Trutz Haase & Jonathan Pratschke

THE 2011 POBAL HP DEPRIVATION INDEX FOR SMALL AREAS (SA)

Conceptual Underpinnings

Dublin, August 2012

THE PURPOSE OF COMPOSITE DEPRIVATION INDICES

1. It is difficult to simultaneously comprehend the spatial distribution of multiple indicators

at multiple points in time

2. For practical purposes, there is a need for a single indicator which draws a variety of

observations together

3. Such indices can provide the basis for the effective targeting of the most

disadvantaged areas

4. Such indices can provide a means by which to assess changes over time, and facilitate

monitoring and evaluation

5. However, it is important that such indices enjoy broad support amongst all key

stakeholders, including government departments, state agencies, community

representatives and the broader public

Deprivation Index Small Area Data in General

To provide insights into the spatial distribution of poverty and deprivation

To identify the specific needs of localities

To provide a basis for consensus-building on targeting need in particular areas

To improve specific services or the integration of multiple services at local level

To facilitate inter-temporal comparison To inform policies that address poverty and deprivation at local level

As a proxy for socio-economic status (SES) when modelling health and other outcomes

n/a

THE PURPOSE OF DEPRIVATION INDICES

Deprivation Index Small Area Data in General

Data ought to be concise (i.e. brief but comprehensive)

Should be more comprehensive

Data need to be consistent for all spatial units Greater emphasis on domains (to inform sectoral policies)

Data needs to be consistent over timeMay include data which are not available for all areas

Data ought to be timely Does not necessarily have to be consistent over time

Ought to have precise statistical properties (ideally normally distributed)

n/a

REQUIREMENTS

Deprivation Index Small Area Data in General

Data have to be available at identical units of analysis

May comprise data at different levels of spatial aggregation

Near-normal distribution of input variables Overall less restrictive

May require transformations n/a

Requires dimensional analysis to avoid double counting

n/a

Requires methods and weights for combining into single index scores

n/a

MEASUREMENT CONSIDERATIONS

Relative Poverty

“People are living in poverty if their income and resources (material, cultural and social) are so inadequate as to preclude them from having a standard of living which is regarded as acceptable by Irish society generally.”

(Government of Ireland, NAPS, 1997)

Relative Deprivation

“The fundamental implication of the term deprivation is of an absence – of essential or desirable attributes, possessions and opportunities which are considered no more than the minimum by that society.”

(Coombes et al., DoE – UK, 1995)

A COMPREHENSIVE DEFINITION OF POVERTY

EFA is essentially an exploratory technique; .i.e. data-driven

all variables load on all factors

the structure matrix is the (accidental) outcome of the variables available

EFA cannot be used to compare outcomes over time

V1

V2

V3

V4

V5

V6

F1

F2

Ordinary Factor Analysis (EFA) reduces variables to a smaller number of underlying Dimensions or Factors

TRADITIONAL APPROACH: EXPLORATORY FACTOR ANALYSIS (EFA)

CFA requires a strong theoretical justification before the model is specified

the researcher decides which of the observed variables are to be associated with which of the latent constructs

variables are conceptualised as the imperfect manifestations of the latent concepts

CFA model allows the comparison of outcomes over time

CFA facilitates the objective evaluation of the quality of the model through fit statistics

V1

V2

V3

V4

V5

V6

L1

L2

Confirmatory Factor Analysis also reduces observations to the underlying Factors, however

1

2

3

4

5

6

NEW APPROACH: CONFIRMATORY FACTOR ANALYSIS (CFA)

true multidimensionality, based on theoretical considerations

provides for an appropriate treatment of both urban and rural deprivation

no double-counting

rational approach to indicator selection

uses variety of alternative fit indices to test model adequacy

identical structure matrix across multiple waves

identical measurement scale across multiple waves

true distances to means are maintained (i.e. measurement, not ranking)

distinguishes between measurement of absolute and relative deprivation

allows for true inter-temporal comparisons

STRENGTHS OF CFA-BASED DEPRIVATION INDICES

OVERVIEW OF SUCCESSIVE DEPRIVATION INDICES, HAASE & PRATSCHKE 1996 - 2012

91 96 02 06 11

06 11

06 11

91 96 02 06 11 06 11

91 96 02 06 11 06 11

91 96 02 06 11 06 11

91 96 02 06 11 06 11

91 96 02 06

06

06

91 96 02 06 06

91 96 02 06 06

91 96 02 06 06

91 96 02 06 06

86 91 96

86 91 96

86 91 96

86 91 96

86 91 96

96

96

96

96

96

91

91

91

91

91

SA n=18,488

ED n = 3,409

NUTS 4 n = 34

NUTS 3 n = 8

NUTS 2 n = 2

NUTS 1 n = 1

Haase et al., 1996

Haase, 1999

Pratschke & Haase, 2004Haase & Pratschke, 2005 Haase & Pratschke, 2008

Haase & Pratschke, 2010Haase & Pratschke, 2012

91 96 02

91 96 02

91 96 02

91 96 02

91 96 02

Pratschke & Haase, 2001

01NI

01NI

01NI

01NI

01NI

01NI

Haase & Pratschke, 2011Level at which model is estimated

Level to which data is aggregated

06 11

Demographic Decline (predominantly rural)

population loss and the social and demographic effects of emigration (age dependency, low education of adult population)

Social Class Deprivation (applying in rural and urban areas)

social class composition, education, housing quality

Labour Market Deprivation (predominantly urban)

unemployment, lone parents, low skills base

THE UNDERLYING DIMENSIONS OF SOCIAL DISADVANTAGE

Age Dependency Rate1

Population Change2

Primary Education only3

Third Level Education4

Professional Classes

5Persons per Room

6

Lone Parents

7 Semi- and Unskilled Classes

8

Male Unemployment Rate9

Female Unemployment Rate 10

DemographicGrowth

Social ClassComposition

Labour MarketSituation

THE BASIC MODEL OF THE POBAL HP DEPRIVATION INDEX

SOLUTION 2:A LONGITUDINAL SEM MODEL

Professional Classes 200612

Semi- and Unskilled Classes 200613

Social ClassComposition

Lone Parents 20069

Male Unemployment Rate 200614

Female Unemployment Rate 200615

Labour MarketSituation

Age Dependency Rate 20067

Population Change 2002-068

Primary Education only 200610

Third Level Education 200611

DemographicGrowth

Persons per Room 200616

Professional Classes 2011 22

Semi- and Unskilled Classes 2011 23

Social ClassComposition

Lone Parents 2011 19

Male Unemployment Rate 2011 24

Female Unemployment Rate 2011 25

Labour MarketSituation

Age Dependency Rate 2011 17

Population Change 2006-11 18

Primary Education only 2011 20

Third Level Education 2011 21

DemographicGrowth

Persons per Room 2011 26

2006

2006

2006

2011

2011

2011

1

3

2

-0.61

0.46

-0.63

-0.51

0.53

0.69

-0.57

0.24

0.95

-0.860.20

-0.65

-0.76

-0.68

0.17

0.820.14

-0.54

0.36

-0.59

0.46

0.49

-0.58

0.73

-0.51

0.97

-0.89

-0.64

-0.86

-0.74

0.89

0.92

0.61

-0.06

0.10

0.03

0.04

0.03

0.35

-0.17

0.63

0.01

0.18

2006 2011

COMPARISON OF MODELS

• Both the means model and the longitudinal model rely on the same factor model

• Using the means model, it is possible to measure the change that occurred in the mean of the latent variables between 2006 and 2011

• Both the means model and the longitudinal model impose equality constraints on all factor loadings

• The Pobal HP Deprivation Index is estimated using a multiple group means and covariance structure model

DISTRIBUTION OF HP INDEX SCORES, 2006 AND 2011

The Figure shows the distribution of the 2006 and 2011 Absolute HP Index Scores in 5-point ranges (one half of a standard deviation)

most disadvantaged most affluent

SMOOTHED DISTRIBUTION OF ABSOLUTE HP INDEX SCORES, 2006 AND 2011

The Figure shows the decline by 7.0 points in the mean of the Absolute HP Index Scores between 2006 and 2011 (or 0.7 of a standard deviation)

most disadvantaged most affluent

SMOOTHED DISTRIBUTION OF RELATIVE HP INDEX SCORES, 2006 AND 2011

The Figure shows the distribution of the 2006 and 2011 Relative HP Index Scores, after de-trending the absolute scores by the difference in means

most disadvantaged most affluent

most disadvantagedmost disadvantaged most affluentmost affluent

marginally below the average marginally above the average

disadvantaged affluent

very disadvantaged very affluent

extremely disadvantaged extremely affluent

MAPPING DEPRIVATION

COMPARISON OF 2006 AND 2011 ABSOLUTE INDEX SCORES

COMPARISON OF 2006 AND 2011 RELATIVE INDEX SCORES

ABSOLUTE INDEX SCORES2006

Absolute Index Score 2006Haase & Pratschke 2012

30 to 50 (22)20 to 30 (293)10 to 20 (2513)0 to 10 (6857)

-10 to 0 (5925)-20 to -10 (2294)-30 to -20 (564)-60 to -30 (20)

ABSOLUTE INDEX SCORES2011

Absolute Index Scores 2011Haase & Pratschke 2012

30 to 50 (2)20 to 30 (70)10 to 20 (838)0 to 10 (3397)

-10 to 0 (7181)-20 to -10 (5132)-30 to -20 (1719)-60 to -30 (149)

Shows the massive increase in disadvantage in wake of the recession after the 2006 Census, affecting literally every part of the country.

COMPARISON OF ABSOLUTE DEPRIVATION SCORES, 1991 AND 2006

RELATIVE INDEX SCORES2006

Relative Index Score 2006Haase & Pratschke 2012

30 to 50 (22)20 to 30 (293)10 to 20 (2513)0 to 10 (6857)

-10 to 0 (5925)-20 to -10 (2294)-30 to -20 (564)-60 to -30 (20)

RELATIVE INDEX SCORES2011

Relative Index Score 2011Haase & Pratschke 2012

30 to 50 (30)20 to 30 (474)10 to 20 (2412)0 to 10 (6232)

-10 to 0 (6483)-20 to -10 (2408)-30 to -20 (447)-60 to -30 (2)

The pattern between affluence and disadvantage, whereby affluence is greatest in the urban peripheries and gradually declining towards more rural locations, remains broadly intact.

There is some indication that the reach of the affluent commuter belts has somewhat diminished.

Within the Greater Dublin Area, there is a marked shift in the location of the most affluent areas. Whereas in 2006 the Western part of the Region scored high in affluence, in 2011 this is again primarily concentrated in Dun Laoghaire / Rathdown.

COMPARISON OF RELATIVE DEPRIVATION SCORES, 1991 AND 2006

CHANGE IN RELATIVE INDEX SCORES2006-2011

Change in Relative HP Index Scores, 2006-2011Haase and Pratschke 2012

improvement by more than 30 points (15)improvement by 20 to 30 points (45)improvement by 10 to 20 points (405)improvement by less than 10 points (8195)no data in 2006 (252)deterioration by less than 10 points (9210)deterioration by 10 to 20 points (350)deterioration by 20 to 30 points (14)deterioration by more than 30 points (2)