Guard exported PUF top-tail capital gains

src/microplex_us/pipelines/us.py

@@ -285,6 +285,7 @@
     "taxable_interest_income",
     "tax_exempt_interest_income",
     "capital_gains",
+    "long_term_capital_gains_before_response",
     "long_term_capital_gains",
     "short_term_capital_gains",
     "non_sch_d_capital_gains",
@@ -303,6 +304,7 @@
 )
 PUF_SUPPORT_CLONE_TOP_TAIL_SCALE_VARIABLES: tuple[str, ...] = (
     "capital_gains",
+    "long_term_capital_gains_before_response",
     "long_term_capital_gains",
     "short_term_capital_gains",
     "non_sch_d_capital_gains",
@@ -5812,7 +5814,8 @@ def add(variable: str) -> bool:
             add(variable)
 
         if not add("capital_gains"):
-            add("long_term_capital_gains")
+            if not add("long_term_capital_gains_before_response"):
+                add("long_term_capital_gains")
             add("short_term_capital_gains")
         add("non_sch_d_capital_gains")
 
@@ -5872,10 +5875,19 @@ def _apply_puf_support_clone_top_tail_guard(
             return clone, summary
 
         integrated_set = set(integrated_variables)
+
+        def is_integrated_or_export_alias(variable: str) -> bool:
+            if variable in integrated_set:
+                return True
+            return (
+                variable == "long_term_capital_gains_before_response"
+                and "long_term_capital_gains" in integrated_set
+            )
+
         scale_variables = [
             variable
             for variable in self.config.puf_support_clone_top_tail_scale_variables
-            if variable in clone.columns and variable in integrated_set
+            if variable in clone.columns and is_integrated_or_export_alias(variable)
         ]
         if not scale_variables:
             summary["max_rough_agi_after"] = summary["max_rough_agi_before"]

tests/pipelines/test_us.py

@@ -4100,6 +4100,50 @@ def test_puf_support_clone_top_tail_guard_avoids_redundant_income_totals(self):
         pd.testing.assert_frame_equal(guarded, clone)
         assert summary["affected_rows"] == 0
 
+    def test_puf_support_clone_top_tail_guard_scales_exported_ltcg_alias(self):
+        pipeline = USMicroplexPipeline(
+            USMicroplexBuildConfig(
+                synthesis_backend="seed",
+                puf_support_clone_enabled=True,
+                puf_support_clone_top_tail_rough_agi_cap=78_999_999.0,
+            )
+        )
+        clone = pd.DataFrame(
+            {
+                "employment_income": [100_000.0],
+                "long_term_capital_gains": [70_000_000.0],
+                "long_term_capital_gains_before_response": [95_000_000.0],
+            }
+        )
+
+        guarded, summary = pipeline._apply_puf_support_clone_top_tail_guard(
+            clone,
+            integrated_variables=["long_term_capital_gains"],
+        )
+        rough_agi, rough_agi_variables = pipeline._puf_support_clone_top_tail_rough_agi(
+            guarded
+        )
+
+        assert rough_agi.iloc[0] == pytest.approx(78_999_999.0)
+        assert rough_agi_variables == [
+            "employment_income",
+            "long_term_capital_gains_before_response",
+        ]
+        assert guarded["employment_income"].iloc[0] == pytest.approx(100_000.0)
+        assert (
+            guarded["long_term_capital_gains_before_response"].iloc[0]
+            < clone["long_term_capital_gains_before_response"].iloc[0]
+        )
+        assert (
+            guarded["long_term_capital_gains"].iloc[0]
+            < clone["long_term_capital_gains"].iloc[0]
+        )
+        assert summary["affected_rows"] == 1
+        assert summary["scale_basis_variables"] == [
+            "long_term_capital_gains_before_response"
+        ]
+        assert "long_term_capital_gains_before_response" in summary["scaled_variables"]
+
     def test_puf_support_clone_top_tail_guard_can_be_disabled(self):
         pipeline = USMicroplexPipeline(
             USMicroplexBuildConfig(