BUG: Create empty dataframe with string dtype fails

doc/source/whatsnew/v1.1.0.rst

@@ -755,7 +755,7 @@ ExtensionArray
 - Fixed bug where :meth:`Series.value_counts` would raise on empty input of ``Int64`` dtype (:issue:`33317`)
 - Fixed bug in :class:`Series` construction with EA dtype and index but no data or scalar data fails (:issue:`26469`)
 - Fixed bug that caused :meth:`Series.__repr__()` to crash for extension types whose elements are multidimensional arrays (:issue:`33770`).
-
+- Fixed bug where :meth:`init_dict` would raise on empty input (:issue:`27953` and :issue:`33623`)
 
 Other
 ^^^^^

pandas/core/internals/construction.py

@@ -257,7 +257,10 @@ def init_dict(data: Dict, index, columns, dtype: Optional[DtypeObj] = None):
 
         # no obvious "empty" int column
         if missing.any() and not is_integer_dtype(dtype):
-            if dtype is None or np.issubdtype(dtype, np.flexible):
+            if dtype is None or (
+                not is_extension_array_dtype(dtype)
+                and np.issubdtype(dtype, np.flexible)
+            ):
                 # GH#1783
                 nan_dtype = np.dtype(object)
             else:

pandas/tests/extension/arrow/test_bool.py

@@ -69,6 +69,10 @@ def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
         # pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays
         super().test_series_constructor_scalar_na_with_index(dtype, na_value)
 
+    @pytest.mark.xfail(reason="raises AssertionError")
+    def test_construct_empty_dataframe(self, dtype):
+        super().test_construct_empty_dataframe(dtype)
+
 
 class TestReduce(base.BaseNoReduceTests):
     def test_reduce_series_boolean(self):

pandas/tests/extension/base/constructors.py

@@ -108,3 +108,11 @@ def test_pandas_array_dtype(self, data):
         result = pd.array(data, dtype=np.dtype(object))
         expected = pd.arrays.PandasArray(np.asarray(data, dtype=object))
         self.assert_equal(result, expected)
+
+    def test_construct_empty_dataframe(self, dtype):
+        # GH 33623
+        result = pd.DataFrame(columns=["a"], dtype=dtype)
+        expected = pd.DataFrame(
+            {"a": pd.array([], dtype=dtype)}, index=pd.Index([], dtype="object")
+        )
+        self.assert_frame_equal(result, expected)