def test_limited_redundancy():
data = generate_data(0,
datatype="numpy",
const=False,
other_effects=1,
ntk=(25, 200, 5))
for i in range(0, data.x.shape[1], 7):
data.x[1, i, :] = data.x[0, i, :]
mod = FamaMacBeth(data.y, data.x)
res = mod.fit()
assert np.any(np.isnan(res.all_params))
def test_fitted_effects_residuals(data):
mod = FamaMacBeth(data.y, data.x)
res = mod.fit()
expected = mod.exog.values2d @ res.params.values
expected = pd.DataFrame(expected,
index=mod.exog.index,
columns=['fitted_values'])
assert_allclose(res.fitted_values, expected)
assert_frame_similar(res.fitted_values, expected)
expected.iloc[:, 0] = mod.dependent.values2d - expected.values
expected.columns = ['idiosyncratic']
assert_allclose(res.idiosyncratic, expected)
assert_frame_similar(res.idiosyncratic, expected)
expected.iloc[:, 0] = np.nan
expected.columns = ['estimated_effects']
assert_allclose(res.estimated_effects, expected)
assert_frame_similar(res.estimated_effects, expected)