diff --git a/doc/source/whatsnew/v2.3.0.rst b/doc/source/whatsnew/v2.3.0.rst
index c999d726be823..5faf73a696e04 100644
--- a/doc/source/whatsnew/v2.3.0.rst
+++ b/doc/source/whatsnew/v2.3.0.rst
@@ -106,6 +106,7 @@ Conversion
 
 Strings
 ^^^^^^^
+- Bug in :meth:`Series.__pos__` and :meth:`DataFrame.__pos__` did not raise for :class:`StringDtype` with ``storage="pyarrow"`` (:issue:`60710`)
 - Bug in :meth:`Series.rank` for :class:`StringDtype` with ``storage="pyarrow"`` incorrectly returning integer results in case of ``method="average"`` and raising an error if it would truncate results (:issue:`59768`)
 - Bug in :meth:`Series.replace` with :class:`StringDtype` when replacing with a non-string value was not upcasting to ``object`` dtype (:issue:`60282`)
 - Bug in :meth:`Series.str.replace` when ``n < 0`` for :class:`StringDtype` with ``storage="pyarrow"`` (:issue:`59628`)
diff --git a/pandas/core/arrays/string_arrow.py b/pandas/core/arrays/string_arrow.py
index c15e50f698a3d..c8aea6f6bab5a 100644
--- a/pandas/core/arrays/string_arrow.py
+++ b/pandas/core/arrays/string_arrow.py
@@ -51,6 +51,7 @@
     from pandas._typing import (
         ArrayLike,
         Dtype,
+        Self,
         npt,
     )
 
@@ -476,6 +477,9 @@ def _cmp_method(self, other, op):
                 return result.to_numpy(np.bool_, na_value=False)
         return result
 
+    def __pos__(self) -> Self:
+        raise TypeError(f"bad operand type for unary +: '{self.dtype}'")
+
 
 class ArrowStringArrayNumpySemantics(ArrowStringArray):
     _na_value = np.nan
diff --git a/pandas/tests/frame/test_unary.py b/pandas/tests/frame/test_unary.py
index a76d33e922486..a48b5c51f9ca7 100644
--- a/pandas/tests/frame/test_unary.py
+++ b/pandas/tests/frame/test_unary.py
@@ -3,9 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
-from pandas.compat import HAS_PYARROW
 from pandas.compat.numpy import np_version_gte1p25
 
 import pandas as pd
@@ -120,9 +117,6 @@ def test_pos_object(self, df):
         tm.assert_frame_equal(+df, df)
         tm.assert_series_equal(+df["a"], df["a"])
 
-    @pytest.mark.xfail(
-        using_string_dtype() and HAS_PYARROW, reason="TODO(infer_string)"
-    )
     @pytest.mark.parametrize(
         "df",
         [