linearmodels.iv.model.IV2SLS¶

class linearmodels.iv.model.IV2SLS(dependent, exog, endog, instruments, *, weights=None)[source]¶

Estimation of IV models using two-stage least squares

Parameters:¶

dependent : array_like¶

Endogenous variables (nobs by 1)

exog : array_like¶

Exogenous regressors (nobs by nexog)

endog : array_like¶

Endogenous regressors (nobs by nendog)

instruments : array_like¶

Instrumental variables (nobs by ninstr)

weights : array_like¶

Observation weights used in estimation

Notes

The 2SLS estimator is defined

\[\begin{split}\hat{\beta}_{2SLS} & =(X'Z(Z'Z)^{-1}Z'X)^{-1}X'Z(Z'Z)^{-1}Z'Y\\ & =(\hat{X}'\hat{X})^{-1}\hat{X}'Y\\ \hat{X} & =Z(Z'Z)^{-1}Z'X\end{split}\]

The 2SLS estimator is a special case of a k-class estimator with \(\kappa=1\),

Todo

• VCV: bootstrap

See also

IVLIML, IVGMM, IVGMMCUE

Methods

estimate_parameters(x, y, z, kappa)	Parameter estimation without error checking
fit(*[, cov_type, debiased])	Estimate model parameters
from_formula(formula, data, *[, weights])	type formula: str
predict(params, *[, exog, endog, data, eval_env])	Predict values for additional data
resids(params)	Compute model residuals
wresids(params)	Compute weighted model residuals

Properties

formula	Formula used to create the model
has_constant	Flag indicating the model includes a constant or equivalent
isnull	Locations of observations with missing values
notnull	Locations of observations included in estimation