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Potential of EU-wide research in tackling key societal challenges of EU countries

08 July 2014

Isabelle Engsted-MaquetDG Employment, Social affairs and Inclusion

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How can EU-wide comparative research support a job rich and inclusive growth?

1. Debunking myths and bringing new ideas2. Increasing visibility accountability 3. Bringing social monitoring to a par with

macro-economic monitoring4. Improving the diagnosis and identifying

the policies that work5. How can research help?

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1.a Debunking myths

What we may think (largely based on theory)…

(Empirical) research shows that

"Inequality is inevitable or even good for growth"

"Too high inequalities may undermine growth"

"Focus on growth and jobs…" "There is no trickle down…"

"Generous benefits discourage people from working" (making work pay)

"higher coverage and adequacy of benefits are associated with higher returns to employment… if well designed and linked to activation"

"More targeted benefits means more efficient spending…"

"Efficiency of spending depends on how you spend it and on what" (social investment)

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1.b New ideas: after decades of rising inequality the policy debate took off recently

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2. Robust Indicators: accountability

• "What is not counted doesn't count"• Agreeing on concepts and measures and the need for

comparable statistics• Monitoring

Three examples:• Europe 2020 target on poverty• EMU scoreboard of employment and social

imbalances• Poverty mapping and small area estimation• Vulnerable groups (homeless, vulnerable children)

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124 million Europeans living at risk of poverty or social exclusion 25% in 2012

At risk of poverty

85 Mio

Severely materially deprived

50 Mio

Jobless households

38 Mio

At Risk of Poverty Severe Material Deprivation Jobless Households

* People at risk of poverty or social exclusion are at least in one of the following three conditions: at-risk-of-poverty, severely material deprivation or living in a jobless household.

19%

Latvia Risk of poverty or

Social exclusion 40%

Italy Risk of poverty or

Social exclusion 28%

Ireland Risk of poverty or

Social exclusion 30%

Deprivationprevails

Relative povertyprevails

Benefit dependencyissues

31%

13%

20%

11%

10%

16%

23%

8%

EU-28

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ETHOS classification to measure homelessness

Housing situations

Roofless 1. Living rough

2. In emergency accomodation

Houseless 3. In accomodation for the homeless

4. In women's shelters

…

Insecure 8. Insecure accomodation

9. Risk of eviction

…

Inadequate 11. Temporary or unconventional accomodation

12. Unfit accomodation

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3.4 - 19.119.1 - 21.421.4 - 28.228.2 - 32.4

(% of total population below 60% of median income per a.e.)At-risk-of-poverty rate, 2011 (direct estimates)

0.0 - 17.417.4 - 25.125.1 - 27.927.9 - 31.431.4 - 49.6

(% of total population below 60% of median income per a.e.)Romania: At-risk-of-poverty rate, 2011

Poverty mapping: SILC vs. Small Area Estimation

Romania: estimating poverty at the local level to improve the targetting of EU funds

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3. Bringing social monitoring to a par with macro-economic monitoring

• Timeliness of social indicators• Social impacts of economic developments and policies• Economic impacts of social developments and policies

Two examples:• Nowcatsing poverty and inequality measures• Social EMU

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Micro-simulation: Nowcasting at-risk of poverty to 2014

Nowcast estimates of at risk of poverty rates, selected Member States, 2011-13•RED: Eurostat BLUE: Euromod nowcasts

Source: Euromod – Employment and Social Situation Quarterly Review – March 2014

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3b. Social EMU

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Social EMU Communication (2/10/2013)

Improve governance to anticipate & address serious employment & social problems in the EMU, taking account of

• Social impacts of economic developments and policies (in macro-economic imbalance procedure: MIP scoreboard now

includes poverty indicators)

• Spill overs of serious social problems, also beyond borders In European Semester: the scoreboard (UR, NEETs, GHDI,

AROP, S80/S20)

EU level instruments Better use of EU Funds, Labour mobility, Steps towards a "fiscal capacity"

for more solidarity and financial support… (EMU-UBS?)

Involvement of social partners in EMU governance

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Growth, employment and household income

Source: Eurostat, National Accounts in Employment and Social Situation Quarterly Review – March 2014

• - Gradual economic recovery

• - GDP, employment and household incomes together on the rise first time since 2011

Real growth in GDP, GDHI and employment growth (y-on-y), EU28

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Gross household income started declining, automatic stabilisation only in the early phase of crisis

Source: Eurostat and ECB in Employment and Social Situation Quarterly Review – March 2014

Market incomes (from work and capital)

Benefits and taxes

GHDI growth

Real change in Gross Disposable Household Income by component in the Euro area (year on year; 2000 – 2013)

GDP growth

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Real growth in GHDI – by components

• Germany • Spain

Source: Eurostat and ECB in Employment and Social Situation Quarterly Review – March 2014

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Micro-simulation: impact of fiscal consolidation on household incomes

Contribution of different austerity measures to change in households incomes, overall (below) and at different points of the income distribution in selected Member States (right)

Source: EUROMOD (cumulated impact of austerity measures on households disposable incomes). In Employment and Social Situation Quarterly Review – March 2014

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Economic impacts of social problems• Unemployment, poverty and inequality undermine growth

in the short to long term by• Lower consumption (aggravated by deleveraging need) depresses

aggregate demand• Under-utilisation and erosion of human capital affects productivity

and competitiveness• Political and confidence effects

• Across borders• Through trade• "Contamination"

Undermine the legitimacy of the European project (Vandenbroucke) and capacity of governments to run the necessary reforms to strengthen EU

Undermine confidence and investmentSource: Employment and Social Developments in Europe 2013

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4. Improving the diagnosis and identifying policies that work

EXAMPLE OF ISSUES• Helping people back to work and escaping poverty• Child poverty: assessing the effectiveness and efficiency of

social transfers

MAIN ANALYTICAL TOOLS

• Comparative analysis based on macro indicators• Longitudinal analysis: analysing transitions • Models (micro-simulation, typical cases) help assessing the

theoretical performance of systems• Counterfactual evaluation methods

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4a. What helps people back to work and escape poverty?

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Taking up a job helps to get out of poverty… only in half of the cases

Source: EU SILC, DG EMPL calculations Transitions 2008-2009 in Employment and Social Developments in Europe 2013

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Unemployment benefits: better coverage & adequacy associated to higher returns to work

Coverage AdequacySource: Employment and Social Developments in Europe 2013

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Unemployment Benefit recipients have greater chances to be working the year after, (propensity score matching)

Source: Employment and Social Developments in Europe 2013

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Country Specific Recommendations 2014

ItalyCSR 5"Work towards a comprehensive social protection for the unemployed, […]. Strengthen the link between active and passive labour market policies. […] scale-up the pilot social assistance scheme, […] and strengthen the link with activation measures"

LithuaniaCSR 3"Improve coverage and adequacy of unemployment benefits and link them to activation."CSR 4"Ensure adequate coverage of those most in need and continue to strengthen the links between cash social assistance and activation measures."

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Counterfactual impact evaluation in Lithuania

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4b. Child poverty, effective and efficient social spending

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What drives child poverty?

-25.4 million children at risk of poverty or social exclusion

-Greater risk than adults

-Main drivers: o- in-work poverty of parents-- insufficient LM participation of parents-- ineffective benefits

Profiles of child poverty drivers

Source: ESSPROSS 2009, EU-SILC 2010, DG EMPL calculations. In ESSQR – June 2012

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Assessing the efficiency of social spending: one dimensional approach

Source: Employment and Social Developments in Europe 2012

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Family benefits: An example of a broadened approach of effectiveness and efficiency

Source: Employment and Social Developments in Europe 2013

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Micro-simulation: policy swapping on family support

Applying policy rules of 4 countries to Lithuania; design effects matter as much as size effects.

Family Benefits & Tax Advantages from EE, HU, SI or CZ applied to Lithuania

Source: Salanauskaitė L. and Verbist G.; Euromod working paper series Dec.2011

EE HU SI CZ

Total 20.3 20.3 19.6 18.9 19.6

Children 26.2 26.8 24.4 23.0 25.4

Large families (3+) 44.3 42.6 34.4 31.1 45.0

Lone parent 45.1 49.8 45.3 45.2 44.7

Budget neutralLT baseline

Risk of poverty headcounts (%)

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4. What do we need?

• Robust and more timely statistics• Comparable indicators based on common definitions• Monitoring framework and policy models• Reporting and visualisation tools• Link to macro-economic monitoring

• Nowcasting• Distributional impacts of economic developments and policies• Better document economic impacts of social developments

and policies

• Methods and models to assess the effectiveness of policies (micro-simulation, evaluation methods, etc… )

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3 Main productshttp://ec.europa.eu/social/main.jsp?langId=en&catId=113

ESDE: Employment and Social Developments in Europe (Annual Review)

Content: Key features + Thematics chapters

ESSQR: Employment and Social Situation Quarterly Review

Content: Recent trends + Special focuses

Working papers

Methodological papers (e.g. Social expenditure in the crisis, timely monitoring of social trends, etc )

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ANNEX: IMPROVING STATISTICS & ANNEX: IMPROVING STATISTICS & MODELSMODELS

TimelinessTimelinessSILC and other sourcesSILC and other sourcesData on social protection systemsData on social protection systemsModelling (Euromod)Modelling (Euromod)

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Statistical Priorities and modelling (1)

Improving timeliness• Improving SILC delivery, especially for material deprivation• Adding auxiliary data in LFS (monthly income)• Use models to produce nowcasts• Use alternative sources: e.g. consumer surveys (financial distress

indicator)

Upcoming SILC revision (with European Statistical systems)• Improving the measurement of material deprivation,• Improving the longitudinal component of SILC to better analyse the

dynamics of poverty and exclusion • Improve data on access to services to better measure the redistributive

impact of in-kind benefits• Better documentation of indicators

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Statistical Priorities and modelling (2)

Data on social protection systems•ESSPROS: Good identification of in-kind benefits, means-tested benefits, net expenditure•Data on benefit recipients (Coverage rates, Take-up rates, Characteristics of the beneficiaries)

Alternative sources•Special data collection efforts « extreme » poverty (homelessness, Roma): Poverty maps and Roma with World Bank and FRA

Modelling•Euromod microsimulation to illustrate impact of reforms on poverty, budgets, labour market incentives or economic stabilisation•OECD/EC tax benefit model•Small area estimation•Evaluation methods