if dtype_backend == "pyarrow":
        from pandas.core.arrays.arrow.array import to_pyarrow_type
        from pandas.core.arrays.string_ import StringDtype

        assert not isinstance(inferred_dtype, str)

        if (
            (convert_integer and inferred_dtype.kind in "iu")
            or (convert_floating and inferred_dtype.kind in "fc")
            or (convert_boolean and inferred_dtype.kind == "b")
            or (convert_string and isinstance(inferred_dtype, StringDtype))
            or (
                inferred_dtype.kind not in "iufcb"
                and not isinstance(inferred_dtype, StringDtype)
            )
        ):
            if isinstance(inferred_dtype, PandasExtensionDtype) and not isinstance(
                inferred_dtype, DatetimeTZDtype
            ):
                base_dtype = inferred_dtype.base
            elif isinstance(inferred_dtype, (BaseMaskedDtype, ArrowDtype)):
                base_dtype = inferred_dtype.numpy_dtype
            elif isinstance(inferred_dtype, StringDtype):
                base_dtype = np.dtype(str)
            else:
                base_dtype = inferred_dtype
            if (
                base_dtype.kind == "O"  # type: ignore[union-attr]
                and input_array.size > 0
                and isna(input_array).all()
            ):
                import pyarrow as pa

                pa_type = pa.null()
            else:
                pa_type = to_pyarrow_type(base_dtype)
            if pa_type is not None:
                inferred_dtype = ArrowDtype(pa_type)
    elif dtype_backend == "numpy_nullable" and isinstance(inferred_dtype, ArrowDtype):
        # GH 53648
        inferred_dtype = _arrow_dtype_mapping()[inferred_dtype.pyarrow_dtype]

    # error: Incompatible return value type (got "Union[str, Union[dtype[Any],
    # ExtensionDtype]]", expected "Union[dtype[Any], ExtensionDtype]")
    return inferred_dtype  # type: ignore[return-value]

    def numpy_dtype(self) -> np.dtype:
        """Return an instance of the related numpy dtype"""
+        if pa.types.is_timestamp(self.pyarrow_dtype):
+            # pa.timestamp(unit).to_pandas_dtype() returns ns units
+            # regardless of the pyarrow timestamp units.
+            # This can be removed if/when pyarrow addresses it:
+            # https://github.com/apache/arrow/issues/34462
+            return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
+        if pa.types.is_duration(self.pyarrow_dtype):
+            # pa.duration(unit).to_pandas_dtype() returns ns units
+            # regardless of the pyarrow duration units
+            # This can be removed if/when pyarrow addresses it:
+            # https://github.com/apache/arrow/issues/34462
+            return np.dtype(f"timedelta64[{self.pyarrow_dtype.unit}]")
        if pa.types.is_string(self.pyarrow_dtype):
            # pa.string().to_pandas_dtype() = object which we don't want
            return np.dtype(str)
        try:
            return np.dtype(self.pyarrow_dtype.to_pandas_dtype())
        except (NotImplementedError, TypeError):
            return np.dtype(object)

            elif isinstance(inferred_dtype, (BaseMaskedDtype, ArrowDtype)):
                base_dtype = inferred_dtype.numpy_dtype