def estimator_2sls_nn_ols_control(data,
est_kwargs={},
mrg_kwargs={},
exog={},
est_kwargs_first={},
regression=True,
splits=('Train', 'Test'),
**kwargs):
# Call 2SLS estimator
betahat, expect, mrgeff = est.estimator_2sls(
data=data,
est_kwargs=est_kwargs,
est_kwargs_first=est_kwargs_first,
mrg_kwargs=mrg_kwargs,
exog=exog,
regression=regression,
constant=True,
estimate_2sls_1st=estimate_2sls_nn_1st,
estimate_2sls_2nd=est.estimate_2sls_2nd_ols_control,
splits=splits,
**kwargs)
#Return results
return betahat, expect, mrgeff
def estimator_2sls_nn_control(data,
est_kwargs={},
mrg_kwargs={},
exog={},
est_kwargs_first={},
regression=True,
splits=('Train', 'Test'),
**kwargs):
# Call 2SLS estimator
# The main point is to specify first and second stage estimation techniques.
betahat, expect, mrgeff = est.estimator_2sls(
data=data,
est_kwargs=est_kwargs,
est_kwargs_first=est_kwargs_first,
mrg_kwargs=mrg_kwargs,
exog=exog,
regression=regression,
estimate_2sls_1st=estimate_2sls_nn_1st,
estimate_2sls_2nd=estimate_2sls_nn_2nd_control,
splits=splits,
**kwargs)
#Return results
return betahat, expect, mrgeff