diff --git a/python/pyarrow/src/arrow/python/arrow_to_pandas.cc b/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
index 348d352a048..85ab9b5251e 100644
--- a/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
+++ b/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
@@ -1292,24 +1292,11 @@ struct ObjectWriterVisitor {
     auto to_date_offset = [&](const MonthDayNanoIntervalType::MonthDayNanos& interval,
                               PyObject** out) {
       ARROW_DCHECK(internal::BorrowPandasDataOffsetType() != nullptr);
-      // DateOffset objects do not add nanoseconds component to pd.Timestamp.
-      // as of Pandas 1.3.3
-      // (https://github.com/pandas-dev/pandas/issues/43892).
-      // So convert microseconds and remainder to preserve data
-      // but give users more expected results.
-      int64_t microseconds = interval.nanoseconds / 1000;
-      int64_t nanoseconds;
-      if (interval.nanoseconds >= 0) {
-        nanoseconds = interval.nanoseconds % 1000;
-      } else {
-        nanoseconds = -((-interval.nanoseconds) % 1000);
-      }
 
       PyDict_SetItemString(kwargs.obj(), "months", PyLong_FromLong(interval.months));
       PyDict_SetItemString(kwargs.obj(), "days", PyLong_FromLong(interval.days));
-      PyDict_SetItemString(kwargs.obj(), "microseconds",
-                           PyLong_FromLongLong(microseconds));
-      PyDict_SetItemString(kwargs.obj(), "nanoseconds", PyLong_FromLongLong(nanoseconds));
+      PyDict_SetItemString(kwargs.obj(), "nanoseconds",
+                           PyLong_FromLongLong(interval.nanoseconds));
       *out =
           PyObject_Call(internal::BorrowPandasDataOffsetType(), args.obj(), kwargs.obj());
       RETURN_IF_PYERROR();
diff --git a/python/pyarrow/tests/test_array.py b/python/pyarrow/tests/test_array.py
index adc3e097b54..b2165b81983 100644
--- a/python/pyarrow/tests/test_array.py
+++ b/python/pyarrow/tests/test_array.py
@@ -2762,11 +2762,10 @@ def test_interval_array_from_relativedelta():
     assert arr.equals(expected)
     assert arr.to_pandas().tolist() == [
         None, DateOffset(months=13, days=8,
-                         microseconds=(
+                         nanoseconds=(
                              datetime.timedelta(seconds=1, microseconds=1,
                                                 minutes=1, hours=1) //
-                             datetime.timedelta(microseconds=1)),
-                         nanoseconds=0)]
+                             datetime.timedelta(microseconds=1)) * 1000)]
     with pytest.raises(ValueError):
         pa.array([DateOffset(years=((1 << 32) // 12), months=100)])
     with pytest.raises(ValueError):
@@ -2814,12 +2813,11 @@ def test_interval_array_from_dateoffset():
     assert arr.equals(expected)
     expected_from_pandas = [
         None, DateOffset(months=13, days=8,
-                         microseconds=(
+                         nanoseconds=(
                              datetime.timedelta(seconds=1, microseconds=1,
                                                 minutes=1, hours=1) //
-                             datetime.timedelta(microseconds=1)),
-                         nanoseconds=1),
-        DateOffset(months=0, days=0, microseconds=0, nanoseconds=0)]
+                             datetime.timedelta(microseconds=1) * 1000) + 1),
+        DateOffset(months=0, days=0, nanoseconds=0)]
 
     assert arr.to_pandas().tolist() == expected_from_pandas
 
diff --git a/python/pyarrow/tests/test_pandas.py b/python/pyarrow/tests/test_pandas.py
index 2a782de1648..19b64e45a1d 100644
--- a/python/pyarrow/tests/test_pandas.py
+++ b/python/pyarrow/tests/test_pandas.py
@@ -1733,8 +1733,7 @@ def test_month_day_nano_interval(self):
         from pandas.tseries.offsets import DateOffset
         df = pd.DataFrame({
             'date_offset': [None,
-                            DateOffset(days=3600, months=3600, microseconds=3,
-                                       nanoseconds=600)]
+                            DateOffset(days=3600, months=3600, nanoseconds=3600)]
         })
         schema = pa.schema([('date_offset', pa.month_day_nano_interval())])
         _check_pandas_roundtrip(