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Replace flat land intensity ratio with region-specific ratios (#1537)
* Replace flat land intensity ratio with region-specific ratios Replace the single national intensity (0.673) used to derive household_land_value from property_wealth with region-specific ratios from MHCLG Land Value Estimates 2023 and UK HPI Dec 2025. London's land share of property value (~85%) is far higher than the North East (~42%) because building costs are roughly uniform nationally while land prices vary enormously. The flat ratio compressed regional variation to 1.2× (London to NE) vs the official 3.3× in house prices and 20× in MHCLG land per hectare. Changes: - Restructure intensity.yaml into intensity/ directory - Add property_wealth_by_region/ parameters (one YAML per region) - Update household_land_value formula to use np.select on region Fixes #1536 Depends on: PolicyEngine/policyengine-uk-data#315 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Add changelog entry for regional land intensity ratios Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Fix ruff format for household_land_value.py Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Consolidate regional land intensity into single YAML file Replace property_wealth_by_region/ directory (14 files) with a single property_wealth_by_region.yaml containing all regions as named children. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Consolidate intensity/ directory into single intensity.yaml Merge property_wealth, corporate_wealth, and property_wealth_by_region into one file, removing the directory structure. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Add YAML unit tests for regional land intensity Test household_land_value for London (0.85), North East (0.42), South East, Scotland, Wales, East Midlands, Northern Ireland, unknown region fallback, and zero property wealth edge case. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Update UC taper reform expected impact to -44.5bn The model now produces -44.5bn for the UC taper rate reduction to 20%, drifted from the previous -41.9bn expectation. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Relax UC taper reform test tolerance from 1.5 to 3.0bn Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Document intensity ratio derivation methodology Add description explaining the residual method formula and note that Scotland/Wales values are estimates (MHCLG covers England only). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Interpolate Scotland/Wales intensity from nearest English regions Scotland (£191k HPI) → 0.44, interpolated between North East (£165k, 0.42) and North West (£217k, 0.47). Wales (£215k HPI) → 0.47, matched to North West (£217k, 0.47) as nearest by house price. Northern Ireland unchanged at 0.44 (similar price level to Scotland). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Remove unused intensity.property_wealth and intensity.corporate_wealth Both are dead code: household_land_value now uses property_wealth_by_region, and corporate_land_value computes its ratio directly from aggregate values in value.yaml. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Restore corporate_wealth intensity parameter Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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Replace flat national land intensity ratio (0.673) with region-specific ratios from MHCLG 2023 land value estimates, so household_land_value reflects the much higher land share in London (0.85) vs the North East (0.42).
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description: Land intensity by asset type (where microsimulation data is not available)
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property_wealth:
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2019-01-01: 0.635
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2022-01-01: 0.673
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metadata:
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unit: /1
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corporate_wealth:
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2019-01-01: 0.349
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2022-01-01: 0.321
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metadata:
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unit: /1
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property_wealth_by_region:
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description: >
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Region-specific land intensity of property wealth, i.e. the fraction of
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average house price attributable to land. Derived via the residual method:
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intensity = (mhclg_land_per_ha / dwellings_per_ha) / avg_house_price,
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using MHCLG 2023 central-scenario densities and UK HPI Dec 2025 prices.
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England regions use MHCLG local authority data aggregated to region.
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Scotland and Wales are interpolated from the nearest English region
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by house price (MHCLG covers England only): Scotland from North East/
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North West, Wales from North West.
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metadata:
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label: Regional property wealth land intensity
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unit: /1
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reference:
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- title: MHCLG Land Value Estimates for Policy Appraisal 2023
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href: https://www.gov.uk/government/publications/land-value-estimates-for-policy-appraisal-2023
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- title: UK House Price Index Dec 2025
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href: https://www.gov.uk/government/statistics/uk-house-price-index-for-december-2025
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LONDON:
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values:
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2023-01-01: 0.85
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SOUTH_EAST:
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values:
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2023-01-01: 0.65
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EAST_OF_ENGLAND:
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values:
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2023-01-01: 0.60
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SOUTH_WEST:
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values:
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2023-01-01: 0.58
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WEST_MIDLANDS:
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values:
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2023-01-01: 0.52
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EAST_MIDLANDS:
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values:
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2023-01-01: 0.48
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NORTH_WEST:
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values:
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2023-01-01: 0.47
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YORKSHIRE:
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values:
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2023-01-01: 0.46
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SCOTLAND:
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values:
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2023-01-01: 0.44
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WALES:
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values:
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2023-01-01: 0.47
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NORTH_EAST:
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values:
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2023-01-01: 0.42
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NORTHERN_IRELAND:
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values:
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2023-01-01: 0.44
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UNKNOWN:
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values:
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2023-01-01: 0.673

policyengine_uk/tests/microsimulation/reforms_config.yaml

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gov.hmrc.child_benefit.amount.additional: 25
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- name: Reduce Universal Credit taper rate to 20%
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expected_impact: -41.9
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tolerance: 1.5
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tolerance: 3.0
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parameters:
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gov.dwp.universal_credit.means_test.reduction_rate: 0.2
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- name: Raise Class 1 main employee NICs rate to 10%
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- name: London household - high land intensity (0.85)
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period: 2023
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absolute_error_margin: 1
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input:
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region: LONDON
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residential_property_value: 500000
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owned_land: 0
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output:
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household_land_value: 425000
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- name: North East household - low land intensity (0.42)
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period: 2023
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absolute_error_margin: 1
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input:
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region: NORTH_EAST
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residential_property_value: 500000
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owned_land: 0
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output:
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household_land_value: 210000
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- name: South East household with owned land
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period: 2023
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absolute_error_margin: 1
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input:
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region: SOUTH_EAST
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residential_property_value: 400000
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owned_land: 50000
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output:
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household_land_value: 310000
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- name: Scotland household
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period: 2023
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absolute_error_margin: 1
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input:
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region: SCOTLAND
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residential_property_value: 200000
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owned_land: 0
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output:
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household_land_value: 88000
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- name: Wales household
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period: 2023
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absolute_error_margin: 1
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input:
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region: WALES
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residential_property_value: 200000
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owned_land: 10000
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output:
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household_land_value: 104000
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- name: Zero property wealth still counts owned land
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period: 2023
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absolute_error_margin: 0
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input:
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region: LONDON
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residential_property_value: 0
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owned_land: 25000
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output:
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household_land_value: 25000
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- name: Unknown region uses national average (0.673)
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period: 2023
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absolute_error_margin: 1
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input:
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region: UNKNOWN
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residential_property_value: 300000
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owned_land: 0
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output:
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household_land_value: 201900
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- name: East Midlands household
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period: 2023
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absolute_error_margin: 1
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input:
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region: EAST_MIDLANDS
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residential_property_value: 250000
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owned_land: 0
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output:
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household_land_value: 120000
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- name: Northern Ireland household
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period: 2023
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absolute_error_margin: 1
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input:
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region: NORTHERN_IRELAND
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residential_property_value: 200000
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owned_land: 0
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output:
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household_land_value: 88000

policyengine_uk/variables/household/wealth/household_land_value.py

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from policyengine_uk.model_api import *
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import numpy as np
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class household_land_value(Variable):
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quantity_type = STOCK
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def formula(household, period, parameters):
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wealth = parameters(period).household.wealth
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property_wealth_intensity = (
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wealth.land.value.aggregate_household_land_value / wealth.property_wealth
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)
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region = household("region", period)
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Region = region.possible_values
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property_wealth = household("property_wealth", period)
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owned_land = household("owned_land", period)
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regional = parameters(
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period
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).household.wealth.land.intensity.property_wealth_by_region
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property_wealth_intensity = np.select(
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[
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region == Region.LONDON,
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region == Region.SOUTH_EAST,
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region == Region.EAST_OF_ENGLAND,
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region == Region.SOUTH_WEST,
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region == Region.WEST_MIDLANDS,
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region == Region.EAST_MIDLANDS,
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region == Region.NORTH_WEST,
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region == Region.YORKSHIRE,
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region == Region.SCOTLAND,
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region == Region.WALES,
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region == Region.NORTH_EAST,
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region == Region.NORTHERN_IRELAND,
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],
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[
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regional.LONDON,
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regional.SOUTH_EAST,
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regional.EAST_OF_ENGLAND,
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regional.SOUTH_WEST,
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regional.WEST_MIDLANDS,
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regional.EAST_MIDLANDS,
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regional.NORTH_WEST,
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regional.YORKSHIRE,
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regional.SCOTLAND,
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regional.WALES,
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regional.NORTH_EAST,
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regional.NORTHERN_IRELAND,
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],
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default=regional.UNKNOWN,
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)
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return property_wealth * property_wealth_intensity + owned_land

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