CHILD POVERTY IN THE UK:CHILD POVERTY IN THE UK:SOCIO-DEMOGRAPHIC SCENARIOS TO 2020 SOCIO-DEMOGRAPHIC SCENARIOS TO 2020

FOR CHILDRENFOR CHILDREN

Phil Rees & John Parsons University of Leeds

Paper presented at the Third International Population

Geographies ConferenceUniversity of Liverpool, Liverpool, UK

19-21 June 2006

Context (1): Questions asked

• The work was part of a School of Geography, Leeds (SOG) project for the Joseph Rowntree Foundation (JRF) in collaboration with the Institute for Fiscal Studies, London (IFS)

• JRF wished to know answers to these questions:– Will the government hit its child poverty reduction

targets?– Are socio-demographic trends favourable for

achieving these goals or not?– How will poverty alleviation strategies affect children

in different parts of the United Kingdom?

Table 1. Child Poverty (GB) estimates and targets

Year Mid-point of

interval

Children in poverty

AHC (millions)

Number of children

(millions)

Percent in poverty

AHC

1998/99 FY 1998.9 4.11 12.71 32.5 1999/00 FY 1999.9 4.11 12.71 31.9 2000/01 FY 2000.9 3.81 12.71 30.3 2001 MY 2001.6 12.7852 2001/02 FY 2001.9 3.71 12.61 29.6 2002/03 FY 2002.9 3.61 12.61 28.3 2003/04 FY 2003.9 3.51 12.51 27.8 2004/05 FY 2004.9 3.41 12.61 27.2 2010 MY 2010.6 12.3972 2010/11 FY 2010.9 2.13 12.3985 17.2 2020 MY 2020.6 12.4342 2020/21 FY 2020.9 1.04 12.4356 8.4

Tony Blair (1999): “this government will eradicate child poverty by 2020”

IFS interprets government statements to mean:

1998/9 to 2004/5: 25% reduction in numbers

1998/9 to 2010: 50% reduction in numbers

2010 to 2020: 50% reduction in numbers (not “official”)

Child poverty

living on less than 60% of UK average (median) income (household income standardised for number of adults & children)

AHC After Housing Costs

These are really ambitious targets

Will socio-demographic trends help?

Context (2): What was needed?

• IFS method is to run a micro-simulation model for households, families and children using inputs from the latest Family Resources Survey (DWP/ONS)

• IFS needed to re-weight the micro-population using key population variables projected to 2010 and 2020 and SOG

• IFS/SOG might have created a dynamic household microsimulation model but time and resource limits meant this was not possible (though two teams in SOG are doing this in current projects with EPSRC and ESRC support)

Our “pragmatic” approach• Use the Individual Sample of Anonymised Records from the 2001

Census of Population to create an 8-dimensional population array: P2001(x1, …, x8)

• Develop 8 sub-array projections for 2010 and 2020: P2010(x1,x2), P2010(x3) etc = marginal distributions of the full array

• Apply Iterative Proportional Fitting to adjust the 2001 population array to the 2010 and 2020 constraints

• Because the data came from many different sources and despite adjusting each sub-array to the same grand UK population total, we were not satisfied with the robustness of the results (further work planned to resolve this by Parsons, Jin and Rees)

• Nevertheless, the marginal distributions were considered reasonable projections of each dimension for IFS to use them to re-weight their microsimulation results

• Full reports will be published by the Joseph Rowntree Foundation this summer

The seven population dimensions projected for each region

• Age and sex, with child dependency– Ages 16-18 split between dependent and non-dependent children

• Household size– Large households are at higher risk of poverty

• Number of dependent children– Families with many children tend to be poor

• Family type– Some types e.g. lone parent families are at high risk of poverty

• Ethnic groups– Some groups face higher poverty risk than others

• Number of earners in household– Non-earner households are poorer

• Tenure– Households in some tenure types (e.g. social housing) tend to be poor

Methods

• A mix of methods was used to project these marginal dimensions into the future

• Mostly we used extrapolation based on trends 1981-2001 in census distributions

• Sometimes we used trends in FRS distributions for 1998-2004

• For ethnic groups we built a cohort-component demographic projection model

• The paper goes into the detail of data sources and methods

• In the rest of the presentation, attention is focussed on our results and their implications for child poverty

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0-9 10-15 16-19d

16-19n

20-24 25-29 30-44 45-59 60+

Age group

UK

po

pu

lati

on

(10

00s)

2001

2010

2020

Year 0-9 10-15 16-19d 16-19n 20-24 25-29 30-44 45-59 60+ 2001 7206 4648 1384 1526 3555 3845 13291 11144 12237 2010 6945 4313 1557 1597 4209 4137 12691 12123 14048 2020 7136 4257 1439 1362 3900 4355 12652 13069 16278

Fig. 1. Trends in UK population by broad age, 2001, 2010 and 2020

0

10000

20000

30000

40000

50000

60000

70000

2001 2010 2020

Year

Non-dependents

Dependent children

2004 based projections 2001 2010 2020 Dependent children 13239 12815 12832 Non-dependents 45598 48804 51617

Fig. 2. Trends in dependent children, 2001, 2010 and 2020

The 2004-based UK projections (the latest) see population growth continuing until the 2070s, despite below replacement fertility, because of higher migration assumptions and improving longevity.

But the population continues to age and the number of children fluctuate (echoes of echoes of the baby boom).

The number of dependent children is falling in this decade but not in the next (in part because of a small shift from non-dependency to dependency among 16-18 year olds).

The numbers help attainment of the 2010 target but not the 2020.

Projected population change (2001=100)

90

95

100

105

110

115

120

NE NW YH EM WM EA SE SW IL OL SC WA NI UK

Region/Country

% o

f 20

01 p

op

ula

tio

n2010

2020

Year NE NW YH EM WM EA SE SW IL OL SC WA NI UK 2001 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2010 101.1 102.7 103.9 106.6 103.5 107.0 105.7 107.0 108.5 105.8 101.1 104.2 104.2 104.7 2020 101.0 105.3 107.6 112.6 106.9 114.7 112.2 114.4 117.4 112.3 101.3 108.6 108.0 109.5

Fig. 3. Projected regional populations, 2010 and 2020

These figures combine GAD 2004 national projections with 2003 regional projections for England. Southern regions are projected, because of lower mortality, higher immigration and net internal migration gains in younger ages, to grow faster than Northern. Note that the populations of the North East and of Scotland grow hardly at all.

Table 2. Changes in the numbers and regional composition of children in relation to income, Great Britain 2001, 2010 and 2020

GOR/Country Income Numbers of Children % GB Change in %

2004/5 2001 2010 2020 2001 2010 2020 2001-2010

2001-

2020

£ per week 1000s 1000s 1000s % % %

North East 279 556 507 475 4.35 4.09 3.82 -0.26 -0.52 Yorks & Humb 286 1129 1073 1067 8.83 8.65 8.58 -0.18 -0.25 Wales 287 659 624 615 5.15 5.04 4.95 -0.12 -0.21 West Midlands 288 1222 1171 1171 9.55 9.45 9.42 -0.11 -0.13 North West 294 1560 1456 1430 12.20 11.74 11.50 -0.46 -0.71 East Midlands 295 933 914 921 7.30 7.37 7.41 0.07 0.11 South West 310 1048 1038 1053 8.20 8.38 8.47 0.18 0.27 Scotland 313 1075 985 929 8.40 7.95 7.47 -0.46 -0.93 Inner London 318 606 627 665 4.74 5.06 5.35 0.32 0.61 Outer London 318 1009 1015 1046 7.89 8.19 8.42 0.29 0.52 East 335 1208 1218 1256 9.45 9.82 10.10 0.38 0.65 South East 337 1781 1770 1804 13.93 14.27 14.51 0.35 0.58 Great Britain 304 12785 12397 12434 100.00 100.00 100.00 0.00 0.00 Northern Ireland 301 453 418 398 3.55 3.37 3.20 -0.18 -0.35

These projected population changes shift the distribution of children towards regions with higher incomes (after housing costs). This will be helpful for the achievement of the child poverty reduction goals.

0

5,000

10,000

15,000

20,000

25,000

Not inHH

Visitors 1 2 3 4 5 6+

Household size

UK

po

pu

lati

on

(th

ou

san

ds)

2001

2010

2020

Fig. 4. Projected UK population by household size, 2001, 2010 and 2020

Our projections of population by household size (based mainly on extrapolating 1981-2001 trends because the national projections fail to provide much information!) show a continuing fall in the numbers of larger households (with 4, 5 or 6+ persons).

Again, this trend favours attainment of child poverty goals.

We use a set of cartograms to display the changes in the population variables.

The cartogram assigns an area on the map in proportion to the regional population (developed by Durham, Dorling and Rees).

The cartogram gives due population weight to the urban region of London.

Fig. 6. Percentage of people in each region in 4+ person households, 2001 and 2020

These maps show a uniform and substantial fall (25%) in the percent of people living in larger households between 2001 and 2020.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

UK

po

pu

lati

on

in d

epen

den

t ch

ildre

n h

ou

seh

old

s

3+ d.c.

2 d.c.

1 d.c.

0 d.c.

3+ d.c. 12.509% 10.475% 10.794%

2 d.c. 18.683% 18.209% 18.266%

1 d.c. 13.761% 13.543% 13.479%

0 d.c. 55.047% 57.773% 57.460%

2001 2010 2020

Fig. 7. Trends in the composition of the UK population by the number of dependent children per household, 2001, 2010 and 2020

Fig. 8. Percentage of people in each region in 3+ dependent children households, 2001 and 2020

The graph and maps confirm that the fall in household sizes is due to both fewer people living in households with dependent children and a fall in share of households with 3 or more dependent children

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

UK

po

pu

lati

on

by

fam

ily t

ype

Other multi-person 10.933% 13.794% 14.749%

One person 12.695% 14.189% 16.277%

Cohabiting Couple 9.055% 12.488% 13.172%

Married Couple 54.542% 50.144% 46.778%

Lone Parent 10.988% 7.597% 7.233%

Not in family 1.787% 1.789% 1.791%

2001 2010 2020

Fig. 9. Projected UK population by family type

Fig. 10. Percentage of people in each region in lone parent households, 2001 and 2020

Lone parent families are the poorest and our projections show a reduction in the share of the population living in these households, except in London.

0

10,000

20,000

30,000

40,000

50,000

60,000

Po

pu

lati

on

in

UK

(10

00s)

White non-dep. 42,744.172 44,667.588 46,432.429

White dependents 11,681.801 11,007.072 10,675.986

2001 2010 2020

0

500

1,000

1,500

2,000

2,500

3,000

Chinese

& O

ther

non

-dep

.

Chinese

& O

ther

dep

ende

nts

Black n

on-d

ep.

Black d

epen

dent

s

Asian no

n-dep

.

Asian de

pend

ents

Mixe

d non

-dep

.

Mixe

d dep

ende

nts

Po

pu

lati

on

in

UK

(10

00s)

2001

2010

2020

Fig. 11. Projected UK population by ethnic group

The White population grows a little during the 2001-2020 period (mainly because of new immigration).

The Ethnic Minority population grows very substantially because of demographic momentum and high immigration.

However, there are differences between the groups in terms of (child) dependents. Very little growth of dependent children in the Black group, high growth in Asian and Mixed dependent children.

0

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300

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0-9 10-15 16-19d 16-19n 20-24 25-29 30-44 45-59 60+

Age group

Asi

an p

op

ula

tio

n (

1000

s)

2001

2010

2020

Fig. 12. Projected Asian population by age group

This graph for the Asian population shows the growth in dependent children but note that there is higher relative growth in the labour force and older ages (as a result of the ageing of earlier cohorts). Fertility rates in the Asian groups are converging to lower national levels.

Fig. 13. Percent of the population who are White in 2001 and 2020

Our projections show what changes are likely in the ethnic composition of the regions of the country. There are profound contrasts in ethnic diversity between the South & East regions and the Celtic periphery.

The changing population mix will tend to work against the attainment of child poverty reduction goals as the population shifts towards groups with larger and poorer populations on average.

Fig. 14. Percent of the population who are Asian in 2001 and 2020

What is interesting about this map is that the greatest relative change in regions that have lower concentrations. There is deconcentration of the ethnic minority population at regional scale (and also probably within regions and cities – see papers by Simpson).

The implications for child poverty reduction are indirect. The ethnic minority populations growing fastest outside their areas of concentration are probably better off and suffer less from child poverty, so this is a favourable trend.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2001 2010 2020

3+ earners

2 earners

1 earner

No earners

N/A

Fig. 15. UK population by the number of earners per household

No great changes projected here, but this ignores other influences on the number of earners such as rising age at retirement, continuing rise in female labour force participation and measures to encourage lone parents and working age persons on disability benefit into work.

Fig. 16. Percentage of people in each region in households with no earners, 2001 and 2020

It is difficult to be confident about the flatness of the trends here. This is based on extrapolation of two decades of Conservative and Labour government. Imagine the contribution to national wealth and child poverty reduction if all regions could attain the labour force participation of the East of England (Cambridge, Peterborough, Norwich, Ipswich etc).

Fig. 18. Percentage of people in each region in social rent households, 2001 and 2020

Our projections see continuing reduction in the social rent household category. This is helpful for reaching child poverty reduction targets. However, London appears to be an exception, with a rising proportion in social rented housing.

Conclusions

• The government’s child poverty reduction target is tough and it has missed it 2004/5 target (though not by much).

• The reductions will need to accelerate to achieve 2010 and 2020 targets

• Socio-demographic trends are favourable in small ways (because the targets are defined in number rather than percent terms).

• However, some trends move in the opposite directions so the net effect is unclear. We need to be confident about our SAR/IPF model or in future dynamic micro-simulation models to be certain what the overall outcome will be.

• When the IFS work is published, we will be able to judge the effect of socio-demographic trends against anticipated or suggested policy changes.