# -*- coding: utf-8 -*-
# STATA adds a constant no matter if you want to or not,
# so I cannot test for having no intercept. This also would make
# no sense for Oaxaca. All of these stata_results
# are from using the oaxaca command in STATA.
import numpy as np
from statsmodels.datasets.ccard.data import load_pandas
from statsmodels.stats.oaxaca import OaxacaBlinder
from statsmodels.tools.tools import add_constant
pandas_df = load_pandas()
endog = pandas_df.endog.values
exog = add_constant(pandas_df.exog.values, prepend=False)
pd_endog, pd_exog = pandas_df.endog, add_constant(
pandas_df.exog, prepend=False)
class TestOaxaca(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(endog, exog, 3)
def test_results(self):
stata_results = np.array([158.7504, 321.7482, 75.45371, -238.4515])
stata_results_pooled = np.array([158.7504, 130.8095, 27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaNoSwap(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(endog, exog, 3, swap=False)
def test_results(self):
stata_results = np.array([-158.7504, -83.29674, 162.9978, -238.4515])
stata_results_pooled = np.array([-158.7504, -130.8095, -27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaPandas(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(pd_endog, pd_exog, 'OWNRENT')
def test_results(self):
stata_results = np.array([158.7504, 321.7482, 75.45371, -238.4515])
stata_results_pooled = np.array([158.7504, 130.8095, 27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaPandasNoSwap(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(pd_endog, pd_exog, 'OWNRENT', swap=False)
def test_results(self):
stata_results = np.array([-158.7504, -83.29674, 162.9978, -238.4515])
stata_results_pooled = np.array([-158.7504, -130.8095, -27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaNoConstPassed(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(pandas_df.endog.values,
pandas_df.exog.values,
3, hasconst=False)
def test_results(self):
stata_results = np.array([158.7504, 321.7482, 75.45371, -238.4515])
stata_results_pooled = np.array([158.7504, 130.8095, 27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaNoSwapNoConstPassed(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(pandas_df.endog.values,
pandas_df.exog.values,
3, hasconst=False, swap=False)
def test_results(self):
stata_results = np.array([-158.7504, -83.29674, 162.9978, -238.4515])
stata_results_pooled = np.array([-158.7504, -130.8095, -27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaPandasNoConstPassed(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(pandas_df.endog,
pandas_df.exog,
'OWNRENT', hasconst=False)
def test_results(self):
stata_results = np.array([158.7504, 321.7482, 75.45371, -238.4515])
stata_results_pooled = np.array([158.7504, 130.8095, 27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)
class TestOaxacaPandasNoSwapNoConstPassed(object):
@classmethod
def setup_class(cls):
cls.model = OaxacaBlinder(pandas_df.endog, pandas_df.exog,
'OWNRENT', hasconst=False, swap=False)
def test_results(self):
stata_results = np.array([-158.7504, -83.29674, 162.9978, -238.4515])
stata_results_pooled = np.array([-158.7504, -130.8095, -27.94091])
char, coef, inter, gap = self.model.three_fold().params
unexp, exp, gap = self.model.two_fold().params
np.testing.assert_almost_equal(gap, stata_results[0], 3)
np.testing.assert_almost_equal(char, stata_results[1], 3)
np.testing.assert_almost_equal(coef, stata_results[2], 3)
np.testing.assert_almost_equal(inter, stata_results[3], 3)
np.testing.assert_almost_equal(gap, stata_results_pooled[0], 3)
np.testing.assert_almost_equal(exp, stata_results_pooled[1], 3)
np.testing.assert_almost_equal(unexp, stata_results_pooled[2], 3)