statsmodels.sandbox.regression.gmm.LinearIVGMM¶
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class
statsmodels.sandbox.regression.gmm.
LinearIVGMM
(endog, exog, instrument, k_moms=None, k_params=None, missing='none', **kwds)[source]¶ class for linear instrumental variables models estimated with GMM
Uses closed form expression instead of nonlinear optimizers for each step of the iterative GMM.
The model is assumed to have the following moment condition
E( z * (y - x beta)) = 0Where y is the dependent endogenous variable, x are the explanatory variables and z are the instruments. Variables in x that are exogenous need also be included in z.
Notation Warning: our name exog stands for the explanatory variables, and includes both exogenous and explanatory variables that are endogenous, i.e. included endogenous variables
Parameters: endog : array_like
dependent endogenous variable
exog : array_like
explanatory, right hand side variables, including explanatory variables that are endogenous
instruments : array_like
Instrumental variables, variables that are exogenous to the error in the linear model containing both included and excluded exogenous variables
Methods
calc_weightmatrix
(moms[, weights_method, ...])calculate omega or the weighting matrix fit
([start_params, maxiter, inv_weights, ...])Estimate parameters using GMM and return GMMResults fitgmm
(start[, weights, optim_method])estimate parameters using GMM for linear model fitgmm_cu
(start[, optim_method, optim_args])estimate parameters using continuously updating GMM fititer
(start[, maxiter, start_invweights, ...])iterative estimation with updating of optimal weighting matrix fitstart
()get_error
(params)gmmobjective
(params, weights)objective function for GMM minimization gmmobjective_cu
(params[, weights_method, wargs])objective function for continuously updating GMM minimization gradient_momcond
(params, **kwds)momcond
(params)momcond_mean
(params)mean of moment conditions, predict
(params[, exog])score
(params, weights, **kwds)score_cu
(params[, epsilon, centered])start_weights
([inv])Attributes
endog_names
exog_names
results_class