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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. ASPIRE: Harmonized data on Social Protection and Labor. Motivation and background.

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ASPIRE: Harmonized data on Social Protection and Labor

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  1. MaddalenaHonorati and RuslanYemtsov (Social Protection, World Bank) Joint World Bank-LIS workshop on database creation and survey harmonization Washington, June 6, 2013 ASPIRE: Harmonized data on Social Protection and Labor

  2. 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.

  3. Objectives • Create a comprehensive, standardized and up-to-date database of SPL indicators on program design, performance and “environment” across countries and time • 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 • Contribute to improve the quality/availability of survey data on SP • Monitor the implementation of the new WB 2012-22 SPL Strategy

  4. ASPIRE components • Data collection, harmonization and validation • “Environment” indicators • Program/system indicators of design and performance • Tools for data analysis (ADePT SP) • Training in tools (Bank and non-Bank clients) • Analytical notes and reports • External partnership and internal collaboration • Dissemination

  5. ASPIRE classification of programs

  6. ASPIRE framework

  7. ASPIRE data sources Primary sources: national • Administrative: published or regional/other databases • Nationally representative household surveys data (AdePT SP) • LSMS • HH budget surveys • Other surveys (program participation, etc.) • I2D2 Secondary sources: international organizations OECD, 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)

  8. ASPIRE data coverage

  9. Administrative data on SA and LM programs 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: • 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

  10. www.worldbank.org/aspire

  11. ASPIRE: HH surveys pillar Percent covered by Main Types Social Protection Programs by Regions (Percent of population receiving transfers from social protection program) • Questionnaires • SP program classifications • ADePT SP ini files • Database • Country-specific outcomes • Metadata • Cross-country figures and tables

  12. 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

  13. ASPIRE SURVEY Database: LAC • Most recent household survey data available at CEDLAS (Centro de Estudios Distributivos Laborales y Sociales) withinformationonhouseholdincome and social protectionprograms • Argentina 2006 • Bolivia 2006, 7 • Brazil2006, 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 • Mexico2008, 10 • Nicaragua 2005 • Panama 2008 • Paraguay 2007, 9 • Peru2008, 9 • Suriname 1999 • Uruguay 2008 • Venezuela 2006 • ….More: • Belize+updates

  14. 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 • Armenia 2008 • Azerbaijan 2007 • Belarus 2008 • Bosnia 2007 • Bulgaria 2007 • Georgia 2007 • Estonia 2004x • Hungary 2004 • Kasakhstan2007 • Kosovo 2006 • Kyrgyzstan 2006 • Latvia 2008 • Lithuania 2004 • Macedonia 2005 • Montenegro 2008x • Poland2005 • Romania 2008 • Russia 2008 • Serbia 2007 • Turkey 2008x • Ukraine2006 • More to come…. • Tajikistan • Albania • Moldova • Croatia • +updates

  15. ASPIRE SURVEY Database: AFRICA, SAR, MENA, EAP • Most recent household survey data available collected from AFR, MENA, EAP and SAS withinformationonhouseholdincome and social protectionprograms • AFR • Cote d’Ivoire 2002x • Ghana 2005 • Kenya 2005 • Malawi 2005 • Mauritius 2005 • Mozambique 2002x • More: Nigeria, Rwanda, Uganda, Zambia, Tanzania, Mali+ updates • MENA • Egypt2008(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…

  16. Structure

  17. 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

  18. THANK YOU!

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