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How data can inform policy? Some examples…. 1. Data from public budgets Public expenditures and revenues are telling a lot about policy (and government.

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Presentation on theme: "How data can inform policy? Some examples…. 1. Data from public budgets Public expenditures and revenues are telling a lot about policy (and government."— Presentation transcript:

1 How data can inform policy? Some examples…

2 1. Data from public budgets Public expenditures and revenues are telling a lot about policy (and government efficiency) –Accountability –Budget transparency –Allocative efficiency

3 Line-item vs. programme budget Ministry of Health Line-item BudgetProgramme Budget Salaries & wages6 000General Administration 462 Overtime150 Building expenses800Primary health care & health promotion Transport750 Equipment400 Shipping125Hospital services2 817 Water & lights15 Telephone25Training & medical research 692 Printing20 Consumables12 TOTAL8 297TOTAL8 297

4 Public Financial Management Fiscal Discipline (govt budget balance) Operational efficiency (implementation) Allocative Efficiency (public expenditure planning) Tax & aid policy (revenue planning)

5 Three basic objectives of PFM Fundamentals not strong enough AGGREGATE FISCAL DISCIPLINE –Keeping spending within limits created by the ability to raise revenue and keeping debt within levels that are not too expensive to service Allocation of current spending not sufficiently targeting poverty- reducing programmes ALLOCATIVE EFFICENCY –Expenditure should be allocated according to strategic priorities between and within sectors Plans and budgets dont always result in actual service delivery OPERATIONAL EFFICIENCY –Efficient and effective use of resources in achieving objectives and targets

6 Questions to ask about PFM objectives Allocative efficiency Is the allocation of resources sufficiently focused on childrens rights (both across sectors and within sectors)? Are poor children being put first in the areas of health, welfare, education and justice? Operational efficiency Are spending agencies using their resources effectively to achieve the outputs of programmes aimed at improving the lives of children?

7 Stages of the budget cycle Formulation Performance evaluation Analysis Tracking

8 Strategies: different options Formulation Contributing to strategy and planning Making policy recommendations Engaging directly with government Analysis Review of budget documents Analysing budgets Advocating for change Analysing spending: VFM and procurement Tracking Analysing the extent to which funding reaches delivery units Analysing expenditures compared to allocations Performance evaluation

9 2. Data from Household Surveys Descriptive statistics – together they can be powerful –Focus on the big picture of issues and policy responsiveness –Can be used for highlighting vicious and virtuous policy cycles (multidimensional model of child poverty) Exploring causality with multivariate statistics –What is the role of certain factors (e.g. parental education) in child outcomes –Why certain policies work or do not work

10 Percentage of children experiencing severe deprivations in East Asia Source: MICS/direct communication with Bristol University

11 Prevalence rates (%) and patterns of severe deprivation of basic human needs among children in Cambodia and Thailand


13 Income Poverty Dynamics Income poverty dynamics in the Maldives, 1997, 2004 and 2005 Source: Dr. Fuwad Thowfeek, Statistics Maldives

14 Jamaica panel data : Significant movements in and out of poverty despite overall low level; need to understand both processes Source: Ashu Handa UNICEF ESARO

15 Intergenerational income mobility: your father earns 100 per cent more than mine - what per cent impact will that alone have on our earning differences? Source: Dr Miles Corak Statistics Canada

16 MATERIALLY POOR POOR HEALTH OUTCOME NOT ATTEDING PRE- SCHOOL 20.2%17.9% 1.3% 11.8% 15.8% are not poor, have access to preschool, clean water and are in good health 2.9% 22.7% 7.3% Albania: % of children 3-5 yrs old materially poor with poor nutritional outcomes and not attending pre-school Albania: % of children 3-5 yrs old materially poor with poor nutritional outcomes and not attending pre-school – Venn diagrams Source: 2002 LSMS. Note: Total number of children 450. Angela Baschieri and Jane Falkingham (University of Southampton) Multidimensional child poverty concepts broaden policy focus

17 Anthropometric failure and breastfeeding practices in Tajikistan Source: MICS 2005 and Baschieri and Falkingham, 2007 Nutritional status by breastfeeding pattern for children less than 18 months

18 Anthropometric failure for moderate and severe levels for children <5 Moderate anthropometric failure Severe anthropometric failure GroupsNumber of children % of children Number of children % of children No failure Wasted only, WH Wasted & Underweight, WH, WA Wasted, Stunted & Underweight, WH, WA, HA Stunted & Underweight, HA, WA Stunted Only Underweight only Baschieri and Falkingham, 2007 TAJIKISTAN – Anthropometric Failure

19 Breastfeeding practices Most women in Tajikistan stop exclusively breastfeeding and switch to a mix feeding pattern relatively early –Amongst children aged 6-23 months under 5 percent are either exclusively or almost exclusively breastfed. As a result many children are exposed to the risk of poor nutrition and associated adverse developmental consequences.

20 Is family land ownership an effective policy against child malnutrition? (results of multivariate analysis) We control for children age (months), region, mother education, wealth quintile, ethnicity, sanitation, household access to land, ownership of livestock We found that children living in a households with access to land have higher probability of being underweight that those without access to land

21 INDIVIDUAL LEVEL VARIABLES CONTEXTUAL VARIABLES Availability/accessibility of services Quality of schooling Opportunity cost School Attendance Parental education Child age Gender Place of residence Socio-economic characteristics of the family Economic development of communities School enrolment in Tajikistan SCHOOL ENROLMENT IN TAJIKISTAN

22 GIS technique 10 Km radius Road with in 10 Km buffer Buffer of 10 Km radius Road outside the buffer PSU 10 Km radius

23 Data 2003 TLSS Community Questionnaire 2003 LandSat Image representingland cover of the country Poverty estimates at jamoat (village) level derived from the poverty mapping technique 1999 Census of Tajikistan SCHOOL ENROLMENT IN TAJIKISTAN

24 Influences on enrolment Individual Age, sex Household Parental education, poverty Community factors Availability of school Perceived quality Employment opportunity outside school SCHOOL ENROLMENT IN TAJIKISTAN

25 Proportion of land between 0-5 degree of slope within 1 km buffer Proportion of people living below the poverty line and cotton growing area SCHOOL ENROLMENT IN TAJIKISTAN

26 ESARO replication of Lancet analysis using 6 year panel from RSA: kids stunted at age 5 are 1.5 grades behind by age 13 Source: Ashu Handa UNICEF ESARO

27 ESARO replication of Lancet analysis: Nutrition in 1998 affects learning in 2004 Residual estimates controlling for income

28 3. International comparisons Can be helpful for big policy ideas Highlighting policy coherence and/or policy efficiency Can stimulate policy transfer Advocacy value


30 Challenges in using statistics to inform policy Existing concepts, data and availability Sensitivity analysis, robustness –child focus –thresholds –economy of scale/equivalence of scale (income data) Design causal analysis: Need hypotheses plus data to test them Overlaps of income and non-income dimension: limitation

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