def test_two_way_clustering(data):
mod = PooledOLS(data.y, data.x)
y = PanelData(data.y)
entity_clusters = pd.DataFrame(y.entity_ids, index=y.index)
vc1 = PanelData(data.vc1)
clusters = vc1.copy()
clusters.dataframe['var.cluster.entity'] = entity_clusters
clusters._frame = clusters._frame.astype(np.int64)
res = mod.fit(cov_type='clustered', clusters=clusters, debiased=False)
y = mod.dependent.dataframe.copy()
x = mod.exog.dataframe.copy()
y.index = np.arange(len(y))
x.index = y.index
clusters = mod.reformat_clusters(clusters)
ols_mod = IV2SLS(y, x, None, None)
ols_res = ols_mod.fit(cov_type='clustered', clusters=clusters.dataframe)
assert_results_equal(res, ols_res)
def test_cov_equiv_cluster(data):
mod = PooledOLS(data.y, data.x)
res = mod.fit(cov_type='clustered', cluster_entity=True, debiased=False)
y = PanelData(data.y)
clusters = pd.DataFrame(y.entity_ids, index=y.index)
res2 = mod.fit(cov_type='clustered', clusters=clusters, debiased=False)
assert_results_equal(res, res2)
res = mod.fit(cov_type='clustered', cluster_time=True, debiased=False)
clusters = pd.DataFrame(y.time_ids, index=y.index)
res2 = mod.fit(cov_type='clustered', clusters=clusters, debiased=False)
assert_results_equal(res, res2)
res = mod.fit(cov_type='clustered', clusters=data.vc1, debiased=False)
y = mod.dependent.dataframe.copy()
x = mod.exog.dataframe.copy()
y.index = np.arange(len(y))
x.index = y.index
clusters = mod.reformat_clusters(data.vc1)
ols_mod = IV2SLS(y, x, None, None)
res2 = ols_mod.fit(cov_type='clustered', clusters=clusters.dataframe, debiased=False)
assert_results_equal(res, res2)
