attributes

Name	Type	Description
_Z	np.ndarray	Processed instruments after handling multicollinearity.
_coefnames_z	list	Names of coefficients for Z after handling multicollinearity.
_collin_vars_z	list	Variables identified as collinear in Z.
_collin_index_z	list	Indices of collinear variables in Z.
_is_iv	bool	Indicator if instrumental variables are used.
_support_crv3_inference	bool	Indicator for supporting CRV3 inference.
_support_iid_inference	bool	Indicator for supporting IID inference.
_tZX	np.ndarray	Transpose of Z times X.
_tXZ	np.ndarray	Transpose of X times Z.
_tZy	np.ndarray	Transpose of Z times Y.
_tZZinv	np.ndarray	Inverse of transpose of Z times Z.
_beta_hat	np.ndarray	Estimated regression coefficients.
_Y_hat_link	np.ndarray	Predicted values of the regression model.
_u_hat	np.ndarray	Residuals of the regression model.
_scores	np.ndarray	Scores used in the regression.
_hessian	np.ndarray	Hessian matrix used in the regression.
_bread	np.ndarray	Bread matrix used in the regression.
_pi_hat	np.ndarray	Estimated coefficients from 1st stage regression
_X_hat	np.ndarray	Predicted values of the 1st stage regression
_v_hat	np.ndarray	Residuals of the 1st stage regression

Raises

Type	Description
ValueError	If Z is not a two-dimensional array.

Methods

Name	Description
get_fit	Fit a IV model using a 2SLS estimator.

get_fit

estimation.Feiv.get_fit()

Fit a IV model using a 2SLS estimator.