CBMS Planning and Budgeting Module for LGUs

1. CBMS Planning and Budgeting Module for LGUs Aniceto C. Orbeta, Jr. Philippine Institute for Development Studies 5th CBMS National Conference Centennial Hall, Manila Hotel January 30-31, 2008

2. Outline Objectives CBMS Planning Module CBMS Budgeting Module Note: This is an abbreviated version of training module that usually need a couple of days

3. Objectives General objective: Strategic use of CBMS data to improve the empirical basis of local planning and budgeting Specific objective: Improve / Enhance CBMS Planning and Budgeting Modules Focus: improve empirical basis of planning and budgeting not on procedural matters

4. CBMS Planning Module

5. Planning Cycle

6. Identifying development problems / issues through benchmarking Why benchmark? One of the simplest way of identifying and prioritizing major development problems objectively

7. Identifying development problems / issues through benchmarking Benchmarking defined: • Comparing performance of city / municipality / barangay with • Other cities/municipalities/barangays • Past performance • Planning standards • Involves • Identifying relevant indicators • Generating / gathering the indicators • Comparing indicators

8. Identifying development problems / issues through benchmarking Identifying relevant indicators • Determined by development goals and objectives • Examples • Poverty Alleviation: CBMS 13+1 Core indicators • Global Millennium Development Goals • National goals and objectives from the MTPDP

9. Identifying development problems / issues through benchmarking Sources of benchmarking information CBMS data from other cities / municipalities / barangays and previous rounds Similar national, regional, provincial and municipal indicators from national censuses and representative surveys Planning standards

10. Identifying development problems / issues through benchmarking Generating / gathering benchmarking indicators Using StatSim to generate CBMS indicators Using published indicators from national censuses and surveys Processing public use files (PUFs) national censuses and surveys

11. Benchmarking illustration … Development Framework / Vision The subsequent illustrative exercises considers the CBMS 13+1 Core Indicators as the desired set of development indicators Can have a slightly or completely different set of development indicators in the future; after initial training you can handle any set of development indicators in the future

12. Benchmarking Illustration… Benchmarking for Escalante, Negros Occidental

13. Benchmarking illustration … Benchmarking for Escalante, Negros Occidental

14. Benchmarking says … Health and nutrition not a pressing problem. The worst case scenario is better than national average. But it should be noted that girls have higher malnutrition incidence than boys School attendance a big problem and in addition boys have higher non-attendance rates than girls particularly at the secondary level Housing not a problem relative to national average Sanitation a big problem both for toilet and for water Almost everybody working but poverty incidence is still very high High subsistence (food) poverty incidence but very small incidence of hunger

15. Identifying Development Problems and Strategies Using Analytical Frameworks What are Analytical Frameworks? • Simplified but structured representation of development realities Why Use Frameworks? • Can use analytical frameworks to: • Enrich situation analysis • Enrich strategy formulation • Organize data into useful summaries

16. Outcomes Determinants Using Frameworks … Determinants Framework Cause Effect

17. Using Frameworks … Proximate Determinants Framework Davis and Blake (1955-56)

18. Using Frameworks … Proximate Determinants Framework Group determinants into underlying and proximate Proximate determinants are those whose impact are more direct and seldom change from one society or socioeconomic group to the next Underlying factors are those that can’t be considered proximate or direct but are known to play also important roles in determining the outcomes

19. Using Frameworks … Determinants of Health Outcomes: Proximate Determinants Framework Orbeta (1994)

20. Using Frameworks … Determinants of Education Outcomes: Proximate Determinants Framework Orbeta (1994)

21. Using Frameworks … Implications • There are other determinants besides obvious direct determinants • School attendance is not only determined by education variables (e.g. availability of school) but others such as health status of child, attitudes of parents towards schooling • We need to examine these other determinants as well

22. Using frameworks … Implications (cont.) Use determinants frameworks to identify important determinants of outcomes of interest Use determinants framework to identify the needed components of intervention programs / projects Often details and more in-depth information on the determinants and how important they are can only be generated from FGDs with frameworks as guide on what questions to ask for specific issues

23. Common perception about development problems Malnourished children are from households with low income, experience food shortage, unhealthy surroundings, Non-attending school-age children are from household with low income, parents with low education status, homes not conducive for studying Poor households have working-age members that are unemployed

24. Using frameworks, CBMS Data and StatSim… Malnourished children and household characteristics, Jonobjonob, Escalante City, 2006

25. Using frameworks, CBMS Data and StatSim… School participation and household characteristics, Jonobjonob, Escalante, 2006

26. Analytical Frameworks Using CBMS Data says… • Malnutrition • Is negatively affected by income and poverty status, family size, education of reference person, positively affected by health condition in the home (water supply, sanitation) • School Attendance (elementary) • Is affected by status of settlement and presence of electricity, education status of reference person • Income and poverty status appears not to be hindrance

27. Identifying Development Problems and Strategies by Disaggregating by Socioeconomic Groups Why disaggregate by socioeconomic groups? Useful for improving efficiency and effectiveness of interventions (PPAs), i.e. via better targeting Useful for assessing fairness of outcomes Useful for assessing equity in access to services which are important determinants of fairness in outcomes

28. Disaggregation by socioeconomic groups Disaggregation by income class Disaggregation by sector or employment and occupation of reference person Disaggregation by gender

29. Disaggregation by income classes

30. Disaggregation by income classes Disaggregation by income classes shows that income is a consistent source of disparity in outcomes except for the case of informal settlers where there seems to be higher incidence even among the higher income groups

31. Access to programs by income classes Programs appears to be reaching more poorer than richer households

32. Gender Responsive Planning and Budgeting and CBMS • Disparity in outcomes • Disparity in access to programs • Analyze impact of proposed PPAs in terms of impact on women • Women empowerment • Reinforcing traditional typecasts

33. GRPB and CBMS Escalante, 2006 Disparity in outcomes Note: Built-in into CBMS data generation systems

34. CBMS Budgeting Module

35. Budgeting Cycle

36. CBMS Data and the Budget Cycle Use of CBMS data in budget preparation – illustrative examples focused here Other uses of CBMS data – budget authorization and budget review

37. Budget Preparation Analysis of sources of income • Purpose • Revenue forecasting • Components • By Type • Tax revenues (IRA here) • Non-tax revenues • By Source • Own/Internal Source • External sources (IRA here) • Analysis of composition and trend • Compute percentage shares of each component • Note the trends and changes in percentage shares • Compute growth rates

38. Budget Preparation Data for Sources of Income Data from administrative reports (e.g. previous income from tax revenues, non-tax revenues); Estimated income from proposed revenue measures

39. Budget Preparation Configuring the Expenditure Program • Programs, Projects and Activities (PPAs) • Components • Personnel • Maintenance and Other Operating Expense (MOOE) • Capital Outlay

40. Budget Preparation Expenditure Program (cont.) • Statutory Requirements • Personnel (45% for 1st-3rd class, 55% for 4th and below of regular sources ) • Non-Office • Development Fund (20% of IRA) • SK – a trust fund (10% of general fund) • Calamity (5% of regular sources) • GAD (5% of total annual appropriation)

41. Budget Preparation Expenditure program (cont.) • New initiative: Improving Results-Orientation of Budget Process through Outcomes-Output Framework • Alignment of PPAs with objectives and strategies • Specifying performance indicators and performance targets • Venue for improving plan-budget link and role of CBMS data

42. Budget Preparation Expenditure program (cont.) Example of a cursory review of proposed Development Fund (20% IRA) budget in the light of CBMS results

45. General comments on priorities as expressed in the AIP allocations • Benchmarking using core indicators show that the main problems of the city are: • High incidence of poverty (74% vs. national poverty incidence rate of 24%) • High school non-attendance rates (twice as high compared to national attendance rates) • Low access to safe water and sanitary toilets (more than twice as high for both safe water and toilets)

46. General comments on priorities as expressed in the AIP allocations Big allocations for housing projects (Site Development (1M) and Land Banking (5M)) when housing is not a problem Given very high poverty incidence, economic development allocations may need to be increased with particular attention to sources of additional income as unemployment is already very low No apparent allocation for education interventions when non-attendance is very high Projects to improve access to safe water sources and sanitary toilet facilities may need more allocation The large allocation in health need some clearer justifications as malnutrition is not a problem as well child death and maternal deaths

47. Budgeting with CBMS Data … Observations Without the CBMS data, it would be difficult to argue for or against allocation of resources into specific PPAs in specific locations; easier to perpetuate previous PPAs With CBMS data, one can argue with confidence even seemingly unpopular allocations

48. Budgeting with CBMS Data … Expenditure program (cont.) Away from lump-sum allocation into evidenced-based budgeting How? In particular, how can CBMS data help?

49. Budgeting with CBMS Data … Expenditure Program (cont.) • Configuring PPA structure • For each development problem, what PPAs to develop? • Use frameworks with CBMS data for validation of what goods and/or services to deliver

50. Budgeting with CBMS Data … Expenditure program (cont.) After priority Program/Projects/ Activities (PPAs) are identified, budget the PPAs • Budget=no. of clients x coverage x unit cost • No. of clients is provided by CBMS data, e.g. number of malnourished children, no. of household without safe water supply, no. of households without sanitary toilet • Coverage – how many/much will be covered for the budget year - determined by financing capability • Unit cost determined from administrative records