An Anatomy of Economic Inequality in Wales

Transcription

1 An Anatomy of Economic Inequality in Wales A report prepared on behalf of the Wales Equality and Human Rights Commission Presented by Rhys Davies, Stephen Drinkwater, Caroline Joll and Victoria Wass

2 Introduction National Equality Panel s (NEP) Report An Anatomy of Economic Inequality in the UK (`The Hills Report ) published in 2010 Provided national picture of economic outcomes (earnings, income and wealth) overall and for population sub-groups Relatively little data for regions, devolved nations What are the patterns of inequality in: a relatively deprived nation? a nation relatively reliant on the public sector as a source of work? a nation that has devolved law making powers?

3 Scope of Research EHRC commissioned WISERD to co-ordinate the production of a report for Wales The report sets out outcomes in education, employment, earnings, income, poverty and wealth in Wales a) in comparison to other areas of the UK b) compares outcomes where possible by gender, age, ethnicity, religion, disability and housing tenure More limited than Hills report due to time, resources and data 15 contributors from 4 Welsh Universities Project undertaken Nov 2010 Feb 2011 Report available from WISERD website

4 Data Sources Annual Population Survey main source of data for education, earnings and employment chapters sample sizes still small merged APS data 2004/5 to 2008/9 Other sources Education published data from National Pupil Database Income and Poverty Households Below Average Income, British Household Panel Survey, Family Resources Survey Wealth Wealth and Assets Survey These are research statistics not National Statistics would not always meet quality criteria of WAG/ONS points towards what is feasible

5 Overview of Welsh Population Wales Outer UK LESE UK Gender male Age < Ethnicity White Mixed Asian Black Other Religion Christian Non-Christian No religion Disability (working age) Not disabled APS 2004/5-8/9

6 Education and Employment Stephen Drinkwater * Melanie Jones * Mamata Parhi * Kate Robinson * Chris Taylor ** * Swansea University ** Cardiff University

7 Importance of Education Vital since its both a cause and effect of inequality Differences emerging from the early years seem to be key e.g. recent report on poverty and life chances in the UK and Heckman research for the US Also strong link here with social (im)mobility and intergenerational issues Higher education is also important given increased jobs polarisation (skill-biased technological change) and is obviously very topical from a policy perspective

8 Importance of Employment Key determinant of income differentials income largely consists of transfer payments or savings for the non-employed Not only a matter of having a job but also what type of job e.g. low incomes in low skill/minimum wage sectors and some types of part-time, temporary and self employment Closely associated with education given the importance of human capital accumulation for labour market outcomes Employment can also lead to improvements in social interaction, health and mental well-being

9 School Examination Results Taken from WAG published statistics Indicate increasing levels of achievement, esp. at Level 2 but Wales has fallen behind English regions => Burgess et al. (2010) examine this in some detail and find that most of the gap has occurred in schools below the first quartile also a recent fall in international ranking according to PISA Income appears to be very important pupils eligible for FSM are 2.5 times less likely to get A*-C Fairly small differences by gender but wide ethnic variation highest achievement by Chinese and lowest amongst Black groups Very low levels of achievement for those with SEN

10 Examination Results in Wales, 2000/1-2009/10 % aged 15 at the start of the academic year achieving % aged 17 achieving Level 1 Level 2 GCSE A*-C in core subjects No recognised qualification Level / / / / / / / / / /

11 % aged 15 at the start of the academic year KS4 Examination Results in Wales by Free School Meet Entitlement, Level 2 GCSE A*-C in core subjects1 Level 2 GCSE A*-C in core subjects1 Level 2 GCSE A*-C in core subjects Academ ic Achievem ent FSM eligible pupils Not eligible pupils

12 % aged 15 at the start of the academic year KS4 Examination Results in Wales by Gender, Level 1 Level 2 GCSE A*-C in core subjects1 Level 1 Level 2 GCSE A*-C in core subjects1 Level 1 Level 2 GCSE A*-C in core subjects Academ ic Achievem ent Boys Girls

13 % aged 15 at the start of the academic year KS4 Examination Results in Wales by Ethnic Group, White Mixed Asian Black Chinese or Chinese British Any other ethnic group Unknow n Ethnic Group Level 2 GCSE A*-C in core subjects1

14 KS4 Examination Results in Wales by Special Educational Needs, % aged 15 at the start of the academic year All pupils on SEN register Statemented School Action Plus School Action All pupils on SEN register Statemented School Action Plus School Action All pupils on SEN register Statemented School Action Plus School Action Special Educational Needs Level 2 GCSE A*-C in core subjects1

15 Highest Qualifications Analysis is based on working age population (excluding fulltime students) mainly using Annual Population Survey Combined GCSE category reported => due to limitations in which data is coded Other qualifications reported separately => important given increasing amount of immigrants, especially in some regions Labour Force Survey also used to show changes between 1992 and 2010 Increasing achievement in Wales has translated into a more highly qualified potential workforce but graduate gap with rest of the UK has increased slightly also a higher percentage with no qualifications in Wales

16 Rest of UK Wales Highest Educational Qualification of the Working Age Population % 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Working age population Higher degree Degree Higher education A level or equivalent GCSE or equivalent Other qualifications No qualifications

17 Variations in Qualifications: Selected Findings Small gender differences again with similar patterns to other parts of the UK higher (lower) % of females with GCSE (A levels) but higher % of graduates in LESE (proportion of males with higher degrees is quite noticeable) Large ethnic differences Indian males in Wales are extremely highly qualified (over a half have a degree), next come Chinese males high proportion of Pakistani (over a third) and Bangladeshi (almost a half) females in Wales have no qualifications Religious differences are in line with ethnicity findings highest % of graduates for Sikh/Hindu males, then Buddhists highest % with no qualifications amongst Muslim females

18 Variations in Qualifications (Continued) Those reporting no disabilities have the highest qualifications lowest educational outcomes for those reporting they are both DDA and work limiting disabled (almost 40% have no qualifications) similar to Outer UK but higher % reporting disabilities in Wales Variations by housing tenure also more pronounced in Wales social renters by far the least likely to be graduates (2% in Wales compared to around 20% in other tenure categories; 6% in LESE) far more likely to have no qualifications (37% in Wales, compared to 35% in Outer UK and 30% in LESE) Findings with respect to age as expected higher proportion of graduates and lower proportion with no qualifications amongst more recent cohorts Welsh speakers are more qualified, especially for females

19 Employment Employment status has been broken down into 9 categories Again the APS is mainly used but changes from 1992 to 2010 are also reported using the LFS Large differences reported between males and females in Wales and the rest of the UK much higher incidence of part-time work amongst females, especially in Wales males much more likely to be self-employed high % females looking after family/home but an increasing proportion of inactive students for both Some evidence of the impact of recessions => higher unemployment in 1992 and 2010

20 Breakdown of Employment Status for the Working Age Population in Wales Wales Female Wales Males % 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % working age population Employed, full-time Employed, part-time Self-employed ILO unemployed Inactive, student Inactive, looking after family, home Inactive, disabled/long-term sick Inactive, retired Inactive, other reason, no reason given

21 Key Findings: Probability of Employment Lowest employment for those entering or leaving working age inactivity particularly high for older males due to LT sickness in Wales (25% in group compared to 19% in Outer UK and 12% in LESE) Non-employment particularly high for Bangladeshi females 81% are in this category in Wales; 78% in LESE and 73% Outer UK also very high for Pakistani females (67% in Wales but lower than in LESE: 70% and Outer UK: 77%) closely linked with religion but difficult to disentangle ethnicity and religion even in regression framework People with DDA and work limiting disabilities are also highly work disadvantaged: 74% are in not in employment in Wales greater than in LESE (63%) and Outer UK (68%) but differentials do narrow in logistic regressions suggesting that education is an important determining factor for this group

22 Key Findings: Types of Employment Self-employment is very high for Pakistani and Bangladeshi males living in Wales Clusters of males and females in Wales in low paying sectors particularly for part-time workers (over 50% in these sectors) but also for 23% of full-time females (same as Outer UK but much higher than for males: 11% ) Despite rising education, a low proportion of FT female employees in Wales are higher managers or professionals 9% compared to 15% in LESE and 10% in Outer UK; also lower for males : 15% compared to 26% in LESE and 17% in Outer UK High proportion of females in Wales work in the public sector, especially for full-timers

23 Earnings in Wales Gerry Makepeace* Victoria Wass* *Cardiff Business School

24 Earnings and Earnings Inequality Measured for the 77% who are employed (relatively advantaged) Largest source of household income Key determinant of inequality elsewhere (e.g. health, well being, life expectancy and personal and household achievement) (Wilkinson & Pickett 2008) Inequality in earnings comprises earnings differences between socio-economic groups and earnings differences within these group Large increase in inequality since 1980

25 What does this chapter do? 1. Reference for statistics on earnings in Wales (and different areas of the UK) for different social groups 2. Summary of the distribution of earnings which show levels and dispersion within and between groups 3. Who is disadvantaged in Wales? 4. How much worse off are the disadvantaged in Wales? 5. How big is within-group inequality in Wales?

26 Measuring earnings Real gross hourly earnings for all employees (in 2009 prices) Real gross weekly earnings for full-time employees (in 2009 prices) Within and between groups Personal characteristics gender, age, ethnic group, religious affiliation, disability, Welsh identity and language, education and qualifications Job characteristics occupation, LPC-defined low pay group, temporary or permanent employment contract, full- or part-time employment contract, public or private sector and region

27 The Box and Whisker Plot 10 th 25 th Median 75 th 90 th Real Hourly Wages by Gender in Wales - all employees

28 Real Hourly Wages by Gender and Region

29 LESE Outer UK Wales Returns to qualifications (women) 90:10 Percentil Higher Degree Degree Other HE Qualification A Levels GCSE Other Qualifications No Qualifications Higher Degree Degree Other HE Qualification A Levels GCSE Other Qualifications No Qualifications Higher Degree Degree Other HE Qualification A Levels GCSE Other Qualifications No Qualifications Gross Hourly Earnings Females ( s)

30 Disentangling the different effects Wales LESE Outer UK Males (relative to females) +12% +13% +14% Age Lower peak Disability (rel. to non-disabled) -7% -7% -7% Non-white ethnicity (rel. to whites) 0-6% -6% Qualifications (rel. to GCSE) Degree (HE/A level) +22% (9%) +30% (10%) +27% (10%) None (low) -12% (-6%) -10% (-1%) -9% (-5%) Public sector (rel. to private) +9% -2.5% +7% Permanent job (rel. to temp) +11% +10% +8% Full-time (rel. to part time) +7% +12% +7%

31 Who are the disadvantaged groups? 1. Young 2. Unskilled and semi-skilled manual and service occupations (SOC 6, 7, 8 and 9) with some exceptions in LESE 3. No and poor qualifications 4. Bangladeshi and Pakistani ethnicity 5. Muslim religious affiliation 6. Temporary workers 7. Women plus all manual and service occupations, disabled, private sector and non-graduates outside LESE

32 Income, Poverty and Wealth Rhys Davies* Huw Lloyd-Williams** *Cardiff University **Bangor University

33 Total UK LESE Outer UK Wales Income and Poverty HBAI 2004/08 Before Housing Costs 90: Poverty (%) 17.5 After Housing Costs Before Housing Costs After Housing Costs Before Housing Costs After Housing Costs Before Housing Costs After Housing Costs Incom e

34 LESE Outer UK Wales Poverty by Family Status 90:10 Poverty (%) Pensioner - Couple Pensioner - Male Pensioner - Female Couple - Children Couple - No Children Lone Parent Single - Male Single - Female Pensioner - Couple Pensioner - Male Pensioner - Female Couple - Children Couple - No Children Lone Parent Single - Male Single - Female Pensioner - Couple Pensioner - Male Pensioner - Female Couple - Children Couple - No Children Lone Parent Single - Male Single - Female Income HBAI 2004/08

35 LESE Tenure Type Outer UK Wales Poverty by Housing Tenure HBAI 2004/08 90:10 Poverty (%) Ow ns Outright Buying w ith a Mortgage Renting Ow ns Outright Buying w ith a Mortgage Renting Ow ns Outright Buying w ith a Mortgage Renting Incom e

36 Family Status In-Work Poverty Wales Outer UK LESE UK couple - children couple - no children lone parent single male single female Tenure renting owns outright buying with a mortgage All HBAI 2004/08

37 Poverty Persistence Wales Outer GB LESE Headcount Exited poverty in Remained in poverty in Headcount Exited poverty in Remained in poverty in Headcount Exited poverty by Remained in poverty by BHPS

38 LESE Outer UK Wales Wealth by Social Class Managerial & Professional Intermediate Small Employers & Own Account Workers Lower Supervisory & Technical Semi-routine Never Worked & Long Term Unemployed Managerial & Professional Intermediate Small Employers & Own Account Workers Lower Supervisory & Technical Semi-routine Never Worked & Long Term Unemployed Managerial & Professional Intermediate Small Employers & Own Account Workers Lower Supervisory & Technical Semi-routine Never Worked & Long Term Unemployed Wealth ( 000s) 2006/08 WAS

39 Summary Approximately 1 in 5 live in poverty The groups most susceptible to living in poverty are lone parents, followed by single females Poverty is also more prevalent in Black and Asian households, households where there is a disabled person present and within the rented sector Being in work does not necessarily provide a route out of poverty - 13% of those in in-work households live in poverty The median level of wealth held by households in Wales (approximately 205,000) is comparable to that held by households across the UK as a whole There is a clear correlation between the accumulation of wealth and social class.

40 Cross Cutting Summary Caroline Joll* Alison Parken* Victoria Wass* *Cardiff University

41 What do we do in this chapter? 1. Compare inequality across different financial outcomes 2. Look at experience of disadvantaged groups across outcomes 3. Present key outcomes for groups of interest 4. Pull together key findings and policy implications

42 Inequality in financial outcomes Four outcomes: Earnings (hourly and weekly), Income (net weekly) and Wealth (of households). Inequality measured by 90:10 ratio Wealth is by far the most unequal distribution: 90:10 ratio = 90 90:10 ratio for income = 4.48, higher than for earnings Hourly earnings (90:10 = 3.5) are slightly more unequal than weekly earnings of full-time employees (90:10 = 3.4)

43 Inequality: Wales vs UK :10 ratios Wales 60 90:10 ratios UK Hourly earnings Weekly earnings Weekly income Wealth

44 Looking at disadvantaged groups in Wales across all possible outcomes Here we ask three questions: A. Which groups are disadvantaged in Wales (compared to the UK)? B. How much worse off are the disadvantaged in Wales? (compared to UK median and to a Wales reference group) C. How great is within-group inequality in Wales?

45 Which groups are disadvantaged in Wales (compared to the UK)? The most disadvantaged groups in Wales are: Bangladeshi & Pakistani; disabled; social housing occupants; youngest age-band; those with poor qualifications; workers in unskilled service sector occupations. Typically experience disadvantage across all measured outcomes Within each group women are more disadvantaged but size of gender differential is comparatively low.

46 Bangladeshi and Pakistani Disadvantage in Wales Schooling & labour Market Outcome B&P in Wales UK median % low or no qualifications (highest is GCSE) % not employed or in F/T education % hourly earnings less than 2/3 rd UK median % weekly earnings less than 2/3 rd UK median % poverty (household net income below 60% UK median includes all Asian households) 44 21

47 Gender top-ups in Wales Disadvantage % total % women Gender top up low or no qualifications (highest is GCSE) at age not employed or in F/T education and DDA and WL disabled hourly earnings less than 2/3 rd UK median and disabled weekly earnings less than 2/3 rd for Wales UK median aggregate weekly earnings less than 2/3 rd UK median aggregate for Wales and house owned with a mortgage hourly earnings less than 2/3 rd UK median and Black African and Caribbean ethnicity

48 How much worse off are the disadvantaged in Wales? We measure the earnings/income penalty by comparing group median earnings/income to the UK median levels These groups have median earnings and/or income below 2/3 rd UK median: Bangladeshi & Pakistani, social housing, young (under 24), no and poor qualifications, unskilled service sector and elementary occupations Bangladeshi & Pakistani in Wales: hourly earnings 66% of UK median; weekly earnings 58% of UK median

49 How great is within-group inequality in Wales? A high level of inequality of income (or earnings) within groups indicates that some group members are much better off than others, so the difference between group median income levels is relatively unimportant in accounting for inequality overall. In general, the level of inequality within groups is only slightly lower than inequality across the whole population. But some groups (e.g. social tenants) exhibit low withingroup inequality in these cases almost all group members have low incomes/earnings so group membership strongly indicates disadvantage.

50 An Anatomy of Economic Inequality in Wales A report prepared on behalf of the Wales Equality and Human Rights Commission Thank you