mcf_main.ModifiedCausalForest.predict_iv

ModifiedCausalForest.predict_iv(data_df)

Compute all effects for instrument mcf (possibly in 2 differnt ways).

train_iv() method must be run beforehand.

Parameters

data_df (DataFrame) – Data used to compute the predictions. It must contain information about features (and treatment if effects for treatment specific subpopulations are desired as well).

Returns

• results_global (Dictionary.) – Contains the results. This dictionary has the following structure: ‘ate’: LATE, ‘ate_se’: Standard error of LATE, ‘ate_effect_list’: List of names of estimated effects, ‘ate_1st’: ATE 1st stage, ‘ate_1st_se’: Standard error of ATE (1st) ‘ate 1st_effect_list’: List of names of estimated effects (1st), ‘ate_redf’: ATE reduced form, ‘ate_redf_se’: Standard error of ATE of reduced form, ‘ate redf_effect_list’: List of names of estimated effects (red.f.), ‘gate’: LGATE, ‘gate_se’: SE of LGATE, ‘gate_diff’: LGATE minus LATE, ‘gate_diff_se’: Standard error of LGATE minus LATE, ‘cbgate’: LCBGATE (all covariates balanced), ‘cbgate_se’: Standard error of LCBGATE, ‘cbgate_diff’: LCBGATE minus LATE, ‘cbgate_diff_se’: Standard error of LCBGATE minus LATE, ‘bgate’: LBGATE (only prespecified covariates balanced), ‘bgate_se’: Standard error of LBGATE, ‘bgate_diff’: LBGATE minus LATE, ‘bgate_diff_se’: Standard errror of LBGATE minus LATE, ‘gate_names_values’: Dictionary: Order of gates parameters and name and values of LGATE effects. ‘iate’: LIATE, ‘iate_se’: Standard error of LIATE, ‘iate_1st’: IATE (1st stage), ‘iate_1st_se’: Standard error of IATE (1st stage), ‘iate_redf’: IATE (reduced form), ‘iate_redf_se’: Standard error of IATE (reduced form), ‘iate_eff’: (More) Efficient LIATE (LIATE estimated twice and averaged where role of tree_building and tree_filling sample is exchanged), iate_1st_eff’: (More) Efficient IATE (1st stage), iate_redf_eff’: (More) Efficient IATE (reduced form), ‘iate_data_df’: DataFrame with LIATEs, ‘iate_1st_data_df’: DataFrame with IATEs (1st stage), ‘iate_redf_data_df’: DataFrame with IATEs (reduced form), ‘iate_names_dic’: Dictionary containing names of LIATEs, ‘iate_1st_names_dic’: Dictionary containing names of IATEs (1st), ‘iate_redf_dic’: Dictionary containing names of LIATEs (red.f.), ‘qiate’: QLIATE, ‘qiate_se’: Standard error of QLIATE, ‘bala_1st’: Effects of balancing tests (1st stage), ‘bala_1st_se’: Standard error of effects of balancing tests (1st), ‘bala_1st_effect_list’: Names of effects of balancing tests (1st), ‘bala_redf’: Effects of balancing tests (reduced form), ‘bala_redf_se’: Standard error of effects of balancing tests (red.), ‘bala_redf_effect_list’: Names of effects of balancing tests (red.). ‘common_support_probabilities’: pd.DataFrame containing treatment probabilities for all treatments, the identifier of the observation, and a dummy variable indicating whether the observation is inside or outside the common support. None if _int_with_output is False. ‘path_output’: Pathlib object, location of directory in which output is saved.

  It is empty if the IV estimation method ‘global’ has not been used.

• results_local (Dictionary.) – Same content as results_wald. It is empty if the IV estimation method ‘local’ has not been used.