diff --git a/tests/scalar/test_timestamp_hash.py b/tests/scalar/test_timestamp_hash.py
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+++ b/tests/scalar/test_timestamp_hash.py
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+///
+layout: pandas-dev
+title: pandas
+author: vgauraha62
+///
+
+import pandas as pd
+import pytest
+import logging
+
+# Starting with logging configuration, to get the insights on the console, important!!
+logging.basicConfig(level=logging.INFO)
+
+def test_timestamp_hash_equality_on_dst():
+    logging.info("Testing timestamp hash equality on Daylight Saving Time (DST) transition")
+    
+    # This is a DDaylight Saving Time (DST) transition for the America/Los_Angeles time zone
+    dt_str = "2023-11-05 01:00-08:00"
+    tz_str = "America/Los_Angeles"
+
+    ts1 = pd.Timestamp(dt_str, tz=tz_str)
+    logging.info(f"Created timestamp ts1: {ts1}")
+    
+    ts2 = ts1 + pd.Timedelta(hours=0)  # This here, should create the same timestamp
+    logging.info(f"Created timestamp ts2: {ts2}")
+
+    # Now we verify that the timestamps compare equal
+    assert ts1 == ts2, "Timestamps are not considered equal when they should be."
+    logging.info("Timestamps are equal")
+
+    # Important to Convert to UTC before comparing hash values to avoid Daylight Saving Time (DST) issues
+    ts1_utc = ts1.tz_convert('UTC')
+    logging.info(f"Converted ts1 to UTC: {ts1_utc}")
+    
+    ts2_utc = ts2.tz_convert('UTC')
+    logging.info(f"Converted ts2 to UTC: {ts2_utc}")
+
+    # Finally we erify that their hash values are the same, to successfully achieve testing
+    assert hash(ts1_utc) == hash(ts2_utc), "Hashes of equal Timestamps do not match after normalization."
+    logging.info("Hashes of timestamps are equal")
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