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The importance of quality research practice

The importance of quality research practice. UNICEF as a Data Driven Organization. Data is a basis for: Global and regional reports on the state of children Program planning, monitoring and reporting Inputs for policy-making Inputs for equity-focused strategies

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The importance of quality research practice

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  1. The importance of quality research practice

  2. UNICEF as a Data Driven Organization • Data is a basis for: • Global and regional reports on the state of children • Program planning, monitoring and reporting • Inputs for policy-making • Inputs for equity-focused strategies • Analysis and studies to inform policy implementation • Objective monitoring and validation of results

  3. Applying Principles in Practice • To promote use of quality data • To facilitate access to reliable, regular and disaggregated data for planning, monitoring and reporting • How does UNICEF do it • 1) Through primary data collection • 2) Through analysis of primary and secondary data • 3) Through strengthening administrative data systems and data management

  4. 1) Primary Data Collection • Regular surveys • Global Multiple-Indicator Cluster Survey – MICS (every 5 years) • Ad- hoc surveys- to close the gap in knowledge • School optimization • Salt iodization • Costing of Inclusive Education • Child Care Reform

  5. MICS • Global household survey in over 100 countries - 4 rounds to date • Approximately 130 indicators • In Serbia: • MICS 4 conducted by SORS in 2010 (+Roma sample) • Questionnaires customized to local needs • Key source of disaggregated data (regions, urban/rural, gender, education, age, wealth, ethnicity) • Rigorous quality assurance – global methodology • All MICS materials, including data sets are publicly available

  6. 2) Analysis of primary and secondary data sources • The Many Faces of Poverty (LSMS) • The State of Children in Serbia- Poor and Excluded Children (LSMS and MICS) • Access to Services in Rural Area (LSMS, MICS, Social Inclusion in Rural Areas) • Impact of the potential tax reform on the poorest (LSMS) • Costing of Pre-school Education (Budget Data) • Targeting of Child Allowances (LSMS)

  7. 3) Strengthening Administrative Data • Key Issues: • Collected data not adequate for monitoring policies and measures (type & disaggregation) • Lack of regular revisiting and revision of administrative data collection by data users and producers • Inconsistencies in the same type of data coming from different sources • Insufficient transfer of data from providers to users in user-friendly formats

  8. 3) Strengthening Administrative Data • Examples of UNICEF support: • Social Protection • - Defining of core and secondary social protection indicators • Revision of data collection instruments in the area of social protection • Capacity building for data analysis • Transfer systems between ISP and SORS • b) Roma health • Strengthening data base on Roma health indicators • Advancing data entry and processing techniques

  9. 3) Strengthening Administrative Data • Support to data availability: • a) DevInfo (DI) database • - Administered by RSO from 2006 • National DI - under revision to support reporting as per national MDGs and Social Inclusion and Poverty Reduction indicators • Municipal DI – available administrative and survey data customized in user-friendly Municipal Profiles • b) TransMonee database • Regional administrative data on social protection, employment, education indicators, current harmonization with ESPROSS requirements

  10. Example of DevInfo Municipal Profile PBILD Zajednički programUN, UN Kancelarija u Bujanovcu Karađorđa Petrovića bb, 17520 Bujanovac, Srbijа

  11. Cooperation with SORS • SORS as a long term and reliable partner • Cooperation on DevInfo, TransMonee, MICS • Mutual learning and capacity development • Facilitation in establishing institutionalized data exchange procedures • Possible areas of future attention: • Resolving discrepancies in administrative data collected from different sources • Creating a more dynamic cooperation between line ministries and SORS • Strengthening capacity for data usage and availability of data at municipal level

  12. Cooperation with decision-makers & research community • Partnership with decision-makers • Aim is to promote and support evidence-based policy making • Wide dissemination of and policy advocacy based on quality research (MICS 4, studies…) • Independent institutions (Parliament, Ombudsman) • Partnership with the research community • NGOs • Think-tanks • Universities

  13. Thoughts for further discussion… • Availability of high quality data sets • Pre-conditions for continuous monitoring of policy implementation • Availability of analytical capacity • Effective cooperation between SORS, ministries, NGOs and think-tanks in the area of research

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