diff --git a/message_ix_models/tests/test_report.py b/message_ix_models/tests/test_report.py
index ba8fe16327..e00ed7e2a9 100644
--- a/message_ix_models/tests/test_report.py
+++ b/message_ix_models/tests/test_report.py
@@ -2,7 +2,7 @@
 
 import re
 from importlib.metadata import version
-from typing import List
+from typing import List, Optional
 
 import numpy as np
 import pandas as pd
@@ -315,10 +315,37 @@ def test_prepare_reporter(test_context):
     assert 14299 <= len(rep.graph) - N
 
 
+# Filters for comparison
+PE0 = r"Primary Energy\|(Coal|Gas|Hydro|Nuclear|Solar|Wind)"
+PE1 = r"Primary Energy\|(Coal|Gas|Solar|Wind)"
+E = (
+    r"Emissions\|CO2\|Energy\|Demand\|Transportation\|Road Rail and Domestic "
+    "Shipping"
+)
+
+IGNORE = [
+    # Other 'variable' codes are missing from `obs`
+    re.compile(f"variable='(?!{PE0}).*': no right data"),
+    # 'variable' codes with further parts are missing from `obs`
+    re.compile(f"variable='{PE0}.*': no right data"),
+    # For `pe1` (NB: not Hydro or Solar) units and most values differ
+    re.compile(f"variable='{PE1}.*': units mismatch .*EJ/yr.*'', nan"),
+    re.compile(r"variable='Primary Energy|Coal': 220 of 240 values with \|diff"),
+    re.compile(r"variable='Primary Energy|Gas': 234 of 240 values with \|diff"),
+    re.compile(r"variable='Primary Energy|Solar': 191 of 240 values with \|diff"),
+    re.compile(r"variable='Primary Energy|Wind': 179 of 240 values with \|diff"),
+    # For `e` units and most values differ
+    re.compile(f"variable='{E}': units mismatch: .*Mt CO2/yr.*Mt / a"),
+    re.compile(rf"variable='{E}': 20 missing right entries"),
+    re.compile(rf"variable='{E}': 220 of 240 values with \|diff"),
+]
+
+
 @to_simulate.minimum_version
 def test_compare(test_context):
     """Compare the output of genno-based and legacy reporting."""
-    key = "pe test"
+    key = "all::iamc"
+    # key = "pe test"
 
     # Obtain the output from reporting `key` on `snapshot_id`
     snapshot_id: int = 1
@@ -340,24 +367,8 @@ def test_compare(test_context):
         engine="pyarrow",
     )
 
-    # Filters for comparison
-    pe0 = r"Primary Energy\|(Coal|Gas|Hydro|Nuclear|Solar|Wind)"
-    pe1 = r"Primary Energy\|(Coal|Gas|Solar|Wind)"
-    ignore = [
-        # Other 'variable' codes are missing from `obs`
-        re.compile(f"variable='(?!{pe0}).*': no right data"),
-        # 'variable' codes with further parts are missing from `obs`
-        re.compile(f"variable='{pe0}.*': no right data"),
-        # For `pe1` (NB: not Hydro or Solar) units and most values differ
-        re.compile(f"variable='{pe1}.*': units mismatch .*EJ/yr.*'', nan"),
-        re.compile(r"variable='Primary Energy|Coal': 220 of 240 values with \|diff"),
-        re.compile(r"variable='Primary Energy|Gas': 234 of 240 values with \|diff"),
-        re.compile(r"variable='Primary Energy|Solar': 191 of 240 values with \|diff"),
-        re.compile(r"variable='Primary Energy|Wind': 179 of 240 values with \|diff"),
-    ]
-
     # Perform the comparison, ignoring some messages
-    if messages := compare_iamc(exp, obs, ignore=ignore):
+    if messages := compare_iamc(exp, obs, ignore=IGNORE):
         # Other messages that were not explicitly ignored → some error
         print("\n".join(messages))
         assert False
@@ -369,8 +380,8 @@ def compare_iamc(
     """Compare IAMC-structured data in `left` and `right`; return a list of messages."""
     result = []
 
-    def record(message: str) -> None:
-        if any(p.match(message) for p in ignore):
+    def record(message: str, condition: Optional[bool] = True) -> None:
+        if not condition or any(p.match(message) for p in ignore):
             return
         result.append(message)
 
@@ -388,16 +399,29 @@ def checks(df: pd.DataFrame):
             "value_rel = value_diff / value_left"
         )
 
+        na_left = tmp.isna()[["unit_left", "value_left"]]
+        if na_left.any(axis=None):
+            record(f"{prefix} {na_left.sum(axis=0).max()} missing left entries")
+            tmp = tmp[~na_left.any(axis=1)]
+        na_right = tmp.isna()[["unit_right", "value_right"]]
+        if na_right.any(axis=None):
+            record(f"{prefix} {na_right.sum(axis=0).max()} missing right entries")
+            tmp = tmp[~na_right.any(axis=1)]
+
         units_left = set(tmp.unit_left.unique())
         units_right = set(tmp.unit_right.unique())
-        if units_left != units_right:
-            record(f"{prefix} units mismatch: {units_left} != {units_right}")
+        record(
+            condition=units_left != units_right,
+            message=f"{prefix} units mismatch: {units_left} != {units_right}",
+        )
 
         N0 = len(df)
 
         mask1 = tmp.query("abs(value_diff) > @atol")
-        if len(mask1):
-            record(f"{prefix} {len(mask1)} of {N0} values with |diff| > {atol}")
+        record(
+            condition=len(mask1),
+            message=f"{prefix} {len(mask1)} of {N0} values with |diff| > {atol}",
+        )
 
     for (model, scenario), group_0 in left.merge(
         right,