Map Arch SOI alimony targets

src/microplex_us/policyengine/target_profiles.py

@@ -770,15 +770,6 @@ def _target_cell_key(cell: PolicyEngineUSTargetCell) -> PolicyEngineUSTargetCell
         "Loaded SOI state AGI sources provide return counts and AGI amounts, "
         "not filer-person counts by AGI band."
     ),
-    (
-        "alimony_expense",
-        "national",
-        None,
-        None,
-    ): (
-        "No accepted primary source mapping is encoded for this "
-        "survey/model-input expense variable."
-    ),
     (
         "child_support_expense",
         "national",

src/microplex_us/targets/arch.py

@@ -92,6 +92,7 @@
     "taxable_interest_amount": "taxable_interest_income",
     "tax_exempt_interest_amount": "tax_exempt_interest_income",
     "alimony_received_amount": "alimony_income",
+    "alimony_paid_amount": "alimony_expense",
     "personal_dividend_income_amount": "dividend_income",
     "ordinary_dividends_amount": "dividend_income",
     "qualified_dividends_amount": "qualified_dividend_income",
@@ -275,6 +276,16 @@
     ),
     "tanf_family_count": ("spm_unit_count", EntityType.SPM_UNIT, "tanf"),
     "tanf_recipient_count": ("person_count", EntityType.PERSON, "tanf"),
+    "alimony_received_returns": (
+        "tax_unit_count",
+        EntityType.TAX_UNIT,
+        "alimony_income",
+    ),
+    "alimony_paid_returns": (
+        "tax_unit_count",
+        EntityType.TAX_UNIT,
+        "alimony_expense",
+    ),
 }
 
 ARCH_FACT_CONCEPT_TO_TARGET = {
@@ -300,6 +311,16 @@
         "taxable_social_security_returns",
         "COUNT",
     ),
+    "irs_soi.returns_with_alimony_received": (
+        "alimony_received_returns",
+        "COUNT",
+    ),
+    "irs_soi.alimony_received": ("alimony_received_amount", "AMOUNT"),
+    "irs_soi.returns_with_alimony_paid": (
+        "alimony_paid_returns",
+        "COUNT",
+    ),
+    "irs_soi.alimony_paid": ("alimony_paid_amount", "AMOUNT"),
     "irs_soi.returns_with_income_tax_after_credits": (
         "income_tax_liability_returns",
         "COUNT",
@@ -1067,7 +1088,6 @@
 
 ARCH_DEPRIORITIZED_SURVEY_OR_MODEL_GAP_VARIABLES = frozenset(
     {
-        "alimony_expense",
         "child_support_expense",
         "child_support_received",
         "health_insurance_premiums_without_medicare_part_b",

tests/policyengine/test_target_profiles.py

@@ -370,10 +370,10 @@ def test_source_backed_profile_excludes_only_documented_non_source_cells() -> No
     }
 
     assert len(broad_cells) == 189
-    assert len(exclusion_reasons) == 23
+    assert len(exclusion_reasons) == 22
     assert all(reason for reason in exclusion_reasons.values())
     assert set(exclusion_reasons) <= broad_cells
-    assert len(source_backed_cells) == 166
+    assert len(source_backed_cells) == 167
     assert source_backed_cells == broad_cells - set(exclusion_reasons)
     assert (
         "childcare_expenses",
@@ -417,6 +417,18 @@ def test_source_backed_profile_excludes_only_documented_non_source_cells() -> No
         None,
         None,
     ) in source_backed_cells
+    assert (
+        "alimony_expense",
+        "national",
+        None,
+        None,
+    ) in source_backed_cells
+    assert (
+        "alimony_income",
+        "national",
+        None,
+        None,
+    ) in source_backed_cells
     assert (
         "medicare_part_b_premiums",
         "national",

tests/targets/test_arch.py

@@ -907,6 +907,19 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
             (
                 9,
                 2,
+                "alimony_paid_amount",
+                2023,
+                25.0,
+                "AMOUNT",
+                None,
+                "IRS_SOI",
+                "SOI",
+                None,
+                None,
+            ),
+            (
+                10,
+                2,
                 "schedule_c_income_amount",
                 2023,
                 30.0,
@@ -918,7 +931,7 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
                 None,
             ),
             (
-                10,
+                11,
                 1,
                 "medicaid_total_enrollment",
                 2024,
@@ -931,7 +944,7 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
                 None,
             ),
             (
-                11,
+                12,
                 2,
                 "wages_salaries_amount",
                 2023,
@@ -944,7 +957,7 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
                 None,
             ),
             (
-                12,
+                13,
                 2,
                 "wages_salaries_returns",
                 2023,
@@ -957,7 +970,7 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
                 None,
             ),
             (
-                13,
+                14,
                 2,
                 "schedule_c_income_returns",
                 2023,
@@ -985,6 +998,11 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
                         "geo_level": "national",
                         "domain_variable": None,
                     },
+                    {
+                        "variable": "alimony_expense",
+                        "geo_level": "national",
+                        "domain_variable": None,
+                    },
                     {
                         "variable": "self_employment_income",
                         "geo_level": "national",
@@ -1027,18 +1045,20 @@ def test_arch_provider_matches_current_profile_aliases(tmp_path):
         11,
         12,
         13,
+        14,
     }
     variables_by_id = {
         target.metadata["target_id"]: target.metadata["variable"]
         for target in target_set.targets
     }
     assert variables_by_id == {
         8: "alimony_income",
-        9: "self_employment_income",
-        10: "person_count",
-        11: "employment_income",
+        9: "alimony_expense",
+        10: "self_employment_income",
+        11: "person_count",
         12: "employment_income",
-        13: "self_employment_income",
+        13: "employment_income",
+        14: "self_employment_income",
     }
 
 

tests/targets/test_arch_facts.py

@@ -1712,6 +1712,82 @@ def test_arch_consumer_fact_jsonl_provider_maps_state_broad_soi_concepts(
     )
 
 
+def test_arch_consumer_fact_jsonl_provider_maps_soi_alimony_concepts(
+    tmp_path: Path,
+) -> None:
+    consumer_jsonl = tmp_path / "consumer_facts.jsonl"
+    rows = [
+        _consumer_fact(
+            "soi-alimony-received-returns",
+            concept="irs_soi.returns_with_alimony_received",
+            domain="all_individual_income_tax_returns",
+            source_name="irs_soi",
+            source_table="Publication 1304 Table 1.4",
+            period={"type": "tax_year", "value": 2023},
+            value=183_582,
+        ),
+        _consumer_fact(
+            "soi-alimony-received-amount",
+            concept="irs_soi.alimony_received",
+            domain="all_individual_income_tax_returns",
+            source_name="irs_soi",
+            source_table="Publication 1304 Table 1.4",
+            period={"type": "tax_year", "value": 2023},
+            value=6_686_429_000,
+            unit="usd",
+        ),
+        _consumer_fact(
+            "soi-alimony-paid-returns",
+            concept="irs_soi.returns_with_alimony_paid",
+            domain="all_individual_income_tax_returns",
+            source_name="irs_soi",
+            source_table="Publication 1304 Table 1.4",
+            period={"type": "tax_year", "value": 2023},
+            value=278_541,
+        ),
+        _consumer_fact(
+            "soi-alimony-paid-amount",
+            concept="irs_soi.alimony_paid",
+            domain="all_individual_income_tax_returns",
+            source_name="irs_soi",
+            source_table="Publication 1304 Table 1.4",
+            period={"type": "tax_year", "value": 2023},
+            value=7_497_135_000,
+            unit="usd",
+        ),
+    ]
+    consumer_jsonl.write_text(
+        "\n".join(json.dumps(row, sort_keys=True) for row in rows) + "\n"
+    )
+
+    target_set = ArchConsumerFactJSONLTargetProvider(consumer_jsonl).load_target_set(
+        TargetQuery(period=2023)
+    )
+    targets_by_arch_variable = {
+        target.metadata["arch_variable"]: target for target in target_set.targets
+    }
+
+    received_amount = targets_by_arch_variable["alimony_received_amount"]
+    assert received_amount.metadata["variable"] == "alimony_income"
+    assert received_amount.measure == "alimony_income"
+
+    received_returns = targets_by_arch_variable["alimony_received_returns"]
+    assert received_returns.metadata["variable"] == "tax_unit_count"
+    assert received_returns.aggregation.value == "count"
+    assert ("alimony_income", ">", "0") in _target_filter_tuples(
+        received_returns
+    )
+
+    paid_amount = targets_by_arch_variable["alimony_paid_amount"]
+    assert paid_amount.metadata["variable"] == "alimony_expense"
+    assert paid_amount.measure == "alimony_expense"
+
+    paid_returns = targets_by_arch_variable["alimony_paid_returns"]
+    assert paid_returns.metadata["variable"] == "tax_unit_count"
+    assert paid_returns.aggregation.value == "count"
+    assert ("alimony_expense", ">", "0") in _target_filter_tuples(paid_returns)
+
+
 def test_arch_consumer_fact_jsonl_provider_maps_eitc_by_agi_and_children(
     tmp_path: Path,
 ) -> None: