The document discusses how open geospatial data can improve development outcomes. It provides examples of how regional spatial analysis can support analytic work, planning, monitoring, sectoral coordination, and donor coordination. A case study of Bolivia shows how spatial analysis was used to better target public investments, strengthen monitoring of aid flows and development goals, and enhance donor coordination. Key findings included unequal distribution of projects relative to poverty levels and lagging progress in reaching development goals in poorer highland regions. The document argues for refocusing aid to target these regions.

1. The power of Open Geospatial Data
to improve development outcomes
Björn-Sören Gigler
bgigler@worldbank.org
23.May 2009
Twitter: bgigler

2. Regional Spatial Analysis can
support:
1) Analytic Work
• Highlight geographic distribution of poverty and
inequalities within countries
• Display and analyze different dimensions of poverty
2) Planning
• Improve targeting of public investment programs
• Raise awareness of policy makers (disaster risks)
3) Monitoring
• Integrate Poverty Maps into results-based M&E
• Better monitor development impact (MDGs) at the
national and sub-national level

3. Regional Spatial analysis can support:
3) Sectoral Coordination
• Carry out cross-sectoral analysis
• Enhance the coordination of different sectoral
programs
4) Donor Coordination
• Analyze the geographic distribution of aid flows
• Improve the coordination of donors and support aid
harmonization
5) Transparency
• Enhance the participation of stakeholders in
decision-making processes

4. International Pillar
PEGASYS
• instrument to monitor the contribution of Bank-
funded projects towards achieving the MDGs.
• provides information about the MDGs and the
Bank’s project portfolio
• enables users to carry out cross-country
comparisons & trend analysis
• information can be analyzed at the global,
regional, or country level

5. PEGASYS: MDGs

6. PEGASYS : WB Projects

7. Spatial Portfolio Review: Disaster
Management

8. Country Pillar
• Support the design of national development plans
and sectoral investment programs
• Improve targeting of public investments to reach
vulnerable groups in poor regions
• Track geographic flow of public investments &ODA
• Enhance the capacity of government to monitor the
MDG’s at the national & sub-national level
• Strengthen the monitoring of aid flows to local
governments (i.e HIPIC)
• Identify overlays of donor programs and enhance
donor coordination

9. Bolivia: Case Study
National Development Plan:
• New Government emphasizes spatial dimension
(territory)
• Constitutional Change: Creation of Regional
Government based on common geographic,
ethnic & cultural aspects
• Ministry of Planning has prioritized programs to
specific regions (146 municipalities)
• Development with Identity (Community/region
and not sector at the center)

10. Bolivia— Government Objectives
- Improve targeting of public investments to reach
vulnerable groups in poor regions (146 and 31
municipalities)
- Strategic planning and enhance coordination of different
donor programs
- Strengthen the monitoring of aid flows (i.e. to local
governments through HIPIC)
- Improve efficiency of existing programs (results-oriented)
- Enhance transparency of government programs
- Improve the participation of civil society and poor
communities

11. Bolivia- Bank program
Policy Notes & ISN
• Identifies donor coordination & harmonization as a key
issue
• Mentions the Aid Management Platform and the use of GIS
M& E project:
• support the Ministry of Planning in developing a M&E
system for the National development Plan
• Enhance the capacity of government to monitor the MDG’s
at the national & sub-national level
IDF on Aid Effectiveness:
• strengthen capacity of VM of Public Investments & External
Financing to track & monitor the flow of ODA
• Improve the coordination/ harmonization of ODA among
donors

12. Bolivia- Bank program
Development Gateway- Aid Management Platform
• E-Government solution, which provides governments with a
tool to plan, monitor and evaluate public investments
• Track geographic flow of public investments & ODA
• Identify overlays of donor programs and enhance donor
coordination
Spatial Poverty & Human Development Analysis
• Analysis of regional disparities in poverty and human
development
• Use of Poverty Maps
• Spatial WB-Portfolio Analysis
• Spatial Analysis of IDTR project

13. Spatial Poverty Analysis
• Visualize trends in poverty and socio-economic
indicators
• Illustrate important regional and social differences
• Geographic dimension of growth & poverty can add
value to the preparation of CAS and AAA
• Overlay of geographic focus of Country Program with
poverty data
• Enhance the portfolio monitoring by adding geography
of projects
• Improve the coordination of projects from different
sectors (i.e. transport & education)
• Use Maps for policy dialogue with governments and
donors (i.e. disaster risk)

14. Poverty Reduction at the National Level

15. Levels of Extreme Poverty (under $1)
in 2001 at the department level
40.4% 42.4% 39.0%
46.3%
66.7%
25.1%
41.0%
34.7%
61.5%
32.8%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
BoliviaC
huquisaca
La
Paz
C
ochabam
ba
O
ruro
Potosí
TarijaSanta
Cruz
Beni
Pando

16. MDG Monitoring – Incidence of Extreme Poverty
(2001)

17. Indigenous Peoples 2001

18. High levels of poverty
• High correlation between poverty and being
indigenous
Bolivia: Poverty Rate by Area and Et hnicity, 2001
Et hnic Group I ndigenous Non-I ndigenous Total
Rural 87.0% 71.7% 81.1%
Urban 67.8% 50.6% 53.7%
Nat ional 80.7% 55.4% 64.1%
Ethnic group defined on mother tongue and language spoken. Source: Own calculations based on MECOVI 2001.

21. Reduction in Infant Mortality Rates
at the national level
Infant Mortality Rate (per 1,000)
89
76
67 63
54 52
0
20
40
60
80
100
1989 1995 1998 2000 2003 2005

22. Important Regional Difference in
Infant Mortality Rates
Infant Mortality Rate (per 1000) in 2003
54
67
52
61
88
72
29
39 33 33
0
20
40
60
80
100
BoliviaC
huquisaca
La
Paz
C
ochabam
ba
O
ruro
Potosí
TarijaSanta
Cruz
Beni
Pando

23. Change in Infant Mortality Rates (1992-2003)
at the department level

24. Change in Infant Mortality Rates (1992-2003)
at the municipal level

25. Improved Health Services
at the national level
Birth attended by skilled staff (in %)
25
33
43
51
6058
54
0
10
20
30
40
50
60
70
1994 1996 1998 2000 2001 2003 2005
Birth attended by
skilled staff (in %)

26. Change in Births Attended by Skilled Staff (2001-2005) at
Department level

27. Change in Births Attended by Skilled Staff (2001-2005) at
Municipal level

28. Georeferencing of WB projects
• Georeferencing of all WB- projects in Bolivia
• Concentration of projects in certain regions
• Spatial Sector Analysis
• Analysis of Regional Resource Flow
• Two states did not have any targeted project
(only national)
• Overlay with spatial poverty and human
development analysis
• Initiated Spatial Public Investment Review
(ODA)

29. Number of World Bank-Financed Projects
FY 2007

30. World Bank Financed Projects by Sector

31. WB project count in Resources

32. Georeferencing a WB-Project

33. Key Findings on MDG analysis
• Important improvements in the MDGs at the national level,
however not in the poorest regions (highlands)
• Important progress in lowering poverty in lowlands (Santa
Cruz, Beni, Pando and Tarija)
• Important improvements in Infant & Maternal Mortality Rates
at the national level
• Departments in the highlands continue to lag behind in
reaching the MDGs
• Extreme poverty levels have remained stagnant at high levels
in the highlands
• Infant mortality rates have worsened in 58 municipalities (La
Paz, Cochabamba, Potosi)
• Birth rates attended by skilled workers have worsened in
several highland municipalities

34. Key Findings on Spatial Portfolio Analysis
• Unequal geographic distribution of World Bank-
financed projects in relation to location of poverty
• Out of 9 projects (6 investment loans) there are 4 (2)
national projects and 5 (4) sub-national projects
• Concentration of WB projects in Santa Cruz region,
in spite of its relatively low levels of poverty
• No sub-national project in Beni and Pando
• Improved targeting of extremely poor regions of
highlands needed
• Relatively few projects in Chuquisaca 5 (2
investment loans) in spite of severe poverty

35. Uses of Inter-active Mapping tools in
Country Programs
• Geographic dimension of growth & poverty can
add value to the preparation of CAS and AAA
• Overlay of geographic focus of Country
Program with poverty data
• Visualize trends in poverty and socio-economic
indicators
• Enhance the portfolio monitoring by adding
geography of projects
• Improve the coordination of projects from
different sectors (i.e. transport & education)
• Use Maps for policy dialogue with governments
and donors (i.e. disaster risk)

36. Uses of Inter-active Mapping tools in
Country Programs
• Enhance the monitoring of MDGs at the
national and sub-national levels;
• Establish stronger linkages between
specific projects and their contribution to
the MDGs
• Enhance donor coordination & aid
harmonization
• Strengthen the Information dissemination
and participation of stakeholders

37. Policy Implications
• Refocus Country Program to target poorest regions (i.e.
Chuquisaca, Potosi, Cochabamba)
• To reach the MDGs a special focus on the poorest
regions & socio-economic groups is necessary
• Establish stronger linkages between specific projects
and their contribution to the MDGs
• Targeted Anti-Poverty Intervention for poorest
municipalities (i.e. malnutrition)
• Improved donor coordination & harmonization needed
(SWAP interventions)
• Better M&E of Public Investments needed (local &
regional governments)