Poverty Mapping, Policy Making and Operations

Transcription

1 Poverty Mapping, Policy Making and Operations Some Applications from Kenya (DECDG) Using Poverty Maps to Design Better Policies and Interventions Washington DC May 11, 2006

2 Outline Poverty Mapping process in Kenya Capacity building exercise Demand driven Some examples of Impact 1. Expenditure Allocation 2. Integrating Geo-Referenced Databases 3. Education SWAp operation

3 On the Poverty Mapping Process Started as a capacity building exercise supported by DECRG poverty mapping team First output was a detailed GoK released Atlas and database of poverty estimates for Administrative areas (70 Districts to over 2,500 Locations) This generated substantial renewed interest in statistics by GoK and wide press coverage People related to maps Leveraged the profile of the Statistics Bureau

4 On the Poverty Mapping Process GoK and donors became more interested in supporting and investing in better statistics GoK requested follow-up exercise - Phase 2: Small-area poverty estimates and map for geo-political areas (210 Constituencies) GoK and donors partnered up to design a SWAp to support the National Statistical System in Kenya Build around a National Strategy for the Development of Statistics

5 On the Poverty Mapping Process The Bank is supporting this SWAp to Statistics via a $20m STATCAP project STATCAP is a new lending program board approved in March 2004 which is especially designed by DECDG to make investments in statistical capacity easier and more effective Set-up a poverty analysis unit and GIS research lab in the Central bureau of Statistics

6 Some Examples of Impact 1. Expenditure Allocations Based on the Constituency-level poverty map, GoK revised the allocation formula of the Constituency Development Fund (2.5% of GDP - $100m in FY05/06) to allocate 25% based on poverty incidence Previously all Constituencies received equal amounts

7 Some Examples of Impact 1. Expenditure Allocations (cont.) Now working on linking and tracking Government expenditures in key Ministries (Education, Health, Agriculture and Roads) to Administrative areas Also working on targeting and improving the transparency of allocations within Constituencies; linking this to maps of development and well-being indicators within Constituencies

8 Integrating Geo-Referenced Databases 1: REFERENCING SPACE POINTS of Service Delivery e.g., schools, health centers, boreholes NETWORKS of Infrastructure e.g., roads, electricity, telecom AREAS of Administration & Livelihood e.g., enumeration, districts, communities

9 Integrating Geo-Referenced Databases 2: GEO-REFERENCING DATA POINTS of Service Delivery e.g., health facility survey and M&E data NETWORKS of Infrastructure e.g., road quality survey and M&E data AREAS of Administration & Livelihood e.g., public spending allocations, e.g., population census data INTEGRATE DATA with geo-referenced poverty data RELEVANT for POLICY, PROGRAMS & PROJECTS

10 The Kenya Integrated GIS Database: Under Construction Topographic Maps [1:50,000] Administrative Boundaries [6,640 sub-locations] Geo-Political Boundaries [210 Constituencies] Population Census data (by sub-location) Poverty Map (by sub-location) Election results (by polling station) Public Expenditures (by Constituency/sub-location) Service Facilities Locations Schools & EMIS Health facilities Weather stations

11 The Kenya Integrated GIS Database: Under Construction (cont.) Agro-Climatic Zones Agro-Ecological Zones Climatic/Rainfall Zones Soil Erosion Rivers, Lakes and Catchment areas Digital Elevation Model Infrastructure Networks Roads quality Mobile phone masts and coverage areas

12 Example 3: Construction of New Schools Kenya Education Sector SWAp GoK and development partners earmarked US $80 million for primary school infrastructure expansion and upgrading Credible and transparent database needed to allocate the funds based on evidence Education Monitoring Information System (EMIS) Use an integrated geo-referenced database for program design, M&E and baseline for evaluation of impacts

13 School Data can now be geo-referenced School Location GIS referenced with GPS device

14 Geo-referenced school data base can now be merged with other info such as roads and sub-location data and maps of poverty and school-aged population density

15 hool map is mbined with nsity of hool-aged ildren at subcation level to mpute tchment eas and tect gaps in cility coverage potential gap in school coverage

16 PLANS FOR NEXT PHASE: Project Supervision: Link Digital Photographs (e.g., Lesotho) Systematically link EMIS data as part of M&E system

17 Other work in progress New Technical Options: Linking data sets Sampling design Operational Support: Using geo-referenced database in the design of a Bank funded CDD project in Western Kenya A impact evaluation (randomized design) is build explicitly into the project and, in addition to evaluating project outcomes, will also evaluate the poverty map