diff --git a/pandas/indexes/category.py b/pandas/indexes/category.py
index 3b7c660f5faa1..1496f3b69aa5a 100644
--- a/pandas/indexes/category.py
+++ b/pandas/indexes/category.py
@@ -8,6 +8,7 @@
                                     deprecate_kwarg)
 from pandas.core.config import get_option
 from pandas.indexes.base import Index, _index_shared_docs
+from pandas.types.concat import union_categoricals
 import pandas.core.base as base
 import pandas.core.common as com
 import pandas.core.missing as missing
@@ -575,6 +576,33 @@ def append(self, other):
         codes = np.concatenate([c.codes for c in to_concat])
         return self._create_from_codes(codes, name=name)
 
+    def _join_non_unique(self, other, how='left', return_indexers=False):
+        """
+        Must be overridden because np.putmask() does not work on Categorical.
+        """
+
+        from pandas.tools.merge import _get_join_indexers
+
+        left_idx, right_idx = _get_join_indexers([self.values],
+                                                 [other._values], how=how,
+                                                 sort=True)
+
+        left_idx = com._ensure_platform_int(left_idx)
+        right_idx = com._ensure_platform_int(right_idx)
+
+        take_left = left_idx != -1
+
+        join_index = union_categoricals([self.values[left_idx[take_left]],
+                                         other._values[right_idx[~take_left]]],
+                                        masks=[take_left, ~take_left])
+
+        join_index = self._wrap_joined_index(join_index, other)
+
+        if return_indexers:
+            return join_index, left_idx, right_idx
+        else:
+            return join_index
+
     @classmethod
     def _add_comparison_methods(cls):
         """ add in comparison methods """
diff --git a/pandas/tests/indexes/common.py b/pandas/tests/indexes/common.py
index d6f7493bb25f9..56387d054dbdd 100644
--- a/pandas/tests/indexes/common.py
+++ b/pandas/tests/indexes/common.py
@@ -225,9 +225,8 @@ def test_copy_name(self):
 
             s1 = Series(2, index=first)
             s2 = Series(3, index=second[:-1])
-            if not isinstance(index, CategoricalIndex):  # See GH13365
-                s3 = s1 * s2
-                self.assertEqual(s3.index.name, 'mario')
+            s3 = s1 * s2
+            self.assertEqual(s3.index.name, 'mario')
 
     def test_ensure_copied_data(self):
         # Check the "copy" argument of each Index.__new__ is honoured
diff --git a/pandas/types/concat.py b/pandas/types/concat.py
index 53db9ddf79a5c..322c6820e4c0a 100644
--- a/pandas/types/concat.py
+++ b/pandas/types/concat.py
@@ -201,7 +201,7 @@ def convert_categorical(x):
         return Categorical(concatted, rawcats)
 
 
-def union_categoricals(to_union):
+def union_categoricals(to_union, masks=None):
     """
     Combine list-like of Categoricals, unioning categories. All
     must have the same dtype, and none can be ordered.
@@ -211,6 +211,10 @@ def union_categoricals(to_union):
     Parameters
     ----------
     to_union : list-like of Categoricals
+    masks: list-like of boolean arrays, all of same shape
+        They indicate where to position the values: their shape will be the
+        shape of the returned array. If None, members of "to_union" will be
+        just concatenated.
 
     Returns
     -------
@@ -243,11 +247,17 @@ def union_categoricals(to_union):
     unique_cats = cats.append([c.categories for c in to_union[1:]]).unique()
     categories = Index(unique_cats)
 
-    new_codes = []
-    for c in to_union:
-        indexer = categories.get_indexer(c.categories)
-        new_codes.append(indexer.take(c.codes))
-    codes = np.concatenate(new_codes)
+    if masks is None:
+        new_codes = []
+        for c in to_union:
+            indexer = categories.get_indexer(c.categories)
+            new_codes.append(indexer.take(c.codes))
+        codes = np.concatenate(new_codes)
+    else:
+        codes = np.empty(shape=masks[0].shape, dtype=first.codes.dtype)
+        for c, mask in zip(to_union, masks):
+            indexer = categories.get_indexer(c.categories)
+            codes[mask] = indexer.take(c.codes)
     return Categorical(codes, categories=categories, ordered=False,
                        fastpath=True)