BUG: pd.Series.replace does not preserve the original dtype

pandas/core/internals/blocks.py

@@ -1010,7 +1010,14 @@ def coerce_to_target_dtype(self, other):
         if is_dtype_equal(self.dtype, dtype):
             return self
 
-        if self.is_bool or is_object_dtype(dtype) or is_bool_dtype(dtype):
+        if (
+            is_extension_array_dtype(self.dtype)
+            and not is_categorical_dtype(self.dtype)
+            and not self.is_datetime
+        ):
+            dtype = self.dtype
+
+        elif self.is_bool or is_object_dtype(dtype) or is_bool_dtype(dtype):
             # we don't upcast to bool
             return self.astype(object)
 

pandas/tests/series/methods/test_replace.py

@@ -250,7 +250,7 @@ def test_replace2(self):
     def test_replace_with_dictlike_and_string_dtype(self):
         # GH 32621
         s = pd.Series(["one", "two", np.nan], dtype="string")
-        expected = pd.Series(["1", "2", np.nan])
+        expected = pd.Series(["1", "2", np.nan], dtype="string")
         result = s.replace({"one": "1", "two": "2"})
         tm.assert_series_equal(expected, result)
 
@@ -402,3 +402,20 @@ def test_replace_only_one_dictlike_arg(self):
         msg = "Series.replace cannot use dict-value and non-None to_replace"
         with pytest.raises(ValueError, match=msg):
             ser.replace(to_replace, value)
+
+    @pytest.mark.parametrize(
+        "series, to_replace, expected",
+        [
+            (
+                pd.Series(["one", "two"], dtype="string"),
+                {"one": "1", "two": "2"},
+                "string",
+            ),
+            (pd.Series([1, 2], dtype="int64"), {1: 10, 2: 20}, "int64"),
+            (pd.Series([True, False], dtype="bool"), {True: False}, "bool"),
+        ],
+    )
+    def test_replace_dtype(self, series, to_replace, expected):
+        # GH 33484
+        result = str(series.replace(to_replace).dtype)
+        assert expected == result