diff --git a/doc/source/whatsnew/v1.2.0.rst b/doc/source/whatsnew/v1.2.0.rst
index 08edc7531bcd6..e875153626b5a 100644
--- a/doc/source/whatsnew/v1.2.0.rst
+++ b/doc/source/whatsnew/v1.2.0.rst
@@ -622,6 +622,7 @@ Indexing
 - Bug in :meth:`Series.loc` and :meth:`DataFrame.loc` raises when the index was of ``object`` dtype and the given numeric label was in the index (:issue:`26491`)
 - Bug in :meth:`DataFrame.loc` returned requested key plus missing values when ``loc`` was applied to single level from a :class:`MultiIndex` (:issue:`27104`)
 - Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using a listlike indexer containing NA values (:issue:`37722`)
+- Bug in :meth:`DataFrame.loc.__setitem__` expanding an empty :class:`DataFrame` with mixed dtypes (:issue:`37932`)
 - Bug in :meth:`DataFrame.xs` ignored ``droplevel=False`` for columns (:issue:`19056`)
 - Bug in :meth:`DataFrame.reindex` raising ``IndexingError`` wrongly for empty DataFrame with ``tolerance`` not None or ``method="nearest"`` (:issue:`27315`)
 - Bug in indexing on a :class:`Series` or :class:`DataFrame` with a :class:`CategoricalIndex` using listlike indexer that contains elements that are in the index's ``categories`` but not in the index itself failing to raise ``KeyError`` (:issue:`37901`)
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index bdd79e37ba386..f66fd19f30d84 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1687,6 +1687,14 @@ def _setitem_with_indexer_split_path(self, indexer, value, name: str):
                 for loc, v in zip(ilocs, value):
                     self._setitem_single_column(loc, v, pi)
 
+            elif len(ilocs) == 1 and com.is_null_slice(pi) and len(self.obj) == 0:
+                # This is a setitem-with-expansion, see
+                #  test_loc_setitem_empty_append_expands_rows_mixed_dtype
+                # e.g. df = DataFrame(columns=["x", "y"])
+                #  df["x"] = df["x"].astype(np.int64)
+                #  df.loc[:, "x"] = [1, 2, 3]
+                self._setitem_single_column(ilocs[0], value, pi)
+
             else:
                 raise ValueError(
                     "Must have equal len keys and value "
diff --git a/pandas/tests/indexing/test_loc.py b/pandas/tests/indexing/test_loc.py
index f8ad16be607a5..cf6c2878acd9a 100644
--- a/pandas/tests/indexing/test_loc.py
+++ b/pandas/tests/indexing/test_loc.py
@@ -952,7 +952,7 @@ def test_loc_uint64(self):
         result = s.loc[[np.iinfo("uint64").max - 1, np.iinfo("uint64").max]]
         tm.assert_series_equal(result, s)
 
-    def test_loc_setitem_empty_append(self):
+    def test_loc_setitem_empty_append_expands_rows(self):
         # GH6173, various appends to an empty dataframe
 
         data = [1, 2, 3]
@@ -963,6 +963,18 @@ def test_loc_setitem_empty_append(self):
         df.loc[:, "x"] = data
         tm.assert_frame_equal(df, expected)
 
+    def test_loc_setitem_empty_append_expands_rows_mixed_dtype(self):
+        # GH#37932 same as test_loc_setitem_empty_append_expands_rows
+        #  but with mixed dtype so we go through take_split_path
+        data = [1, 2, 3]
+        expected = DataFrame({"x": data, "y": [None] * len(data)})
+
+        df = DataFrame(columns=["x", "y"])
+        df["x"] = df["x"].astype(np.int64)
+        df.loc[:, "x"] = data
+        tm.assert_frame_equal(df, expected)
+
+    def test_loc_setitem_empty_append_single_value(self):
         # only appends one value
         expected = DataFrame({"x": [1.0], "y": [np.nan]})
         df = DataFrame(columns=["x", "y"], dtype=float)