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Add water bills projections (#1224)
* Add validate function to dataset * Add water bills uprating * Add docs page
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‎changelog_entry.yaml‎

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- bump: minor
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changes:
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added:
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- Water bills projections.

‎docs/book/_toc.yml‎

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- caption: Economic assumptions
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chapters:
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- file: assumptions/growthfactors
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- file: assumptions/water-bills
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- caption: Validation
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chapters:
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- file: validation/hbai

‎docs/book/assumptions/water-bills.md‎

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# Water bills projection and uprating
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This documentation describes the water bills projection and uprating methodology used in PolicyEngine UK.
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## Overview
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We implement water bills projections through a combination of historical data analysis and regulatory projection data. The system uses:
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1. **Historical data** (2021-2025) from Ofwat average bills
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2. **Regulatory projection data** from Ofwat company-specific increases (2025-2030)
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3. **Economic uprating** using Consumer Price Index (CPIH) growth rates
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## Implementation
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### Data sources
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#### Historical data
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The projection uses historical real water bills data from Ofwat:
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- **2021**: £486 (real terms)
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- **2022**: £470 (real terms)
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- **2023**: £486 (real terms)
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- **2024**: £492 (real terms)
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- **2025**: £503 (real terms)
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**Data source**: [Ofwat average bills data for England and Wales](https://www.ofwat.gov.uk/average-bills-press-statement-2024-25/)
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#### Regulatory projections
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We source company-specific water bill increases from the Consumer Council for Water (CCW) based on Ofwat's price review data for 2025-2030. The data includes projected bills for 16 water companies covering both water and sewerage services.
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**Data source**: [CCW Water Company Bill Increases 2025-30](https://www.ccw.org.uk/our-work/price-review/how-much-will-my-water-and-sewerage-bills-increase-by-2030/breakdown-of-water-companies-bill-increases-2025-30/)
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### Projection methodology
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#### Historical period (2021-2025)
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1. We convert real bills to nominal terms using CPIH values
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2. We calculate year-on-year nominal growth rates
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3. We normalize to 2021 baseline (index = 100)
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#### Future period (2025-2030)
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1. We calculate average of company-specific projected increases
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2. We apply Consumer Price Index (CPIH) uprating to account for inflation
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3. We compound inflation adjustments year-over-year
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The methodology ensures that:
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- We preserve real increases from regulatory decisions
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- We apply additional inflation adjustments using CPIH forecasts
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- Future projections account for both policy changes and economic conditions
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### Code structure
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#### Core implementation
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- **Location**: `policyengine_uk/utils/water/forecast_water_bills.py`
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- **Function**: `project_water_bills()`
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- **Data**: `policyengine_uk/utils/water/ofwat_increases.csv`
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#### Parameters integration
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We store water bills year-on-year growth rates in:
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- **Location**: `policyengine_uk/parameters/gov/economic_assumptions/yoy_growth.yaml`
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- **Parameter**: `ofwat.water_bills`
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### Growth rates
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The model uses these resulting year-on-year growth rates:
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| Year | Growth rate |
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|------|-------------|
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| 2022 | 5.2% |
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| 2023 | 9.2% |
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| 2024 | 4.4% |
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| 2025 | 6.1% |
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| 2026 | 6.1% |
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| 2027 | 5.1% |
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| 2028 | 3.8% |
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| 2029 | 4.3% |

‎policyengine_uk/data/dataset_schema.py‎

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household=self.household.copy(),
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)
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def validate(self):
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# Check for NaNs in the tables
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for df in self.tables:
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for col in df.columns:
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if df[col].isna().any():
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raise ValueError(f"Column '{col}' contains NaN values.")
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@staticmethod
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def from_simulation(
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simulation: "Microsimulation", fiscal_year: int = 2025

‎policyengine_uk/parameters/gov/economic_assumptions/yoy_growth.yaml‎

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reference:
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- title: ONS Population Projections
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href: https://www.ons.gov.uk/
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ofwat:
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water_bills:
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description: Water and sewerage bills year-on-year growth.
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values:
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2022-01-01: 0.052
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2023-01-01: 0.092
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2024-01-01: 0.044
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2025-01-01: 0.061
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2026-01-01: 0.061
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2027-01-01: 0.051
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2028-01-01: 0.038
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2029-01-01: 0.043
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metadata:
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unit: /1
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label: water bills growth
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reference:
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- title: Ofwat (and custom projections)
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href: https://www.ofwat.gov.uk/price-review/

‎policyengine_uk/utils/water/README.md‎

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# Water bills projections
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In this folder, we have:
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* `forecast_water_bills.py` - A script that projects water bills based on historical data and proposed increases.
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* `ofwat_increases.csv` A CSV with the data from [here](https://www.ccw.org.uk/our-work/price-review/how-much-will-my-water-and-sewerage-bills-increase-by-2030/breakdown-of-water-companies-bill-increases-2025-30/) with proposed pre-inflation increases for each water company.

‎policyengine_uk/utils/water/forecast_water_bills.py‎

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import pandas as pd
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from pathlib import Path
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def project_water_bills():
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df_pre_2025 = pd.DataFrame(
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{
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"Year": [2021, 2022, 2023, 2024, 2025],
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"Oftwat avg bills (real)": [486, 470, 486, 492, 503],
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"CPIH": [113.1, 123.0, 129.9, 134.0, 139.0],
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}
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)
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df_pre_2025["Oftwat avg bills (nominal)"] = (
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df_pre_2025["Oftwat avg bills (real)"] * df_pre_2025["CPIH"] / 100
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)
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df_pre_2025["Oftwat avg bills (nominal)"] = (
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df_pre_2025["Oftwat avg bills (nominal)"]
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/ df_pre_2025["Oftwat avg bills (nominal)"].iloc[0]
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* 100
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).round(1)
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df_pre_2025["Nominal YoY change"] = (
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df_pre_2025["Oftwat avg bills (nominal)"].pct_change() * 100
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).round(1)
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proposed_increases = pd.read_csv(
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Path(__file__).parent / "ofwat_increases.csv"
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)
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avg_bills_2025_onwards = (
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proposed_increases[proposed_increases.columns[1:]].mean()[1:].values
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)
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df_post_2025 = pd.DataFrame(
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{
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"Year": [2025, 2026, 2027, 2028, 2029],
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"CPIH": [139.0, 142.2, 145.2, 148.2, 151.3],
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"Pre-inflation avg bills (nominal)": avg_bills_2025_onwards,
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}
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)
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# Add CPIH to each year's change
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df_post_2025["Avg bills (nominal)"] = df_post_2025[
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"Pre-inflation avg bills (nominal)"
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].values
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df_post_2025["CPIH change"] = df_post_2025["CPIH"].pct_change() * 100
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for year in range(2026, 2030):
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row = df_post_2025[df_post_2025["Year"] == year].iloc[0]
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cpi_change = (
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row["CPIH"]
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/ df_post_2025[df_post_2025["Year"] == year - 1]["CPIH"].values[0]
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- 1
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) * 100
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# Increase the nominal bills by the CPIH change
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addition = df_post_2025.loc[
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df_post_2025["Year"] == year - 1, "Avg bills (nominal)"
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].values[0] * (cpi_change / 100)
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# Add addition to this and future years
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df_post_2025.loc[
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df_post_2025["Year"] >= year, "Avg bills (nominal)"
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] += addition
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df_post_2025["Relative change"] = (
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df_post_2025["Avg bills (nominal)"].pct_change() * 100
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).round(1)
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df_post_2025
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combined_water_forecast = pd.DataFrame(
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{
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"Year": list(range(2022, 2030)),
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"Average nominal bills YoY change": df_pre_2025[
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"Nominal YoY change"
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].tolist()[1:]
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+ df_post_2025["Relative change"].tolist()[1:],
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}
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)
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print(combined_water_forecast.to_markdown(index=False))

‎policyengine_uk/variables/input/consumption/property/water_and_sewerage_charges.py‎

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label = "water and sewerage charges"
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documentation = "Total amount spent on water and sewerage charges"
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definition_period = YEAR
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uprating = "gov.economic_assumptions.indices.ofwat.water_bills"

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