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ASPIRE: Harmonized data on Social Protection and Labor

Maddalena Honorati and Ruslan Yemtsov (Social Protection, World Bank)

Joint World Bank-LIS workshop on database creation and survey harmonization

Washington, June 6, 2013

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Motivation and background

• Lack of comprehensive and systematic data collection tools on SP programs and systems in developing world (especially LICs)

• Optimize and capitalize on existing data collection efforts by the WB regional teams – data collected/compiled in a decentralized way and in

different format making comparisons difficult• Increasing demand from policymakers, civil society,

World Bank staff and other international stakeholders to access SPL data.

Objectives

1. Create a comprehensive, standardized and up-to-date database of SPL indicators on program design, performance and “environment” across countries and time

2. Need to build empirical evidence for SP systems and their components

– Focus also on program complementarities in addressing risks, overlaps…

– Develop common matrix for assessing performance of SP and monitor over time

3. Contribute to improve the quality/availability of survey data on SP

4. Monitor the implementation of the new WB 2012-22 SPL Strategy

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ASPIRE components

1. Data collection, harmonization and validation– “Environment” indicators– Program/system indicators of design and performance

2. Tools for data analysis (ADePT SP)3. Training in tools (Bank and non-Bank clients)4. Analytical notes and reports5. External partnership and internal collaboration6. Dissemination

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ASPIRE classification of programs

• Social assistance (Social Safety Nets)SA

• Labor Market Programs (active and passive) LM

• Social InsuranceSI

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ASPIRE framework

Indicator type SA LM SIENVIRONMENT HC and poverty gap,

% of children economically active

Primary activity rates, employment status, share of employment in main sectors

Life expectancy, old age dependency ratio, co-residence rate, poverty rates of old population

DESIGN Benefit modality (in kind, cash), eligibility criteria, targeting method, benefit formula

Ratio of front-line counselors to total PES staff, number of registered vacancies

Modalities of pension schemes, contribution rates, qualifying condition, defined benefit parameters

PERFORMANCE Coverage, benefit and beneficiary incidence, adequacy, simulated impacts on poverty and inequality, spending

Coverage, benefit and beneficiary incidence, adequacy, simulated impacts on poverty and inequality, spending, activation of registered unemployed (placement in jobs)

Coverage (recipients and contributors), benefit and beneficiary incidence, adequacy, simulated impacts , pension spending, administrative efficiency

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ASPIRE data sources

Primary sources: national1. Administrative: published or regional/other databases2. Nationally representative household surveys data (AdePT SP)

LSMS HH budget surveys Other surveys (program participation, etc.) I2D2

Secondary sources: international organizationsOECD, IMF, ILO , ISSA , Helpage, WHO, UN, UCW

SI coverage indicators are 65% based on primary administrative sources in the country, and 25% on ILO statistics.

World Bank country-level SP system assessments, targeting assessment reports, regional databases (SPEED in ECA)Regulations and laws (for design indicators)

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ASPIRE data coverage

SURVEY BASED INDICATORS ADMIN. BASED INDICATORS

N. of countries

Aggregation Level

N. of countries Aggregation Level

Environment 150 Country 160 Country

Design Private transfers/NGOs- run SSN (60 developing countries)

Program LM indicators only for ECA countries,SI for ~ 165 countriesSA for 65: Africa (20), ECA (23), LAC(10), MENA(12).

Country, program

Performance 60 developing countries

Program, Country

SI for ~ 165 countriesSA for 65: Africa (20), ECA (21), LAC((8), MENA(12).

Country, Program

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Administrative data on SA and LM programs

• Program design/description– Program objective– Eligibility criteria– Targeting mechanism– Payment type– Benefit amount/indexation– Frequency of payment– Source and structure of financing– Implementing agency– Year in which the program

started

• Program performance– Total expenditure/GDP– Number of

beneficiaries/population

Regional existing efforts to collect program-level comparable data (ECA (23), LAC (10), Africa (20), MENA (8) + 35 countries in EAP and SAR by ADB SPI) on focus on the following indicators:

www.worldbank.org/aspire

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ASPIRE: HH surveys pillar

• Questionnaires• SP program

classifications• ADePT SP ini files• Database• Country-specific

outcomes• Metadata• Cross-country figures

and tables

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76 7467

6053

37

59

7 67

916

29

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16 1722

18 2220

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2 3 413 9 15

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Africa Middle East &North Africa

South Asia East Asia andPacific

Latin America& Caribbean

Europe &Central Asia

World

No transfer Social Insurance Social Safety Nets Combination of programs (incl. labor market prog.)

PERCENT COVERED BY MAIN TYPES SOCIAL PROTECTION PROGRAMS BY REGIONS (Percent of population receiving transfers from social protection program)

ASPIRE SURVEY Database : What else is inside?

• Country-specific standard tables on coverage (direct and indirect), adequacy, and benefit incidence analysis – By quintiles of welfare, with counterfactuals – pre-transfer; BWR variations);

Using household income/consumption per capita as welfare– By program– Using relative poverty line (20% percentile)– Using absolute poverty line ($1.25 in PPP)- NEW

• Impact of SP transfers on FGT (0, 1, 2) and inequality (Gini); cost-benefit ratios– By program

• Country-specific data base in STATA with harmonized SP programs and welfare variables; ADePT routines

• Full documentation of main variables/peculiarities of data• Decomposition of SP impact into budget adequacy/efficiency: PLANNED• Metadata with administrative statistics; facility to make imputations following

program rules (with ADePT SP): PLANNED 12

ASPIRE SURVEY Database: LAC

• Most recent household survey data available at CEDLAS (Centro de Estudios Distributivos Laborales y Sociales) with information on household income and social protection programs

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Argentina 2006 Bolivia 2006, 7 Brazil 2006, 9 Chile 2006,9 Colombia 2003 Costa Rica 2008,9 Rep Dominicana

2007,9 Ecuador 2008,9 El Salvador 2007,10

Guatemala 2006 Honduras 2007 Jamaica 2006 Mexico 2008, 10 Nicaragua 2005 Panama 2008 Paraguay 2007, 9 Peru 2008, 9 Suriname 1999

Uruguay 2008 Venezuela 2006 ….More: Belize+updates

ASPIRE SURVEY Database: ECA

• Most recent household survey data available at ECA data bases (SPEED and ECAPOV) with information on household income and social protection programs

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Armenia 2008 Azerbaijan 2007 Belarus 2008 Bosnia 2007 Bulgaria 2007 Georgia 2007 Estonia 2004x

Hungary 2004 Kasakhstan 2007 Kosovo 2006

Kyrgyzstan 2006 Latvia 2008 Lithuania 2004 Macedonia 2005 Montenegro 2008x

Poland 2005 Romania 2008 Russia 2008 Serbia 2007 Turkey 2008x

Ukraine 2006

More to come…. Tajikistan Albania Moldova Croatia +updates

ASPIRE SURVEY Database: AFRICA, SAR, MENA, EAP

• Most recent household survey data available collected from AFR, MENA, EAP and SAS with information on household income and social protection programs

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AFR Cote d’Ivoire 2002x Ghana 2005 Kenya 2005 Malawi 2005 Mauritius 2005 Mozambique 2002x More: Nigeria,

Rwanda, Uganda, Zambia, Tanzania, Mali+ updates

MENA Egypt 2008(sub) Jordan 2003 Morocco 2001 Yemen 2005x

West Bank 2007 More: Iraq, Djibouti,

updates EAP

Cambodia, 2008 Lao, 2008 Malaysia,2008 Mongolia, 2007

Phillippines 2006 Thailand, 2009 Timor Leste 2007 Vietnam 2002 ……+Updates

SAS Afghanistan, 2007 Bangladesh 2002,6 India 2005 Pakistan 2005, 8 Sri Lanka 2008…

Structure

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Challenges• Expanding (this year +10 countries, and 25 updates, next

year?)– New data collection : coordination– I2D2– China?– HIC?

• Classification/ Harmonization• Deflation/ scale economies/equivalence• Counterfactual (pre-, post- transfer, in between)• Quality checks on SP/ Imputations• Developing good instrument(s) for SP data collection• User-friendly / target different audiences 17

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THANK YOU!