Carry FRS employer sector (mjobsect) and SIC industry into the dataset

changelog.d/433.md

@@ -0,0 +1 @@
+- Populate `employment_sector` (public/private, from FRS `mjobsect`) and `sic_industry_division` (SIC 2007, from FRS `sic`) Person-level variables in the FRS dataset.

policyengine_uk_data/datasets/frs.py

@@ -749,6 +749,25 @@ def determine_education_level(fted_val, typeed2_val, age_val):
         person.empstati, 1, range(12), EMPLOYMENTS
     ).fillna("LONG_TERM_DISABLED")
 
+    # Add employer sector of the main job from FRS `mjobsect`
+    # (1 = private, 2 = public; missing/blank = not in paid work).
+    EMPLOYMENT_SECTORS = ["NOT_EMPLOYED", "PRIVATE", "PUBLIC"]
+    pe_person["employment_sector"] = categorical(
+        pd.to_numeric(person.mjobsect, errors="coerce"),
+        0,
+        [0, 1, 2],
+        EMPLOYMENT_SECTORS,
+    ).fillna("NOT_EMPLOYED")
+
+    # Standard Industrial Classification (2007) division of the main job from
+    # FRS `sic` (0 if unknown; 84 = public administration and defence).
+    pe_person["sic_industry_division"] = (
+        pd.to_numeric(person.sic, errors="coerce")
+        .fillna(0)
+        .clip(lower=0)
+        .astype(int)
+    )
+
     REGIONS = [
         "NORTH_EAST",
         "NORTH_WEST",