Fix invalid value error in weekly_hours_worked file by using np.divide

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: patch
+  changes:
+    fixed:
+    - Invalid value encountered when dividing income_effect by original_earnings and dividing substitution_effect by original_earnings in weekly hours worked calculation

policyengine_us/tests/policy/baseline/household/income/person/weekly_hours_worked.yaml

@@ -0,0 +1,59 @@
+- name: Weekly hours worked with labor supply response
+  period: 2022
+  input:
+    weekly_hours_worked_before_lsr: 40
+    labor_supply_behavioral_response: 1
+    income_elasticity_lsr: 0.1
+    substitution_elasticity_lsr: 0.2
+    employment_income_before_lsr: 100_000
+    self_employment_income_before_lsr: 50_000
+  output:
+    # Calculation steps:
+    # Total earnings: 100_000 + 50_000 = 150_000
+    # weekly_hours_worked_behavioural_response_income_elasticity = 40 * (0.1 / 150_000)
+    # = 40 * 6.6666667e-07
+    # = 2.6666667e-05
+    weekly_hours_worked_behavioural_response_income_elasticity: 2.6666667e-05
+
+    # weekly_hours_worked_behavioural_response_substitution_elasticity = 40 * (0.2 / 150_000)
+    # = 40 * 1.3333333e-06
+    # = 5.3333333e-05
+    weekly_hours_worked_behavioural_response_substitution_elasticity: 5.3333333e-05
+
+    # weekly_hours_worked_behavioural_response = 2.6666667e-05 + 5.3333333e-05
+    # = 8.0000000e-05
+    weekly_hours_worked_behavioural_response: 8.0000000e-05
+
+- name: Weekly hours worked with zero earnings
+  period: 2022
+  input:
+    weekly_hours_worked_before_lsr: 40
+    labor_supply_behavioral_response: 1
+    income_elasticity_lsr: 0.1
+    substitution_elasticity_lsr: 0.2
+    employment_income_before_lsr: 0
+    self_employment_income_before_lsr: 0
+  output:
+    # Calculation steps:
+    # Total earnings: 0 + 0 = 0
+    # weekly_hours_worked_behavioural_response_income_elasticity = 0 (division by zero avoided in Python code)
+    weekly_hours_worked_behavioural_response_income_elasticity: 0
+
+    # weekly_hours_worked_behavioural_response_substitution_elasticity = 0 (division by zero avoided in Python code)
+    weekly_hours_worked_behavioural_response_substitution_elasticity: 0
+
+    # weekly_hours_worked_beha
+
+- name: Weekly hours worked with zero labor supply response
+  period: 2022
+  input:
+    weekly_hours_worked_before_lsr: 40
+    labor_supply_behavioral_response: 0  # Trigger the condition for np.zeros_like(original)
+    income_elasticity_lsr: 0.1
+    substitution_elasticity_lsr: 0.2
+    employment_income_before_lsr: 100_000
+    self_employment_income_before_lsr: 50_000
+  output:
+    weekly_hours_worked_behavioural_response_income_elasticity: 0
+    weekly_hours_worked_behavioural_response_substitution_elasticity: 0
+    weekly_hours_worked_behavioural_response: 0

policyengine_us/variables/household/income/person/weekly_hours_worked.py

@@ -32,16 +32,24 @@ class weekly_hours_worked_behavioural_response_income_elasticity(Variable):
     def formula(person, period, parameters):
         original = person("weekly_hours_worked_before_lsr", period)
         lsr = person("labor_supply_behavioral_response", period)
+
         if (lsr != 0).any():
             income_effect = person("income_elasticity_lsr", period)
         else:
-            income_effect = 0
+            income_effect = np.zeros_like(original)
+
         original_emp = person("employment_income_before_lsr", period)
         original_self_emp = person("self_employment_income_before_lsr", period)
         original_earnings = original_emp + original_self_emp
-        lsr_relative_change = np.where(
-            original_earnings == 0, 0, income_effect / original_earnings
+
+        lsr_relative_change = np.divide(
+            income_effect,
+            original_earnings,
+            # Assign no LSR change to people with no original earnings to avoid dividing by zero.
+            out=np.zeros_like(income_effect, dtype=np.float32),
+            where=original_earnings != 0,
         )
+
         return original * lsr_relative_change
 
 
@@ -60,13 +68,19 @@ def formula(person, period, parameters):
         if (lsr != 0).any():
             substitution_effect = person("substitution_elasticity_lsr", period)
         else:
-            substitution_effect = 0
+            substitution_effect = np.zeros_like(original)
         original_emp = person("employment_income_before_lsr", period)
         original_self_emp = person("self_employment_income_before_lsr", period)
         original_earnings = original_emp + original_self_emp
-        lsr_relative_change = np.where(
-            original_earnings == 0, 0, substitution_effect / original_earnings
+
+        lsr_relative_change = np.divide(
+            substitution_effect,
+            original_earnings,
+            # Assign no LSR change to people with no original earnings to avoid dividing by zero.
+            out=np.zeros_like(substitution_effect, dtype=np.float32),
+            where=original_earnings != 0,
         )
+
         return original * lsr_relative_change