linearmodels.iv.model.IV2SLS¶
- class IV2SLS(dependent, exog, endog, instruments, *, weights=None)[source]¶
Estimation of IV models using two-stage least squares
- Parameters:
- dependentarray_like
Endogenous variables (nobs by 1)
- exogarray_like
Exogenous regressors (nobs by nexog)
- endogarray_like
Endogenous regressors (nobs by nendog)
- instrumentsarray_like
Instrumental variables (nobs by ninstr)
- weightsarray_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
- Attributes:
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
Methods
estimate_parameters
(x, y, z, kappa)Parameter estimation without error checking
fit
(*[, cov_type, debiased])Estimate model parameters
from_formula
(formula, data, *[, weights])- Parameters:
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 used to create the model
Flag indicating the model includes a constant or equivalent
Locations of observations with missing values
Locations of observations included in estimation