Statistical Requirements for Poverty Monitoring in Pakistan

1. Statistical Requirements for Poverty Monitoring in Pakistan Tara Vishwanath Ambar Narayan (World Bank) Workshop in Dubai – Towards a Monitoring Framework for the Full PRSP for Pakistan, August 5-7, 2002

2. Ensuring Compatibility Across Statistical Databases in Pakistan • Pakistan’s statistical base • Multiple data sources: Population Census, Agricultural Census, Census of Private Schools, PIHS, Labor force survey • Issues of compatibility across databases • Using most recent census information for sample design of household surveys • Using census information to extrapolate from household survey findings • Potential benefits of compatibility • Poverty map exercise • Poverty monitoring • Establishing a school database of private and public schools

3. Poverty Map for Pakistan • Poverty maps are spatial descriptions of the distribution of poverty in a country • Most useful when they represent small geographic units for use by policymakers for targeting public investments or poverty programs • Household surveys – not representative at such fine levels of disaggregation; census data – lack poverty information • Solution: combine sample survey data with census data to predict consumption poverty indicators using all households in the census • Statistical underpinnings of the methodology make such maps more credible than the more commonly found maps based on ad-hoc methods • Methodology developed in the Bank have now been piloted in several countries, e.g. Ecuador, South Africa, and Nicaragua • For Pakistan – important for Census and PIHS to be compatible • E.g. sampling frame of PIHS must be based on the latest census information

4. GIS School Database • Already immense GIS progress in Pakistan (NADRA): Next Step: GIS School Database? • Why a GIS School Database? • What school choices does a child have? • Private/Public/NGO • In village: Merge data from Census/Private School Census/EMIS • BUT • Schools may be close to village: NO INFORMATION CURRENTLY AVAILABLE • Educational Policy: Upgrading schools, school construction, school improvement • GIS will provide village catchment areas for each village

5. Example: School Catchments in Zambia • Polygon around each dot is the area closest to X school • BUT: no information on villages • PAKISTAN: Both information on villages and schools

6. GIS: A reality? • Problems • Compatibility • Different Administrative categories across data sets (Census: Land-based; EMIS: Political Units that change with time) • No centralized consistent village list • Where are the Current Users? • Difficult to use school data below district-wide aggregates • Large amounts of data collected: but poor use of available information • GIS • Very user-friendly database: information on all villages and schools • Leads to consistent demand for new and updated information • Improves monitoring and efficiency

7. Poverty Monitoring • Monitoring important in the context of MDGs • Developing baselines; setting targets • For measuring long-term impacts, PIHS is primary source • Certain issues regarding improvement of PIHS important to consider • Intermediate indicators: Monitor indicators that show changes over shorter time horizon • Proposed CWIQ-style rotating module should be able to track such indicators

8. Why a Monitoring Tool Like CWIQ(Core Welfare Indicators Questionnaire) ? • Urgent need for district level data • To inform provincial planners’ decisions to allocate resources to districts • To monitor the I-PRSP targets • Various sources of information need to be tapped • Not just administrative systems, but information directly from households, communities and facilities • Why information from households in addition to administrative records (e.g. MIS)? • Tells us how key indicators vary across household characteristics: useful for targeting or policy planning • Check reliability of administrative data

9. What is CWIQ ? • Primarily a household survey used to monitor outcomes of development outcomes (such as PRSPs)……. • …… through the use of leading indicators, such as access, use and satisfaction • Simple, small set of indicators monitored regularly • Indicators are “signals” for broad-based impact of development programs • CWIQ also helps strengthen the capacity of countries to use such indicators to design and monitor programs and projects more efficiently

10. Innovative Features in CWIQ • Standardized, mostly pre-packaged questionnaire and analytical tools • Large sample size • Data can be representative at district level • Simple and thin questionnaire • With multiple choice questions for easy and rapid data collection • Quick data entry, validation and result reporting • The use of machine-readable questionnaires and optical scanners • Pre-programmed validation procedures to ensure high built-in data quality levels • “Push-button” standardized outputs to provide quick feedback to policy-makers

11. A Typical CWIQ Survey • Typical CWIQ questionnaire for African countries • Basic household roster; education; health; household assets; household amenities; child characteristics • Not more than a page for each module • Includes questions on satisfaction with public services, e.g. schools, health centers • Sample CWIQ outputs – Ghana • School enrollment ratios by public/private, rural/urban, regions • Reasons for not attending schools • Reasons for not satisfied with school/health services • Access to school/health facilities • Flexible modules • E.g. gender module (Nigeria); community CWIQ (Tanzania)

12. Typical Timeline for CWIQs Implemented So Far • 1-month pilot survey: small sample of ~1000 households • Evaluation workshop, involving data users and suppliers, to assess pilot experience • Period of around 6 months to prepare for final survey • Full national survey taking 3 months • Implemented with close technical support and training from donors • Preliminary results available within a few weeks • National seminar to discuss survey results • Second round to be carried out 1 year after the first • the National Statistical Organization expected to implement fully, using institutional capacity developed during previous round, with necessary technical support from donors

13. Specific Recommendations for CWIQ-style Survey in Pakistan • Household survey should focus on key indicators related to service delivery & poverty programs • District level representation • Survey of schooling and health facilities to complement the household survey • Coordination with PIHS • Integrate with the PIHS time cycle • Combine key questions from CWIQ, MICS and PIHS

14. Integrating CWIQ into the Survey Framework • PIHS has the important role of measuring a large set of indicators that show changes in the long-term • CWIQ will monitor a set of key indicators that will reflect more short-term changes • One possible way to integrate • Conduct PIHS on a 3-year cycle • Conduct CWIQ every year • Align the 2 surveys such that PIHS and CWIQ data can be combined to generate a yearly time-series for a small set of key indicators • Most importantly, such issues need detailed discussion to arrive at a consensus

15. Policy-Related Benefits from District Level Data • Improving geographic targeting of poverty programs • E.g. Khushal Pakistan; Food Support program • Facilitating fiscal transfers from the national/provincial govt. to the district level • Inducing competition among districts for federal and provincial funds

16. Challenges • Institutions and capacity building • Imperative to ensure that the survey is institutionalized, and becomes a part of the regular statistical monitoring process • Ensuring data flow from the bottom up to the national decision-making process • Linking policy decisions and budget allocation with feedback from monitoring