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Towards a Dynamic View of UK Depriation: Harmonising the IMD Indices using Claimant Count Data

 

GISRUK Presentation, 20 March 2026

Johara Meyer, johara.meyer.25@ucl.ac.uk

  • Small-area deprivation measures have been a key feature of UK policymaking since at least the 1960s
  • Historically, national indexes of 'multiple deprivation' were based on annual census data
  • Early examples include the Carstairs and Morris index (Scotland) and the Townsend index (England)
  • Since 2001, the Index of Multiple Deprivation has been the UK government's official statistic of deprivation
  • IMD considers deprivation across multiple dimensions or ‘domains’ such as employment, health, and education
  • Domain scores are combined to calculate overall index scores, ranked, and divided into deciles

Introduction

  • Every nation in the UK uses a different IMD measure ( SIMD, NIMDM, WIMD, EIMD)
  • National IMD scores are not directly comparable
  • Underlying IMD data is often years out of date
  • What spatial patterns of deprivation are hidden through the use of national and out-of-date IMD measures in the UK?

The Issue:

Previous Work

  • Focussed on Temporal Differences: Annual Index of Deprivation (Autonomy)
  • Focussed on UK Comparison: Composite 2020 UK Index of Multiple Deprivation (MySociety), UK Deprivation Index (Nuffield Foundation)
  • My approach examines both issues to calculate IMD displacement in 2025 and across the UK

 

  • Comparing national IMDs - Key Differences and Similarities
  • Methodology - Harmonisation Approach and Claimant Count Comparison
  • Findings - National vs Harmonised IMD, National IMD vs 2025 Claimant Count
  • IMD Displacement Index - Putting it all together
  • Conclusion

Overview:

Comparing National IMDs 

Key differences between national IMD measures:

  • Temporal scope
  • Small area geographies
  • Domain weighting schemes
  • Underlying Indicators

Northern Ireland

NIMDM 2017

NIMDM 2017

SIMD 2020

EIMD 2025

WIMD 2025

Employment Domain Measures Comparison 

NIMDM 2017SIMD 2020WIMD 2025EIMD 2025
Job Seeker’s Allowanceyesyes
yesyes
New Style Jobseeker’s Allowanceyesyesyes
yes
Universal Credit (UC) in ’out of work’ categoriesyesyesyesyes
Income Support----------yesyes
Incapacity Benefityesyesyesyes
Severe Disablement Allowanceyesyesyesyes
Employment and Support Allowanceyesyesyesyes
New Style Employment and Support Allowanceyesyesyesyes
Carer’s Allowanceyes-----yesyes
People who do not receive benefits or income from employmentyes---------------

Non-Benfit Measures

Disability

Related

Non-Disability

Related

Benfit

Measures

claimant count

Methodology - IMD Displacement

  1. Modelling overall IMD scores as a function of Claimant Counts (CC)
  2. Standardising residuals to a reference nations' residual distribution
  3. Calculating harmonised IMD scores
  4. Re-ranking and dividing into UK population deciles
  5. Calculate rank and decile displacement
Step 1: Overall IMD score(Wales) = CC(Wales) + Residuals(Wales)
Step 2: Std.Residuals(Wales, ref=Eng) = Residuals(Wales)/Residuals(Eng)

 

Step 3: Harmonised overall IMD score(Wales, ref=England) = 
        CC(Wales) + Std.Residuals(Wales, ref=Eng)

Harmonising WIMD with EIMD as Reference Index

Step 5: IMD rank displacement(Wales, ref=Eng) =
        IMD rank(Wales) - Harmonised IMD rank(Wales, ref=Eng)

Methodology  - Claimant Count Comparison

  1. Collect Claimant Count and population data for timeperiod in national IMD
  2. Collect Claimant Count and population data for 2025
  3. Calculate Claimant Count score
  4. Calculate difference in Claimant Count scores
CC score (IMD) = (Claimant Count(IMD) /Population denominator(IMD) ) *100

CC score (2025) = (Claimant Count(2025) /Population denominator(2025))  *100
CC difference = CC score(IMD) - CC score(2025)

 

Index NameClaimant Count Data Collection Timeframe (IMD)Population Denominator (IMD)
SIMD 2020Feb, May, Aug, Nov 2017SAPE 2017 mid-year
NIMDM 2017April 2015 - March 2016
 		SAPE mid-2016 
WIMD 2025Apr 2022 - Mar 2023SAPE mid-2022
EIMD 2025Apr 2022 - Mar 2023SAPE mid-2022
Index NameClaimant Count Data Collection Timeframe (IMD)Population Denominator (IMD)
SIMD 2020Feb, May, Aug, Nov 2017SAPE 2017 mid-year
NIMDM 2017Dec, Nov, Oct, Sep, Aug, Jul, Apr 2015
and Jan, Feb 2016		SAPE mid-2016 
WIMD 2025Apr 2022 - Mar 2023SAPE mid-2022
EIMD 2025Apr 2022 - Mar 2023SAPE mid-2022
Index NameClaimant Count Data Collection Timeframe (IMD)Population Denominator (IMD)Claimant Count Data Collection Timeframe (2025)Population Denominator (2025)
SIMD 2020Feb, May, Aug, Nov 2017SAPE 2017 mid-yearJan 2025-Dec 2025NRS mid-2024
NIMDM 2017Dec, Nov, Oct, Sep, Aug, Jul, Apr 2015
and Jan, Feb 2016		SAPE mid-2016 Jan 2025-Dec 2025NISRA mid-2024 
WIMD 2025Apr 2022 - Mar 2023SAPE mid-2022Jan 2025-Dec 2025SAPE mid-2024
EIMD 2025Apr 2022 - Mar 2023SAPE mid-2022Jan 2025-Dec 2025SAPE mid-2024
IMD Decile
 		E
​(%)		N
​​(%)		S
(%)		W
(%)
19.3619.5810.8314.49
29.6713.89.2614.97
39.7914.888.713.28
49.8212.297.7515.87
59.9410.219.2412.33
610.18.759.369.92
710.187.489.858.47
810.297.529.397.24
910.44.6711.413.39
1010.450.8414.210.04

Decile Distribution Claimant Count Harmonisation Model 

by decile

by nation

Conclusion

  • There are significant differences in deprivation between UK nations which are concealed when national IMD measures are used 
  • The IMD displacement Index is an experimental approach to estimating the uncertainty of using out of date and national-scale deprivation statistics
  • We need up-to-date deprivation statistics that are comparable across nations and across time-periods
  • Administrative statistics like the claimant may be useful but we need to be careful with benefit-based measures of deprivation
  • “Poverty is a dynamic, not a static concept”  (Townsend, 1962: 219)

N
S
W

E            W            S

Agreement in

Decile Distribution

...affecting the allocation of local authority funding within and between UK nations

English Funding Formulas - £47 billion

UK Pride in Place Fund - £5 billion

A few months ago the new IMD for England and Wales dropped....

IMD Decile
 		ENSW
19.3619.5810.8314.49
29.6713.89.2614.97
39.7914.888.713.28
49.8212.297.7515.87
59.9410.219.2412.33
610.18.759.369.92
710.187.489.858.47
810.297.529.397.24
910.44.6711.413.39
1010.450.8414.210.04
IMD Decile
 		ENSW
19.8422.124.0715.99
29.8221.05613.68
39.9517.696.1612.97
49.9713.636.3614.69
510.1210.917.0412.45
610.338.897.568.88
710.254.3210.18.61
810.291.2912.076.25
910.250.113.265.7
109.18027.380.79

Decile Distribution Claimant Count Harmonisation Model 

IMD Decile

Decile Distribution Employment Domain Harmonisation Model

Percentage (%)

IMD Decile
 		E
​(%)		N
​​(%)		S
(%)		W
(%)
19.3619.5810.8314.49
29.6713.89.2614.97
39.7914.888.713.28
49.8212.297.7515.87
59.9410.219.2412.33
610.18.759.369.92
710.187.489.858.47
810.297.529.397.24
910.44.6711.413.39
1010.450.8414.210.04

Decile Distribution Claimant Count Harmonisation Model 

by decile

by nation

IMD Decile
 		E
​(%)		N
​​(%)		S
(%)		W
(%)
19.3619.5810.8314.49
29.6713.89.2614.97
39.7914.888.713.28
49.8212.297.7515.87
59.9410.219.2412.33
610.18.759.369.92
710.187.489.858.47
810.297.529.397.24
910.44.6711.413.39
1010.450.8414.210.04
IMD Decile
 		E
(%)		N
(%)		S
(%)		W
(%)
19.8422.124.0715.99
29.8221.05613.68
39.9517.696.1612.97
49.9713.636.3614.69
510.1210.917.0412.45
610.338.897.568.88
710.254.3210.18.61
810.291.2912.076.25
910.250.113.265.7
109.18027.380.79

Decile Distribution Claimant Count Harmonisation Model 

Decile Distribution Employment Domain Harmonisation Model

by decile

by nation

NIMDM 2017SIMD 2020WIMD 2025EIMD 2025
Job Seeker’s Allowanceyesyes
yesyes
New Style Jobseeker’s Allowanceyesyesyes
yes
Universal Credit (UC) in ’out of work’ categoriesyesyesyesyes
Income Support----------yesyes
Incapacity Benefityesyesyesyes
Severe Disablement Allowanceyesyesyesyes
Employment and Support Allowanceyesyesyesyes
New Style Employment and Support Allowanceyesyesyesyes
Carer’s Allowanceyes-----yesyes
People who do not receive benefits or income from employmentyes---------------

CHANGING THIS TO ONLY NATIONAL AND CC HARMONISED

  • High relative contributions to overall IMD scores, 20-28% across nations

  • Scores reflect what proportion of a population are 'employment deprived' 

  • In most cases, the underlying indicator is a count of the number of people claiming a range of employment related benefits 

 

  • (Note: Confusingly, the Welsh 'employment domain score' is rescaled from 0-100)

Employment Domain Comparisson 

https://www.gov.uk/government/statistics/english-indices-of-deprivation-2025/english-indices-of-deprivation-2025-statistical-release

  • Every nation in the UK uses a different IMD measure and they are not directly comparable
  • IMD data is out of date.

The Issue: