Reintroduce age-specific labor supply response multipliers

changelog.d/lsr-age-heterogeneity.changed.md

@@ -0,0 +1 @@
+Reintroduce age-specific labor supply response multipliers without changing the legacy scalar income elasticity path, and fix the labor-supply-response zero guard so nonzero primary or secondary substitution elasticities are not skipped.

policyengine_us/parameters/gov/simulation/labor_supply_responses/elasticities/income_age_multiplier_over_threshold.yaml

@@ -0,0 +1,6 @@
+description: Multiplier applied to income elasticity for people at or above the age threshold.
+values:
+  2020-01-01: 2.0
+metadata:
+  unit: /1
+  label: income elasticity multiplier for people at or above the age threshold

policyengine_us/parameters/gov/simulation/labor_supply_responses/elasticities/income_age_threshold.yaml

@@ -0,0 +1,6 @@
+description: Age at which the income elasticity multiplier begins to apply.
+values:
+  2020-01-01: 65
+metadata:
+  unit: year
+  label: age threshold for income elasticity multiplier

policyengine_us/parameters/gov/simulation/labor_supply_responses/elasticities/substitution.yaml

@@ -5,6 +5,20 @@ all:
   metadata:
     unit: /1
     label: substitution elasticity of labor supply
+age_threshold:
+  description: Age at which the substitution elasticity multiplier begins to apply.
+  values:
+    2020-01-01: 65
+  metadata:
+    unit: year
+    label: age threshold for substitution elasticity multiplier
+age_multiplier_over_threshold:
+  description: Multiplier applied to substitution elasticities for people at or above the age threshold.
+  values:
+    2020-01-01: 2.0
+  metadata:
+    unit: /1
+    label: substitution elasticity multiplier for people at or above the age threshold
 by_position_and_decile:
   metadata:
     label: by position and decile

policyengine_us/tests/core/test_labor_supply_behavioral_response_guard.py

@@ -0,0 +1,100 @@
+from types import SimpleNamespace
+from unittest.mock import Mock, patch
+
+from policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response import (
+    labor_supply_behavioral_response,
+)
+
+
+def _parameters(*, income=0, substitution_all=0, substitution_secondary=0, primary_1=0):
+    return lambda period: SimpleNamespace(
+        gov=SimpleNamespace(
+            simulation=SimpleNamespace(
+                labor_supply_responses=SimpleNamespace(
+                    elasticities=SimpleNamespace(
+                        income=income,
+                        substitution=SimpleNamespace(
+                            all=substitution_all,
+                            by_position_and_decile=SimpleNamespace(
+                                secondary=substitution_secondary,
+                                primary=SimpleNamespace(
+                                    **{
+                                        str(decile): primary_1 if decile == 1 else 0
+                                        for decile in range(1, 11)
+                                    }
+                                ),
+                            ),
+                        ),
+                    )
+                )
+            )
+        )
+    )
+
+
+def _person():
+    person = Mock()
+    person.simulation = Mock()
+    person.simulation.baseline = Mock()
+    person.simulation._lsr_calculating = False
+    return person
+
+
+def test_guard_returns_zero_only_when_all_elasticities_are_zero():
+    result = labor_supply_behavioral_response.formula(_person(), 2026, _parameters())
+
+    assert result == 0
+
+
+@patch(
+    "policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response.calculate_substitution_lsr_effect",
+    return_value=500,
+)
+@patch(
+    "policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response.calculate_income_lsr_effect",
+    return_value=0,
+)
+@patch(
+    "policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response.get_behavioral_response_measurements",
+    return_value={"baseline_net_income": 1},
+)
+def test_guard_does_not_short_circuit_primary_decile_responses(
+    mock_measurements,
+    mock_income,
+    mock_substitution,
+):
+    result = labor_supply_behavioral_response.formula(
+        _person(), 2026, _parameters(primary_1=0.2)
+    )
+
+    assert result == 500
+    mock_measurements.assert_called_once()
+    mock_income.assert_called_once()
+    mock_substitution.assert_called_once()
+
+
+@patch(
+    "policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response.calculate_substitution_lsr_effect",
+    return_value=250,
+)
+@patch(
+    "policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response.calculate_income_lsr_effect",
+    return_value=0,
+)
+@patch(
+    "policyengine_us.variables.gov.simulation.labor_supply_response.labor_supply_behavioral_response.get_behavioral_response_measurements",
+    return_value={"baseline_net_income": 1},
+)
+def test_guard_does_not_short_circuit_secondary_responses(
+    mock_measurements,
+    mock_income,
+    mock_substitution,
+):
+    result = labor_supply_behavioral_response.formula(
+        _person(), 2026, _parameters(substitution_secondary=0.15)
+    )
+
+    assert result == 250
+    mock_measurements.assert_called_once()
+    mock_income.assert_called_once()
+    mock_substitution.assert_called_once()

policyengine_us/tests/policy/baseline/gov/simulation/labor_supply_response/income_elasticity.yaml

@@ -5,9 +5,22 @@
   output:
     income_elasticity: 0
 
-- name: Custom income elasticity value
+- name: Custom income elasticity value under threshold
   period: 2023
   input:
+    age: 50
     gov.simulation.labor_supply_responses.elasticities.income: -0.2
+    gov.simulation.labor_supply_responses.elasticities.income_age_threshold: 65
+    gov.simulation.labor_supply_responses.elasticities.income_age_multiplier_over_threshold: 2.0
   output:
     income_elasticity: -0.2
+
+- name: Income elasticity for people at or above threshold applies multiplier
+  period: 2023
+  input:
+    age: 70
+    gov.simulation.labor_supply_responses.elasticities.income: -0.2
+    gov.simulation.labor_supply_responses.elasticities.income_age_threshold: 65
+    gov.simulation.labor_supply_responses.elasticities.income_age_multiplier_over_threshold: 2.0
+  output:
+    income_elasticity: -0.4

policyengine_us/tests/policy/baseline/gov/simulation/labor_supply_response/integration.yaml

@@ -0,0 +1,42 @@
+- name: Older secondary earner gets the age multiplier on the secondary elasticity
+  period: 2023
+  input:
+    people:
+      older_secondary:
+        age: 67
+        employment_income_before_lsr: 40_000
+        self_employment_income_before_lsr: 0
+      younger_primary:
+        age: 55
+        employment_income_before_lsr: 50_000
+        self_employment_income_before_lsr: 0
+    tax_units:
+      tax_unit:
+        members: [older_secondary, younger_primary]
+    spm_units:
+      spm_unit:
+        members: [older_secondary, younger_primary]
+    households:
+      household:
+        members: [older_secondary, younger_primary]
+    families:
+      family:
+        members: [older_secondary, younger_primary]
+    marital_units:
+      marital_unit:
+        members: [older_secondary, younger_primary]
+    gov.simulation.labor_supply_responses.elasticities.income: -0.04
+    gov.simulation.labor_supply_responses.elasticities.income_age_threshold: 65
+    gov.simulation.labor_supply_responses.elasticities.income_age_multiplier_over_threshold: 2.0
+    gov.simulation.labor_supply_responses.elasticities.substitution.all: 0
+    gov.simulation.labor_supply_responses.elasticities.substitution.age_threshold: 65
+    gov.simulation.labor_supply_responses.elasticities.substitution.age_multiplier_over_threshold: 2.0
+    gov.simulation.labor_supply_responses.elasticities.substitution.by_position_and_decile.primary.5: 0.20
+    gov.simulation.labor_supply_responses.elasticities.substitution.by_position_and_decile.secondary: 0.10
+  output:
+    income_elasticity:
+      - -0.08
+      - -0.04
+    substitution_elasticity:
+      - 0.20
+      - 0.20

policyengine_us/tests/policy/baseline/gov/simulation/labor_supply_response/substitution_elasticity.yaml

@@ -27,6 +27,19 @@
   output:
     substitution_elasticity: 0  # TODO: Debug why single person isn't getting primary earner elasticity
 
+- name: Primary earner at or above threshold gets substitution multiplier
+  period: 2023
+  input:
+    age: 70
+    employment_income_before_lsr: 50_000
+    self_employment_income_before_lsr: 0
+    gov.simulation.labor_supply_responses.elasticities.substitution.all: 0
+    gov.simulation.labor_supply_responses.elasticities.substitution.age_threshold: 65
+    gov.simulation.labor_supply_responses.elasticities.substitution.age_multiplier_over_threshold: 2.0
+    gov.simulation.labor_supply_responses.elasticities.substitution.by_position_and_decile.primary.5: 0.15
+  output:
+    substitution_elasticity: 0.30
+
 - name: Negative total earnings should have zero elasticity
   period: 2023
   input:

policyengine_us/variables/gov/simulation/labor_supply_response/income_elasticity.py

@@ -7,4 +7,21 @@ class income_elasticity(Variable):
     label = "income elasticity of labor supply"
     unit = "/1"
     definition_period = YEAR
-    adds = ["gov.simulation.labor_supply_responses.elasticities.income"]
+    reference = [
+        "https://www.cbo.gov/publication/43675",
+        "https://www.cbo.gov/publication/43676",
+        "https://academic.oup.com/restud/article-abstract/72/2/395/1558553",
+    ]
+
+    def formula(person, period, parameters):
+        elasticities = parameters(
+            period
+        ).gov.simulation.labor_supply_responses.elasticities
+        base_elasticity = elasticities.income
+        age = person("age", period.this_year)
+        age_multiplier = where(
+            age >= elasticities.income_age_threshold,
+            elasticities.income_age_multiplier_over_threshold,
+            1.0,
+        )
+        return base_elasticity * age_multiplier

policyengine_us/variables/gov/simulation/labor_supply_response/labor_supply_behavioral_response.py

@@ -18,7 +18,22 @@ def formula(person, period, parameters):
         simulation = person.simulation
         if simulation.baseline is None:
             return 0  # No reform, no impact
-        if p.elasticities.income == 0 and p.elasticities.substitution.all == 0:
+
+        substitution_elasticities = p.elasticities.substitution
+        by_position = getattr(substitution_elasticities, "by_position_and_decile", None)
+        primary_elasticities = (
+            getattr(by_position, "primary", None) if by_position else None
+        )
+        no_income_response = p.elasticities.income == 0
+        no_substitution_response = (
+            substitution_elasticities.all == 0
+            and getattr(by_position, "secondary", 0) == 0
+            and all(
+                getattr(primary_elasticities, str(decile), 0) == 0
+                for decile in range(1, 11)
+            )
+        )
+        if no_income_response and no_substitution_response:
             return 0
 
         # Guard against re-entry (prevents recursion when branches calculate variables)

policyengine_us/variables/gov/simulation/labor_supply_response/substitution_elasticity.py

@@ -7,6 +7,11 @@ class substitution_elasticity(Variable):
     label = "substitution elasticity of labor supply"
     unit = "/1"
     definition_period = YEAR
+    reference = [
+        "https://www.cbo.gov/publication/43675",
+        "https://www.cbo.gov/publication/43676",
+        "https://academic.oup.com/restud/article-abstract/72/2/395/1558553",
+    ]
 
     def formula(person, period, parameters):
         p = parameters(
@@ -46,7 +51,7 @@ def formula(person, period, parameters):
         max_earnings_in_unit = tax_unit.max(earnings)
         is_primary_earner = earnings == max_earnings_in_unit
 
-        elasticities = np.zeros_like(earnings)
+        elasticities = np.zeros_like(earnings, dtype=float)
 
         # Handle zero earnings first
         zero_earnings = earnings == 0
@@ -57,18 +62,32 @@ def formula(person, period, parameters):
 
         if np.any(non_zero_earnings):
             # First assign primary earner elasticities by decile
-            decile_elasticities = [
-                p.by_position_and_decile.primary._children[str(i + 1)]
-                for i in range(10)
-            ]
             for i in range(10):
                 mask = (
                     non_zero_earnings & (earnings_decile == i + 1) & is_primary_earner
                 )
-                elasticities[mask] = decile_elasticities[i]
+                if np.any(mask):
+                    decile_param = getattr(p.by_position_and_decile.primary, str(i + 1))
+                    param_value = (
+                        decile_param(period) if callable(decile_param) else decile_param
+                    )
+                    elasticities[mask] = param_value
 
             # Then assign secondary earner elasticity where applicable
             secondary_mask = non_zero_earnings & ~is_primary_earner
-            elasticities[secondary_mask] = p.by_position_and_decile.secondary
+            secondary_param = p.by_position_and_decile.secondary
+            secondary_value = (
+                secondary_param(period)
+                if callable(secondary_param)
+                else secondary_param
+            )
+            elasticities[secondary_mask] = secondary_value
 
-        return elasticities
+        age = person("age", period.this_year)
+        age_multiplier = where(
+            age >= p.age_threshold,
+            p.age_multiplier_over_threshold,
+            1.0,
+        )
+
+        return elasticities * age_multiplier