diff --git a/ci/run_tests.sh b/ci/run_tests.sh
index 6a70ea1df3e71..90dec1a2f3e90 100755
--- a/ci/run_tests.sh
+++ b/ci/run_tests.sh
@@ -11,7 +11,7 @@ echo PYTHONHASHSEED=$PYTHONHASHSEED
 COVERAGE="-s --cov=pandas --cov-report=xml --cov-append --cov-config=pyproject.toml"
 
 # TODO: Support NEP 50 and remove NPY_PROMOTION_STATE
-PYTEST_CMD="NPY_PROMOTION_STATE=legacy MESONPY_EDITABLE_VERBOSE=1 PYTHONDEVMODE=1 PYTHONWARNDEFAULTENCODING=1 pytest -r fEs -n $PYTEST_WORKERS --dist=loadfile $TEST_ARGS $COVERAGE $PYTEST_TARGET"
+PYTEST_CMD="NPY_PROMOTION_STATE=legacy MESONPY_EDITABLE_VERBOSE=1 PYTHONDEVMODE=1 PYTHONWARNDEFAULTENCODING=1 pytest -v --setup-show -r fEs -n $PYTEST_WORKERS --dist=loadfile $TEST_ARGS $COVERAGE $PYTEST_TARGET"
 
 if [[ "$PATTERN" ]]; then
   PYTEST_CMD="$PYTEST_CMD -m \"$PATTERN\""
diff --git a/pandas/tests/io/parser/conftest.py b/pandas/tests/io/parser/conftest.py
index 471f525e229e5..7aaba40d0d95f 100644
--- a/pandas/tests/io/parser/conftest.py
+++ b/pandas/tests/io/parser/conftest.py
@@ -134,9 +134,10 @@ def all_parsers(request):
         pytest.importorskip("pyarrow", VERSIONS["pyarrow"])
         # Try finding a way to disable threads all together
         # for more stable CI runs
-        import pyarrow
+        # import pyarrow
 
-        pyarrow.set_cpu_count(1)
+        # pyarrow.set_cpu_count(1)
+        # pyarrow.set_io_thread_count(1)
     return parser
 
 
diff --git a/pandas/tests/io/parser/test_index_col.py b/pandas/tests/io/parser/test_index_col.py
index b938b129ac38d..95c0096ae864b 100644
--- a/pandas/tests/io/parser/test_index_col.py
+++ b/pandas/tests/io/parser/test_index_col.py
@@ -8,6 +8,8 @@
 import numpy as np
 import pytest
 
+from pandas.compat import is_ci_environment
+
 from pandas import (
     DataFrame,
     Index,
@@ -94,7 +96,6 @@ def test_infer_index_col(all_parsers):
     tm.assert_frame_equal(result, expected)
 
 
-@xfail_pyarrow  # CSV parse error: Empty CSV file or block
 @pytest.mark.parametrize(
     "index_col,kwargs",
     [
@@ -134,9 +135,20 @@ def test_infer_index_col(all_parsers):
         ),
     ],
 )
-def test_index_col_empty_data(all_parsers, index_col, kwargs):
+def test_index_col_empty_data(all_parsers, index_col, kwargs, request):
     data = "x,y,z"
     parser = all_parsers
+    if parser.engine == "pyarrow":
+        if is_ci_environment():
+            pytest.skip(f"Can hang in CI environment with {parser.engine=}")
+        else:
+            mark = pytest.mark.xfail(
+                reason=(
+                    "CSV parse error: Empty CSV file or block: "
+                    "cannot infer number of columns"
+                )
+            )
+            request.applymarker(mark)
     result = parser.read_csv(StringIO(data), index_col=index_col)
 
     expected = DataFrame(**kwargs)
diff --git a/pandas/tests/io/parser/test_parse_dates.py b/pandas/tests/io/parser/test_parse_dates.py
index 47e654fc606af..6987df4783dda 100644
--- a/pandas/tests/io/parser/test_parse_dates.py
+++ b/pandas/tests/io/parser/test_parse_dates.py
@@ -19,6 +19,7 @@
 
 from pandas._libs.tslibs import parsing
 from pandas._libs.tslibs.parsing import py_parse_datetime_string
+from pandas.compat import is_ci_environment
 
 import pandas as pd
 from pandas import (
@@ -1752,13 +1753,23 @@ def test_parse_timezone(all_parsers):
     tm.assert_frame_equal(result, expected)
 
 
-@xfail_pyarrow  # pandas.errors.ParserError: CSV parse error
 @pytest.mark.parametrize(
     "date_string",
     ["32/32/2019", "02/30/2019", "13/13/2019", "13/2019", "a3/11/2018", "10/11/2o17"],
 )
-def test_invalid_parse_delimited_date(all_parsers, date_string):
+def test_invalid_parse_delimited_date(all_parsers, date_string, request):
     parser = all_parsers
+    if parser.engine == "pyarrow":
+        if is_ci_environment():
+            pytest.skip(f"Can hang in CI environment with {parser.engine=}")
+        else:
+            mark = pytest.mark.xfail(
+                reason=(
+                    "CSV parse error: Empty CSV file or block: "
+                    "cannot infer number of columns"
+                )
+            )
+            request.applymarker(mark)
     expected = DataFrame({0: [date_string]}, dtype="object")
     result = parser.read_csv(
         StringIO(date_string),