Add fuel duty revenue projections and increase imputation granularity (…

…#831) * Add docker step * Versioning * Remove push action from PRs * Add requirements.txt * Update carbon tax intensities for 2024 data * Versioning * Temporarily suspend fuel duty parameters * Add fuel duty revenues * Versioning * Fix tests * Reduce consumer incidence
PolicyEngine · Mar 5, 2024 · e29a512 · e29a512
1 parent 4407653
commit e29a512
Show file tree

Hide file tree

Showing 8 changed files with 61 additions and 13 deletions.
diff --git a/changelog_entry.yaml b/changelog_entry.yaml
@@ -0,0 +1,4 @@
+- bump: minor
+  changes:
+    added:
+    - Fuel duty revenue projections
diff --git a/policyengine_uk/data/datasets/frs/enhanced_frs.py b/policyengine_uk/data/datasets/frs/enhanced_frs.py
@@ -86,7 +86,7 @@ def generate(self):
                     target_values,
                     X_input,
                     frs_household_weight,
-                    max_iterations=5,
+                    max_iterations=8,
                 )
             else:
                 quantiles = None

diff --git a/policyengine_uk/data/datasets/frs/imputations/consumption.py b/policyengine_uk/data/datasets/frs/imputations/consumption.py
@@ -104,6 +104,33 @@ def generate_lcfs_table(
     ].dropna()
 
 
+def uprate_lcfs_table(
+    household: pd.DataFrame, time_period: str
+) -> pd.DataFrame:
+    from policyengine_uk.system import system
+
+    fuel_duty_revenue = (
+        system.parameters.calibration.programs.fuel_duty.revenue
+    )
+    fuel_duty_rate = system.parameters.gov.hmrc.fuel_duty.petrol_and_diesel
+    start_period = 2020
+    start_index = fuel_duty_revenue(start_period) / fuel_duty_rate(
+        start_period
+    )
+    end_index = fuel_duty_revenue(time_period) / fuel_duty_rate(time_period)
+    fuel_uprating = end_index / start_index
+    household["petrol_spending"] *= fuel_uprating
+    household["diesel_spending"] *= fuel_uprating
+
+    cpi = system.parameters.calibration.uprating.CPI
+    cpi_uprating = cpi(time_period) / cpi(start_period)
+
+    for variable in IMPUTATIONS:
+        if variable not in ["petrol_spending", "diesel_spending"]:
+            household[variable] *= cpi_uprating
+    return household
+
+
 def save_imputation_models():
     consumption = Imputation()
     lcfs_household = pd.read_csv(
@@ -115,6 +142,7 @@ def save_imputation_models():
         LCFS_TAB_FOLDER / "lcfs_2020_dvper_ukanon202021.tab", delimiter="\t"
     )
     household = generate_lcfs_table(lcfs_person, lcfs_household)
+    household = uprate_lcfs_table(household, "2023")
     consumption.train(
         household[PREDICTOR_VARIABLES],
         household[IMPUTATIONS],

diff --git a/policyengine_uk/data/storage/imputations/consumption_targets.yaml b/policyengine_uk/data/storage/imputations/consumption_targets.yaml
@@ -1,15 +1,15 @@
 alcohol_and_tobacco_consumption: 20649078205.153564
 clothing_and_footwear_consumption: 20963698388.085712
 communication_consumption: 16271364314.480564
-diesel_spending: 6376596007.607264
+diesel_spending: 8267208905.41007
 domestic_energy_consumption: 34019184412.316296
 education_consumption: 12218834004.851433
 food_and_non_alcoholic_beverages_consumption: 101271123549.67178
 health_consumption: 9779703005.577099
 household_furnishings_consumption: 50520352854.88441
 housing_water_and_electricity_consumption: 124038611200.9107
 miscellaneous_consumption: 54415069695.58299
-petrol_spending: 10060152807.35514
+petrol_spending: 13042912673.083202
 recreation_consumption: 65969989192.65327
 restaurants_and_hotels_consumption: 26464397527.409103
 transport_consumption: 89217063076.27383
diff --git a/policyengine_uk/parameters/calibration/programs/fuel_duty/revenue.yaml b/policyengine_uk/parameters/calibration/programs/fuel_duty/revenue.yaml
@@ -0,0 +1,16 @@
+description: Fuel duty revenues.
+values:
+  2020-01-01: 20_934_000_000
+  2021-01-01: 25_943_000_000
+  2022-01-01: 24_799_033_375
+  2023-01-01: 24_799_033_375
+  2024-01-01: 24_348_775_447
+  2025-01-01: 26_621_382_708
+  2026-01-01: 26_262_427_712
+  2027-01-01: 26_034_425_644
+metadata:
+  unit: currency-GBP
+  label: Fuel duty revenues
+  reference:
+    - title: OBR forecast
+      href: https://obr.uk/forecasts-in-depth/tax-by-tax-spend-by-spend/fuel-duties
diff --git a/policyengine_uk/tests/policy/baseline/gov/hmrc/fuel_duty/fuel_duty.yaml b/policyengine_uk/tests/policy/baseline/gov/hmrc/fuel_duty/fuel_duty.yaml
@@ -1,13 +1,13 @@
 - name: Petrol only in 2022.
   period: 2022
-  absolute_error_margin: 0.1
+  absolute_error_margin: 1
   input:
     petrol_spending: 1_200
     diesel_spending: 0
   output:
-    petrol_litres: 1200 / 1.491
+    petrol_litres: 1200 / 1.4910
     diesel_litres: 0
-    fuel_duty: 804.83 / 0.508 * 0.5795
+    fuel_duty: 1322
 - name: No fuel spending, no fuel duty.
   period: 2023
   absolute_error_margin: 0.1
@@ -26,8 +26,8 @@
     diesel_spending: 350
   output:
     petrol_litres: 800 / 1.6703
-    diesel_litres: 350 / 1.7897
-    fuel_duty: (478.96 + 195.56) / 0.508 * 0.5295
+    diesel_litres: 350 / 1.4559
+    fuel_duty: (478.96 + 240.40) / 0.33 * 0.5295
 - name: Petrol and diesel in 2021.
   period: 2021
   absolute_error_margin: 0.1
@@ -37,5 +37,5 @@
   output:
     petrol_litres: 800 / 1.0669
     diesel_litres: 350 / 1.1186
-    fuel_duty: (749.84 + 312.89) / 0.508 * 0.5795
+    fuel_duty: (749.84 + 312.89) / 0.33 * 0.5795
 
diff --git a/policyengine_uk/tests/policy/reforms/parametric/fuel_duty_cut.yaml b/policyengine_uk/tests/policy/reforms/parametric/fuel_duty_cut.yaml
@@ -4,14 +4,14 @@
   input:
     petrol_spending: 100
   output:
-    fuel_duty: 54.32 / 0.51
+    fuel_duty: 54.32 / 0.33
 
 - name: Reduction from 5p cut
   period: 2021
   absolute_error_margin: 1
   input:
     gov.hmrc.fuel_duty.petrol_and_diesel: 0.5295
     petrol_spending: 100
-    baseline_fuel_duty: 54.32 / 0.51
+    baseline_fuel_duty: 54.32 / 0.33
   output:
-    change_in_fuel_duty: -5 / 0.51
+    change_in_fuel_duty: -5 / 0.33
diff --git a/policyengine_uk/variables/gov/hmrc/fuel_duty/fuel_duty.py b/policyengine_uk/variables/gov/hmrc/fuel_duty/fuel_duty.py
@@ -1,7 +1,7 @@
 from policyengine_uk.model_api import *
 
 
-STATUTORY_CONSUMER_INCIDENCE = 0.508
+STATUTORY_CONSUMER_INCIDENCE = 0.33
 ECONOMIC_CONSUMER_INCIDENCE = 1