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### I. Introduction — core argument
- PRS approach is a powerful vehicle for mobilizing nationally owned efforts and resources to grow out of poverty but "still lags in its capacity to monitor these desirable objectives effectively."
- Root cause: developing institutional statistical capacity to permit evidence-based monitoring of PRSP goals has not been integral to, and therefore has not moved in step with, advances in PRSP design and implementation.
- Integrating PRS and statistical development strategies could:
  - Improve monitoring of PRSP goals.
  - Enhance effectiveness of statistical capacity building.
  - Facilitate costing of essential statistical reforms and their incorporation into the medium-term expenditure framework (MTEF).
- Mainstreaming statistical strategies into national development plans should:
  - Enhance national priority for statistical reforms.
  - Provide a basis for costing reforms for inclusion in the MTEF.
  - Create an environment conducive to sustained transfer of expertise to local officials and improve technical assistance (TA) effectiveness.

### II. Development strategies, PRS approach, and the demand for data — analysis and facts
- Major international initiatives shaping demand for statistics:
  - PRSP introduced September 1999.
  - PRGF launched September 1999.
  - Millennium Development Goals established September 2000.
  - Monterrey Consensus March 2002.
  - Paris Declaration on Aid Effectiveness March 2005.
- As of July 2007:
  - "45 countries had prepared PRSPs, while 12 countries had prepared interim PRSPs."
  - "Eleven countries comprising Benin, Burkina Faso, Ghana, Madagascar, Mauritania, Mozambique, Nicaragua, Senegal, Tanzania, Uganda, and Vietnam had already implemented their original PRSPs and adopted a second-generation PRSP."
- The PRS approach and related strategies require substantial macroeconomic and sociodemographic statistics compiled largely by LICs.
- Paris Declaration and related initiatives increased emphasis on effective monitoring, creating a second wave of data requirements to:
  - Establish benchmarks against which to measure progress.
  - Provide intermediate markers to quantify changes over time.
- Increased data demand exacerbates pressure on LICs' statistical systems, which are resource-constrained and must undertake extensive surveys and censuses (poverty, gender, household income and expenditure, sectoral surveys) to produce internationally comparable, high-quality, and timely datasets.
- Debt-relief initiatives (HIPC, Enhanced HIPC, MDRI) and associated debt sustainability exercises generate additional significant data requirements for LICs.

### III. Evaluations and common conclusions — findings from assessments
- Multiple evaluations (IMF Independent Evaluation Office; joint Bank/Fund reviews; DFID/World Bank staff review of 12 countries) reached broadly similar conclusions:
  - Some progress has been made in mainstreaming monitoring into PRSPs, but "much remains to be done" to integrate monitoring systems with policy analysis and decision making.
  - Needs differ across countries; Africa faces "a particularly more difficult challenge in terms of a lower starting point and the progress made thus far."
  - Linking PRSPs to the budget process, particularly the MTEF, is critical and generally weak; appropriate costing and prioritization for resource allocation are needed.
  - Capacity building for national institutions is essential; avoid duplication of statistical systems and ensure harmonization with donor requirements and procedures.
- Specific IMF Independent Evaluation Office findings:
  - PRSPs focus mainly on composition of public expenditure, especially social sector spending, with "much less emphasis on other aspects of a broader strategy to encourage poverty-reducing growth."
  - "Operational value of PRSPs is often limited because of the still rudimentary nature of most costing and prioritization...." Capacity constraints have been a severe impediment.
  - PRSPs that meet original goals require considerable technical and analytical capacities and financial support; nothing in current settings ensures capacity-strengthening priorities will be addressed or clearly linked to lending decisions.
  - Analytic bases of PRSPs are typically weak, notably the macroeconomic framework and policies to promote growth; insufficient prioritization, inadequate costing, and avoidance of controversial structural reform issues limit PRSPs' strategic value.
  - Indicators and monitoring arrangements in PRSPs often "far exceed the underlying data capacity to collect and analyze the underlying data" — institutionalizing such capacity is resource-intensive and will take many years.
  - Indicators are typically better defined for health and education than for areas dominated by inputs/process indicators or where indicators are lacking (e.g., structural reforms or governance).
  - More than half of PRSPs initially lacked links to the budget and MTEF; where links existed on paper, their effectiveness was often weakened by the MTEF's weak connection to the actually implemented budget.
  - Joint Staff Assessment papers identified costing, financing, and prioritization as main weaknesses in two thirds of 23 cases; costing is frequently partial and rudimentary, and over a third of PRSPs lack a financing plan and/or a prioritized action plan.
  - Obstacles to mainstreaming poverty and social impact analysis most often cited were data limitations and national capacity constraints, though some assessment is possible even in countries with limited data.

### IV. Policy implications and operational recommendations
- Prioritize integration of statistical capacity building into PRSP formulation and implementation to:
  - Ensure availability of data to monitor progress and inform policies.
  - Enable costing of statistical reforms for inclusion in MTEF and budgets.
  - Improve effectiveness of technical assistance by embedding reforms within national planning and budgeting processes.
- Strengthen links between PRSPs and budget/MTEF processes with explicit costing and prioritization to enhance resource allocation and implementation feasibility.
- Avoid duplication of statistical systems and harmonize donor requirements to reduce fragmentation and increase efficiency of capacity building.
- Recognize institutionalizing data systems and analytical capacity is resource-intensive and multi-year; plan for sustained support and realistic timetables.

### V. Box 3 — Essential features and issues in PRSP monitoring (12-country experience)
- Purpose and role:
  - Monitoring system is critical for continuous improvement of PRS and to influence development policy by making it more evidence-based and results-oriented.
- Scope:
  - Track overall progress in poverty reduction against national targets and MDGs via periodic measurement of selected indicators using administrative data, surveys, censuses, quantitative and qualitative data; usually led by national statistics agencies.
- Implementation challenges:
  - Progress in establishing effective PRS monitoring systems has been limited.
  - Few systems have functioning links between monitoring and decision making.
  - Coordinated monitoring systems and ensuring monitoring data are used in the policy process are major practical challenges.
- Linking outcomes to resources:
  - Expenditure tracking depends on parallel progress in budget and public expenditure management reforms and availability of quality and timely data.
- Role and resourcing of national statistical agencies:
  - National statistical agencies often most institutionally advanced; systems must ensure complementarity to avoid duplication.
  - PRS monitoring systems should ensure statistics agencies have sufficient resources and mandates to set standards, undertake surveys/censuses, provide TA, and build capacity of other agencies.
- Donor alignment limits:
  - Donors often find annual progress reports insufficient for accountability/management; donors tend to incorporate separate monitoring and evaluation systems in individual projects, leading to duplication.
- Design and funding modalities:
  - Lack of complementarity may result from existing funding modalities; national agencies prioritize donor-funded operations, leaving little time for other functions.
  - Donors may need more flexible ways of supporting institutional development (e.g., basket funding).
- Building demand and linking to budget:
  - Effective systems must build demand for monitoring; linking PRS to the budget process is critical and more readily accomplished where MTEF exists.

### VI. Box 5 — Select major statistical development initiatives and constraints
- Major initiatives and objectives:
  - Special Data Dissemination Standard (SDDS) — 1996.
  - General Data Dissemination System (GDDS) — 1997.
  - PARIS21 — November 1999.
  - International Standards and Codes (including DQAF and ROSCs) — 2000; DQAF developed July 2001 (updated July 2003).
  - Marrakech Action Plan for Statistics (MAPS) — February 2004 (mainstreaming strategic planning for all low-income countries by 2006; urgent MDG monitoring improvements by 2005; increase financing).
  - National Strategy for the Development of Statistics (NSDS) — 2004.
- Links among standards/frameworks and macro statistics:
  - Four main macroeconomic datasets: national accounts; balance of payments and international investment position; monetary and financial; government finance statistics.
  - Standards anchored in the System of National Accounts 1993 (1993 SNA).
  - SDDS/GDDS linked with DQAF and data module ROSC process.
  - GDDS includes sociodemographic datasets; SDDS does not.
- Convergence of statistical and development strategies:
  - Mainstreaming statistical strategies into development strategies driven by need to monitor PRS and MDG targets and TA providers’ frustration with lack of priority/funding for statistical reforms.
  - Proposal to treat statistical activities as a "sector" and employ a systemwide approach (SWAp-equivalent).
  - NSDS aligns with development banks’ and donors’ mandates and attracts increased funding (e.g., STATCAP).
- Constraints to effective statistical TA:
  - LICs often lack financial resources, IT, and skilled manpower; resource constraints emphasized in DQAF elements 0.2 and source data element 3.1.
  - Data ROSC findings for PRGF-eligible countries indicate resources are a major factor impeding data quality, most severe in government finance statistics and national accounts, followed by prices and balance of payments.
  - Operational constraints: decentralization increases reporting units (examples: over 70 units in Sierra Leone; Kenya identifies 83 autonomous agencies); abolition of exchange controls reduced administrative source data for balance of payments; increasing services and private financial flows require more regular enterprise surveys.

### VII. Data on adequacy of resources for statistical production (DQAF-based data ROSCs in 22 PRGF-eligible countries since 2001)
- Number of countries with Adequate Resources vs Inadequate Resources:
  - National accounts: 2 Adequate, 20 Inadequate
  - Consumer prices: 3 Adequate, 15 Inadequate
  - Producer prices: 3 Adequate, 8 Inadequate
  - Government finance statistics: 1 Adequate, 21 Inadequate
  - Money and financial statistics: 13 Adequate, 8 Inadequate
  - Balance of payments: 6 Adequate, 16 Inadequate
- Percent of Total (Adequate vs Inadequate):
  - National accounts: 9.1 Adequate, 90.9 Inadequate
  - Consumer prices: 16.7 Adequate, 83.3 Inadequate
  - Producer prices: 27.3 Adequate, 72.7 Inadequate
  - Government finance statistics: 4.5 Adequate, 95.5 Inadequate
  - Money and financial statistics: 61.9 Adequate, 38.1 Inadequate
  - Balance of payments: 27.3 Adequate, 72.7 Inadequate
- Memorandum item:
  - Weighted average (percent of total): 24.1 Adequate, 75.9 Inadequate
- Notes:
  - In some cases, data ROSCs exclude assessments for certain datasets.
  - Rating of "Observed" indicates resources commensurate with tasks.
  - Ratings of "Largely Observed," "Largely Not Observed," and "Not Observed" denote some, significant, and substantial insufficiency, respectively.

### VIII. Findings from GDDS review and regional patterns
- Preliminary findings from a 10-year GDDS review:
  - Readiness to subscribe to SDDS appears more problematic in Africa and the Western Hemisphere, which are farthest from SDDS requirements in real and external data timeliness and periodicity.
  - Uneven progress across macroeconomic datasets reflects that real and external sectors rely on expensive and resource-intensive source data.
  - Regional deviations in compliance with SDDS requirements may result from differences in availability of resources to absorb capacity-building TA.
- Participation counts:
  - 94 countries have participated in the GDDS, 6 of which went on to become subscribers to the SDDS, leaving 88 countries as current participants.

### IX. IMF, donors, and coordination of TA delivery; country-level experiments
- Donors/agencies increased coordination to mobilize aid for sustainable TA; statistical TA spans institution/infrastructure support and data quality work.
- IMF focuses TA on data quality issues and depends on donor-provided financial and other inputs to build foundations for effective TA.
- Need to mainstream statistics into PRS and MTEF to secure national priority and medium-term funding for reforms.
- IMF country-level experiments and projects:
  - Anglophone Africa GDDS project (since 2002; IMF and World Bank executing; funded by DFID) prepared metadata and plans; 13 of original 14 countries joined the GDDS.
  - Second phase GDDS project (2006–09) launched September 2006 with modules delivering TA via workshops and expert visits; one module assists five countries (Lesotho, Malawi, Seychelles, Sudan, and Zambia) to integrate GDDS plans into PRSPs.
  - Sierra Leone pilot: integrated GDDS plans into PRSP with a medium-term budget for reforms but faced limits due to staff turnover, domestic budget constraints, and donors not being part of the exercise.
  - Zambia (2006): assistance helped integrate cost of macroeconomic statistical reforms into National Development Plan (NDP, 2006–2011); sociodemographic reforms had been costed and reflected in associated MTEF.
  - IMF provided TA to Burundi using prototype costing framework (ISTEBU) as basis for costed comprehensive reforms covering macroeconomic and sociodemographic datasets.

### X. Pilot efforts to mainstream statistics into the PRS approach (Africa) — Appendix V
- Joint missions with PARIS21 in 2006 assisted Burkina Faso and Senegal to:
  - integrate their GDDS and other plans for statistical reform into the PRSP, and
  - cost them for incorporation in the MTEF.
- Early pilot activities include identifying existing good practices and selecting countries where SWAps may be appropriate and more intensive donor effort is needed.
- PARIS21 envisages a greater advocacy role with a SWAp for statistics as a follow-up to the Third Roundtable in Hanoi.
- Full impact is still too early to assess; success requires greater acceptance of mainstreaming, broader participation by donors and country authorities, and practical steps informed by pilot cases.

### XI. Realistic budget for statistical reforms
- Key principles:
  - Resource claims must incorporate prudence and realism.
  - Scope of reforms should be tempered to fit the existing environment.
  - Incremental and well-phased design may ensure better sustainability than wholesale introduction of state-of-the-art systems.
  - Components and total cost of reforms need to be developed with overall resource constraints in mind.
- Roles and processes:
  - GDDS/NSDS coordinator, working with all statistical agencies and experts in costing reforms, should ensure funding is comprehensive and appropriately phased over the PRSP and MTEF period.
  - Early and continuous coordination with donors and the ministry of finance is key to maintaining feasible reform cost proposals for MTEF inputs.
- Practical considerations:
  - Occasional critical but lumpy projects (e.g., population and housing or agricultural censuses; setting up autonomous national statistical agencies) can be fitted within the MTEF with adequate advance timing and phased donor/government support.
  - Adopting a systemwide approach to medium-term budgeting for statistics could emulate social sector practices using annual public expenditure reviews (PERs).
- Historical caution:
  - Early NSDS versions showed overly ambitious infrastructural projects and reforms resulted in substantial resource requirements unacceptable to ministries of finance and donors; setbacks required confidence rebuilding.

### XII. Conclusions — findings and implications
- Since the late 1990s, practitioners, national authorities, donors, and TA providers have converged to address weak statistical capacity in developing countries within poverty reduction frameworks.
- The PRS approach and the Monterrey Consensus changed interactions, emphasizing broad public participation, national ownership, and specific objectives (the MDGs).
- Donors committed to increasing assistance within frameworks that channel resources through developing country institutions via improved harmonization and accountability.
- Parallel efforts developed broad-based statistical strategies to meet increased demand for data to support poverty reduction and monitoring.
- Main conclusions on resources and TA:
  - Emerging evidence indicates resources are critical to TA effectiveness, especially for macroeconomic datasets in national accounts, prices, and balance of payments due to high dependence on surveys and censuses.
  - Resources are a constraint for government finance statistics, linked to decentralization and limited capacity to compile and disseminate data from autonomous central government agencies and local governments.
  - Addressing these problems requires increased resources and enhanced coordination among partner country statistical agencies, donors, and TA providers—an important but not necessarily sufficient condition for more effective TA.
- Implementation and advocacy:
  - Implementing the proposed approach will take time; advocacy is key because statistics have public good characteristics and significant market failure.
  - Building public awareness in LICs and among development partners is crucial to enhance priority and funding for statistical development within the PRS approach and MTEFs.
  - Comprehensive listing and costing followed by prioritization of statistical reforms are central and require leadership by partner country authorities supported by donors and the IMF.
  - Selecting countries to pilot endeavors, including the SWAp, should provide best practices to guide future work.
  - Statisticians and TA providers should formulate comprehensive but realistic reform budgets and are advised to emulate annual sector PERs proven successful in other PRS sectors.
- Africa-specific note:
  - Africa faces particularly challenging starting positions and relative effort needed to mobilize requisite resources for statistical capacity.
  - Success depends crucially on local ownership and leadership by country authorities and policymakers to mainstream statistics in national development priorities and MTEFs.

### XIII. Appendix IV — GDDS/PRSP Module: Improving planning and execution of statistical reforms using the GDDS
- Expected output:
  - A medium-term revolving plan for improvement in statistics integrated with GDDS plans for improvement and into the PRSP, Statistical Master Plan (SMP), NSDS, and/or other committed, funded multiyear statistical improvement program.
  - Facilitate monitoring of the PRS and support national policymaking through enhanced data transparency (national website, advance release calendar).
- Module rationale and focus:
  - Negotiated, committed, funded multiyear statistical plans make a stronger business case for TA and funding and should be consistent with PRS or comprehensive national development plan.
  - Module focuses on developing a GDDS-based plan with government and external support and creating a national data page and advance release calendar.
- Participating countries: Lesotho, Malawi, Seychelles, Sudan, and Zambia.
- Capacity requirements:
  - Revolving plans require a description and periodic update of current state and a set of planned tasks achieving well-defined objectives.
  - Internet-based dissemination requires an agency website, structured data page, and coordinating agency to ensure timely updates.
  - Human resources: technical statisticians/economists, statistical agency managers, module manager/consultants, local IT specialists.
- Planned execution:
  - Initial regional workshop planned for May 2007 (overview of GDDS framework, linkages, and designing/updating statistical business plans).
  - Follow-up TA missions (typical 2–3 missions per country) to update GDDS plans and create publicly available data with advance release notices.
  - Closing workshop to confirm outputs and identify common problems.
- Template for costing and integration into the MTEF:
  - Template columns: Cost (In thousands of U.S. dollars); Internal Financing (National Budget); External Financing (Aggregate of Donors' Contributions); Financing Gap (= Cost - Internal Financing - External Financing).
  - Years labeled 2006, 2007, 2008, 2009 and totals, with numeric placeholders "0" in source template.
  - Template covers domains including national accounts; industrial production index; price indices; labor market indicators; public sector operations and fiscal items; financial corporations surveys; balance of payments and external accounts; population and census; education; health; socio-demographic/poverty; statistical agency; central bank; ministry of finance; other governmental agencies.

*Source: MAINSTREAMING STATISTICS IN THE PRS APPROACH TO PROVIDE FOR MORE EFFECTIVE TECHNICAL ASSISTANCE: SOME EXPERIENCE AT THE IMF (selected excerpts). PDF: _wp07255.*

### 1.     Adequacy of Resources for Statistical Production in PRGF-Eligible Countries .............20

### 1.     Adequacy of Resources for Statistical Production in PRGF-Eligible Countries

### I. Introduction — core argument
- The PRS approach has emerged as a powerful vehicle for mobilizing nationally owned efforts and resources to grow out of poverty, but it "still lags in its capacity to monitor these desirable objectives effectively."
- A root cause is that developing institutional statistical capacity to permit evidence-based monitoring of PRSP goals has not been integral to, and therefore has not moved in step with, advances in PRSP design and implementation.
- Integrating the PRS approach and statistical development strategies could provide significant synergies:
  - Improve monitoring of PRSP goals.
  - Enhance effectiveness of statistical capacity building.
  - Facilitate costing of essential statistical reforms and their incorporation into the medium-term expenditure framework (MTEF).
- Mainstreaming statistical strategies into national development plans should:
  - Enhance national priority for statistical reforms.
  - Provide a basis for costing reforms for inclusion in the MTEF.
  - Create an environment conducive to sustained transfer of expertise to local officials and improve technical assistance (TA) effectiveness.

### II. Development strategies, PRS approach, and the demand for data — analysis and facts
- Major international initiatives shaping demand for statistics (as summarized in Box 1):
  - PRSP introduced September 1999.
  - PRGF launched September 1999.
  - Millennium Development Goals established September 2000.
  - Monterrey Consensus March 2002.
  - Paris Declaration on Aid Effectiveness March 2005.
- As of July 2007:
  - "45 countries had prepared PRSPs, while 12 countries had prepared interim PRSPs."
  - "Eleven countries comprising Benin, Burkina Faso, Ghana, Madagascar, Mauritania, Mozambique, Nicaragua, Senegal, Tanzania, Uganda, and Vietnam had already implemented their original PRSPs and adopted a second-generation PRSP."
- The PRS approach and related development strategies require substantial macroeconomic and sociodemographic statistics compiled largely by LICs.
- The Paris Declaration and related initiatives increased emphasis on effective monitoring, creating a second wave of data and information requirements to:
  - Establish benchmarks against which to measure progress.
  - Provide intermediate markers to quantify changes over time.
- The increase in data demand exacerbates pressure on LICs' statistical systems, which are resource-constrained and must undertake extensive surveys and censuses (e.g., poverty, gender, household income and expenditure, sectoral surveys) to produce internationally comparable, high-quality, and timely datasets.
- Debt-relief initiatives (HIPC, Enhanced HIPC, MDRI) and associated debt sustainability exercises and documentation generate additional significant data requirements for LICs.

### III. Evaluations and common conclusions — findings from assessments
- Multiple evaluations (IMF Independent Evaluation Office; joint Bank/Fund reviews; DFID/World Bank staff review of 12 countries) reached broadly similar conclusions:
  - Some progress has been made in mainstreaming monitoring into PRSPs, but "much remains to be done" to integrate monitoring systems with policy analysis and decision making.
  - Needs differ across countries; Africa faces "a particularly more difficult challenge in terms of a lower starting point and the progress made thus far."
  - Linking PRSPs to the budget process, particularly the MTEF, is critical and generally weak; appropriate costing and prioritization for resource allocation are needed.
  - Capacity building for national institutions is essential; avoid duplication of statistical systems and ensure harmonization with donor requirements and procedures.
- Specific findings from the IMF Independent Evaluation Office (Box 2):
  - PRSPs focus mainly on composition of public expenditure, especially social sector spending, with "much less emphasis on other aspects of a broader strategy to encourage poverty-reducing growth."
  - "Operational value of PRSPs is often limited because of the still rudimentary nature of most costing and prioritization...." Capacity constraints have been a severe impediment.
  - PRSPs that meet original goals require considerable technical and analytical capacities and financial support; nothing in current settings ensures capacity-strengthening priorities will be addressed or clearly linked to lending decisions.
  - Analytic bases of PRSPs are typically weak, notably the macroeconomic framework and policies to promote growth; insufficient prioritization, inadequate costing, and a tendency to avoid controversial structural reform issues limit PRSPs' strategic value.
  - Indicators and monitoring arrangements in PRSPs often "far exceed the underlying data capacity to collect and analyze the underlying data" — institutionalizing such capacity is resource-intensive and will take many years.
  - Indicators are typically better defined for health and education than for areas where inputs or process-based indicators dominate or where indicators are lacking (e.g., structural reforms or governance).
  - More than half of PRSPs initially lacked links to the budget and MTEF; where links existed on paper, their effectiveness was often weakened by the MTEF's weak connection to the actually implemented budget.
  - Joint Staff Assessment papers identified costing, financing, and prioritization as main weaknesses in two thirds of 23 cases; costing is frequently partial and rudimentary, and over a third of PRSPs lack a financing plan and/or a prioritized action plan.
  - Obstacles to mainstreaming poverty and social impact analysis most often cited were data limitations and national capacity constraints, though some assessment is possible even in countries with limited data.

### IV. Policy implications and operational recommendations (as discussed)
- Prioritize integration of statistical capacity building into PRSP formulation and implementation to:
  - Ensure availability of data to monitor progress and inform policies.
  - Enable costing of statistical reforms for inclusion in MTEF and budgets.
  - Improve effectiveness of technical assistance by embedding reforms within national planning and budgeting processes.
- Strengthen links between PRSPs and budget/MTEF processes with explicit costing and prioritization to enhance resource allocation and implementation feasibility.
- Avoid duplication of statistical systems and harmonize donor requirements to reduce fragmentation and increase efficiency of capacity building.
- Recognize that institutionalizing the data systems and analytical capacity required will be resource-intensive and multi-year; plan for sustained support and realistic timetables.

*Source: MAINSTREAMING STATISTICS IN THE PRS APPROACH TO PROVIDE FOR MORE EFFECTIVE TECHNICAL ASSISTANCE: SOME EXPERIENCE AT THE IMF (selected excerpts).*

### Box 3. Essential Features and Issues in PRSP Monitoring

### Box 3. Essential Features and Issues in PRSP Monitoring (Based on a 12-Country Experience)

### Purpose and role of a PRS monitoring system
- The development of a monitoring system is critical to a successful PRS. Such a system is intended both as a way of ensuring continuous improvement of the PRS and as an instrument of influencing the nature of the development policy process by making it more evidence-based and results-oriented.

### Scope: what the system should track and how
- The system should track overall progress in poverty reduction against national targets and international measures of development success, such as MDGs, through the periodic measurement of selected indicators.
- This focuses on monitoring impact indicators and is accomplished by using administrative data as well as surveys, censuses, and quantitative and qualitative data and is usually led by the national statistics agencies.

### Implementation experience and challenges
- The case studies demonstrate that progress in establishing effective PRS monitoring systems has been limited.
- Few systems have created functioning links between monitoring and decision making.
- Organizing coordinated monitoring systems and ensuring that monitoring data are used in the policy process are both proving major practical challenges.

### Linking outcomes to resources and expenditure tracking
- Information on poverty outcomes and implementation can be used only to improve strategies and intervention when these outcomes are associated with cost and resource requirements.
- Expenditure tracking depends upon parallel progress in budget and public expenditure management reforms and availability of quality and timely data.

### Role and resourcing of national statistical agencies
- Involving national statistical agencies is important because they are often the relatively most institutionally advanced elements in PRS monitoring systems.
- The systems arrangement must ensure complementarity with existing systems and statistical planning so as to avoid duplication.
- PRS monitoring systems should ensure that statistics agencies have sufficient resources and mandates to play their role in setting standards, undertaking the requisite surveys and censuses, providing technical assistance, and building the capacity of other national agencies.
- This may help increase the compatibility and complementarity of the data supplied by numerous agencies.

### Donor alignment and its limits
- The alignment of donor monitoring and reporting requirements around the national PRS monitoring systems remains at an early stage of development.
- Most donors do not seem to find annual progress reports sufficient for their own accountability and management purposes both because of quality concerns.
- Therefore donors tend to incorporate a separate monitoring and evaluation system in each of their individual projects leading to duplication of efforts and spreading resources thinly.

### Design considerations and funding modalities
- Care should be taken in designing a PRS monitoring system to ensure complementarity with the development of the statistical systems.
- In practice, this lack of complementarity may be partly the result of the existing funding modalities for statistical systems.
- National statistical agencies tend to prioritize statistical operations for which donor funding is readily available, leaving little time for other functions.
- To remedy this, donors may need to consider more flexible ways of supporting the institutional development of national statistics agencies, such as through basket funding.

### Building demand and linking monitoring to the budget process
- Effective systems for monitoring a PRS must build demand for monitoring while organizing the supply side.
- Unless decision makers actively seek evidence to support policymaking and program management, monitoring practices are unlikely to hold across government administration.
- Creating a link between the PRS and the budget process is a critical objective for the PRS monitoring system.
- The need to access public resources creates powerful incentives across all public agencies and provides the most promising hook for creating demand for effective monitoring.
- This is more readily accomplished in countries that have successfully introduced an MTEF.
- While the PRS sets down the general objectives and priorities, it is usually the MTEF that provides the framework within which explicit spending choices and trade-offs are made; it therefore represents the ideal opportunity to use monitoring information.

*Source: Bedi and others, 2006.*

### Box 5. Select Major Statistical Development Initiatives

### Box 5. Select Major Statistical Development Initiatives

### Major initiatives and their objectives
- Special Data Dissemination Standard (SDDS) — 1996
  - Launched by the IMF to set internationally accepted standards for emerging economies to provide quality and timely economic and financial data to markets.
  - Voluntary subscription with requirements to disseminate metadata and a broad range of economic and financial data on the national data dissemination page.
  - Data dissemination is based on advance release calendars and meets specified periodicity and timeliness requirements. The IMF monitors SDDS requirements.
- General Data Dissemination System (GDDS) — 1997
  - Launched by the IMF to help countries without access to international capital markets adopt a holistic approach to developing statistical systems.
  - Voluntary participation; participants expected to disseminate metadata including plans for improvement for specified economic, financial, and sociodemographic data categories to meet suggested coverage, periodicity, and timeliness.
- PARIS21 (Partnership in Statistics Development in the 21st Century) — November 1999
  - Founded by OECD, World Bank, European Commission, IMF, and United Nations to act as a catalyst for promoting evidence-based policymaking and monitoring, especially in developing countries.
  - Focuses on promoting high-quality statistics, making data meaningful, and fostering dialogue among producers and users via events, country-based activities, regional workshops, and task teams.
- International Standards and Codes (including DQAF and ROSCs) — 2000
  - Developed by several international organizations to promote governance, transparency, and sound economic policies.
  - IMF collaborates to prepare Reports on the Observance of Standards and Codes (ROSCs), including data ROSCs that assess data quality using the Data Quality Assessment Framework (DQAF) and either the GDDS or the SDDS.
  - DQAF developed by the IMF in July 2001 (updated July 2003) with prerequisites for quality and five dimensions: assurances of integrity; methodological soundness; accuracy and reliability; serviceability; and accessibility.
- Marrakech Action Plan for Statistics (MAPS) — February 2004
  - Adopted actions include:
    - mainstreaming strategic planning of statistical development strategies for all low-income countries by 2006;
    - undertaking urgent improvements needed for MDG monitoring by 2005;
    - increasing financing for statistical capacity building.
- National Strategy for the Development of Statistics (NSDS) — 2004
  - Major MAPS component designed to provide a strategic framework for developing relevant poverty-focused statistics.
  - NSDS approach builds on initiatives such as the GDDS and borrows from PRS processes; input-oriented and broader (infrastructure, surveys, administrative data, long-term training, data demand/use).

### Links among standards, frameworks, and macroeconomic statistics
- Four main sets of macroeconomic statistics viewed as an integral system: national accounts; balance of payments and international investment position; monetary and financial; and government finance statistics.
- Standards anchored in the System of National Accounts 1993 (1993 SNA) as the overarching conceptual framework.
- SDDS/GDDS dissemination initiatives closely linked with the DQAF and the data module ROSC process; DQAF extended dissemination standards to a comprehensive basis for assessing data quality.
- GDDS includes sociodemographic datasets to reflect their importance for likely GDDS participants and to avoid skewing resources away from social data. SDDS does not include sociodemographic data.

### Convergence of statistical and development strategies
- Trend toward mainstreaming statistical strategies into development strategies (e.g., PRS approach) driven by:
  - need to effectively monitor PRS and MDG targets; and
  - TA providers’ frustration with lack of priority and funding for statistical reforms absent clear links to national priorities.
- Paris Declaration and international roundtables (e.g., Hanoi, February 2007) emphasize ownership, alignment, harmonization, managing for results, and mutual accountability, with implications for mainstreaming statistical strategies into national development strategies and MTEFs.
- Proposal (World Bank, PARIS21, DFID paper) to treat statistical activities as a "sector" and employ a systemwide approach (SWAp-equivalent) to harmonize donor actions, align interventions with national needs, and scale up interventions within a predictable program of support.
- NSDS provides an input-oriented, broader framework that aligns with development banks’ and donors’ mandates and attracts increased funding (e.g., STATCAP, regional development banks).

### Constraints to effective statistical technical assistance (TA)
- Low-income countries (LICs) often lack financial resources, information technology, and skilled manpower to design and implement statistical reforms; resource constraints are emphasized in the DQAF (element 0.2 and source data element 3.1).
- Data ROSC findings for PRGF-eligible countries indicate resources are a major factor impeding data quality, with the most severe impacts in government finance statistics and national accounts, followed by prices and balance of payments.
- Specific operational constraints:
  - Decentralization has increased the number of autonomous agencies and local governments, complicating coverage and regular reporting (examples: over 70 units in Sierra Leone; Kenya identifies 83 autonomous agencies).
  - Donor-funded projects implemented by autonomous agencies can undermeasure central government capital formation.
  - Abolition of exchange controls reduced administrative source data for balance of payments; increasing services and private financial flows require more regular enterprise and other surveys.

### Data on adequacy of resources for statistical production (PRGF-eligible countries)
Source: DQAF-based data ROSCs conducted in 22 PRGF-eligible countries since 2001.

- Number of countries with Adequate Resources vs Inadequate Resources:
  - National accounts: 2 Adequate, 20 Inadequate
  - Consumer prices: 3 Adequate, 15 Inadequate
  - Producer prices: 3 Adequate, 8 Inadequate
  - Government finance statistics: 1 Adequate, 21 Inadequate
  - Money and financial statistics: 13 Adequate, 8 Inadequate
  - Balance of payments: 6 Adequate, 16 Inadequate
- Percent of Total (Adequate vs Inadequate):
  - National accounts: 9.1 Adequate, 90.9 Inadequate
  - Consumer prices: 16.7 Adequate, 83.3 Inadequate
  - Producer prices: 27.3 Adequate, 72.7 Inadequate
  - Government finance statistics: 4.5 Adequate, 95.5 Inadequate
  - Money and financial statistics: 61.9 Adequate, 38.1 Inadequate
  - Balance of payments: 27.3 Adequate, 72.7 Inadequate
- Memorandum item:
  - Weighted average (percent of total): 24.1 Adequate, 75.9 Inadequate
- Notes:
  - In some cases, data ROSCs exclude assessments for certain datasets.
  - Rating of “Observed” indicates resources commensurate with tasks.
  - Ratings of “Largely Observed,” “Largely Not Observed,” and “Not Observed” denote some, significant, and substantial insufficiency, respectively.

### Findings from GDDS review and regional patterns
- Preliminary findings from a 10-year GDDS review:
  - Readiness to subscribe to SDDS appears more problematic in Africa and the Western Hemisphere, which are farthest from SDDS requirements in real and external data timeliness and periodicity.
  - Uneven progress across macroeconomic datasets reflects that real and external sectors rely on expensive and resource-intensive source data.
  - Regional deviations in compliance with SDDS requirements may result from differences in availability of resources to absorb capacity-building TA.
- Participation counts: To date, 94 countries have participated in the GDDS, 6 of which went on to become subscribers to the SDDS, leaving 88 countries as current participants.

### IMF, donors, and coordination of TA delivery
- Donors and agencies have increased coordination to mobilize aid for effective and sustainable TA; statistical TA spans institution/infrastructure support (censuses, surveys, administrative systems) and data quality work.
- IMF focuses TA on data quality issues and is dependent on donor-provided financial and other inputs to build foundations for effective TA.
- Recognized need to mainstream statistics into PRS and MTEF to secure national priority and medium-term funding for statistical reforms.
- IMF country-level experiments and projects:
  - Anglophone Africa GDDS project (since 2002; IMF and World Bank executing; funded by DFID) prepared metadata and plans; 13 of original 14 countries joined the GDDS.
  - Second phase GDDS project (2006–09) launched September 2006 incorporates modules delivering TA via workshops and expert visits; one module assists five countries (Lesotho, Malawi, Seychelles, Sudan, and Zambia) to integrate GDDS plans into PRSPs.
  - Sierra Leone pilot: integrated GDDS plans into PRSP with a medium-term budget for reforms but faced implementation limits due to staff turnover, domestic budget constraints, and donors not being part of the exercise.
  - Zambia (2006): assistance helped integrate cost of macroeconomic statistical reforms into National Development Plan (NDP, 2006–2011); sociodemographic reforms had been costed and reflected in associated MTEF.
  - IMF provided TA to Burundi using a prototype costing framework (ISTEBU) as a basis for costed comprehensive reforms covering macroeconomic and sociodemographic datasets.

### Analysis and policy implications highlighted in the source
- Statistical capacity building requires alignment with national development priorities (PRSPs, MTEFs) to secure funding and priority.
- A systemwide approach to statistics (analogous to SWAp) can harmonize donor actions, align with national strategies (NSDS), and scale up interventions in predictable, monitored programs.
- Sustained improvements in macroeconomic and sociodemographic statistics depend on coordinated donor funding for infrastructure (censuses, surveys, administrative systems) and targeted TA for data quality and methodological adoption (e.g., GFSM 2001, COFOG).
- Addressing resource shortfalls is critical for improving data needed to monitor fiscal performance, PRS benchmarks, and MDG progress.

*Source: Box 5 from the provided IMF content unit.*

### Appendix V). Assistance was provided to the Democratic Republic of the Congo with

### _wp07255 - Appendix V). Assistance was provided to the Democratic Republic of the Congo with

### Pilot efforts to mainstream statistics into the PRS approach (Africa)
- Joint missions with PARIS21 in 2006 assisted Burkina Faso and Senegal to:
  - integrate their GDDS and other plans for statistical reform into the PRSP, and
  - cost them for incorporation in the MTEF.
- Early pilot activities include identifying existing good practices and selecting a group of countries where SWAps may be appropriate and more intensive donor effort is needed.
- PARIS21 envisages a greater advocacy role with a SWAp for statistics as a follow-up to the Third Roundtable meeting in Hanoi.
- It is still too early to assess the full impact of these pilot efforts in Africa; success will require:
  - greater acceptance of mainstreaming statistics into the PRS approach,
  - broader participation by donors and country authorities,
  - practical steps informed by experience from pilot cases.

### VI. Realistic budget for statistical reforms
- Key principles:
  - Resource claims for statistical reforms must incorporate prudence and realism.
  - The proposed scope of statistical reforms should be tempered to fit the existing environment.
  - An incremental and well-phased design of reforms may ensure better sustainability than wholesale introduction of new state-of-the-art systems.
  - Components and total cost of reforms need to be developed keeping in mind overall resource constraints.
- Roles and processes:
  - The GDDS/NSDS coordinator, working with all statistical agencies and experts in costing reforms, should ensure funding for overall reforms is comprehensive and appropriately phased over the period of the PRSP and the MTEF.
  - Early and continuous coordination with donors and the ministry of finance is key to maintaining feasible reform cost proposals for MTEF inputs.
- Practical considerations:
  - Occasional critical but lumpy projects (e.g., population and housing or agricultural censuses and setting up autonomous national statistical agencies) will arise; with adequate advance timing and phased donor and government support, these can be fitted within the MTEF.
  - Adopting a systemwide approach to medium-term budgeting for statistics could emulate successful practices in social sectors that use annual public expenditure reviews (PERs) to provide regular updates for the MTEF.
- Historical caution (footnote 24):
  - Experience with some early versions of the NSDS showed overly ambitious infrastructural projects and reforms resulted in substantial resource requirements unacceptable to ministries of finance and donors; such setbacks required confidence rebuilding.

### VII. Conclusions — findings and implications
- Since the late 1990s, efforts by development practitioners, national authorities, donors, and TA providers have converged to address weak statistical capacity in developing countries within poverty reduction frameworks.
- The PRS approach and the Monterrey Consensus changed interactions among partner countries, donors, and development partners, emphasizing:
  - broad public participation,
  - national ownership,
  - specific objectives (the MDGs) to address poverty.
- Donors committed to increasing assistance within frameworks that channel resources through developing country institutions via improved harmonization and accountability to enhance effectiveness of financial and TA resources.
- Parallel efforts developed broad-based statistical strategies to meet substantially increased demand for data to support poverty reduction and monitoring.
- Main conclusions on resources and TA:
  - Emerging evidence indicates resources are critical to the effectiveness of TA, especially for macroeconomic datasets in national accounts, prices, and balance of payments, due to high dependence on surveys and censuses.
  - Resources are also a constraint for government finance statistics, linked to decentralization and limited capacity to compile and disseminate data from autonomous central government agencies and local governments.
  - Addressing these problems requires increased resources and enhanced coordination among partner country statistical agencies, donors, and TA providers—an important but not necessarily sufficient condition for more effective TA.
- Implementation and advocacy:
  - Implementing the proposed approach will take time; advocacy is key because statistics have public good characteristics and significant market failure.
  - Building public awareness in LICs and among development partners is crucial to enhance priority and funding for statistical development within the PRS approach and MTEFs.
  - Comprehensive listing and costing followed by prioritization of statistical reforms are central and require leadership by partner country authorities supported by donors and the IMF.
  - Selecting countries to pilot endeavors, including the SWAp, should provide best practices to guide future work.
  - Statisticians and TA providers should formulate comprehensive but realistic reform budgets and are advised to emulate annual sector PERs proven successful in other PRS sectors.
- Africa-specific note:
  - Africa faces particularly challenging situations in both starting position and relative effort needed to mobilize requisite resources for statistical capacity.
  - While development partner support is important, success depends crucially on local ownership and leading roles by country authorities and policymakers to mainstream statistics in national development priorities and MTEFs to reduce poverty.

### Appendix II — Data Quality Assessment Framework (July 2003 Framework) — selected elements
- Prerequisites of quality (0):
  - 0.1 Legal and institutional environment: indicators 0.1.1 through 0.1.4 (e.g., responsibility clearly specified; data sharing adequate; confidentiality; legal mandate).
  - 0.2 Resources: indicators 0.2.1 and 0.2.2 (staff, facilities, computing, financing commensurate; measures for efficient use).
  - 0.3 Relevance: indicator 0.3.1 (monitor relevance and practical utility).
  - 0.4 Other quality management: indicators 0.4.1 through 0.4.3 (processes to focus on, monitor, and deal with quality).
- Assurances of integrity (1):
  - 1.1 Professionalism: indicators 1.1.1 through 1.1.3 (impartiality, source/technique choices guided by statistics, entitlement to comment on misuse).
  - 1.2 Transparency: indicators 1.2.1 through 1.2.4 (terms and conditions available; internal access identified; products identified; advance notice of major changes).
  - 1.3 Ethical standards: indicator 1.3.1 (guidelines for staff behavior).
- Methodological soundness (2):
  - 2.1 Concepts and definitions: 2.1.1 (follow international standards).
  - 2.2 Scope: 2.2.1 (scope consistent with international standards).
  - 2.3 Classification/sectorization: 2.3.1 (consistent with international standards).
  - 2.4 Basis for recording: 2.4.1 through 2.4.3 (market prices, accrual basis, grossing/netting procedures consistent).
- Accuracy and reliability (3):
  - 3.1 Source data: 3.1.1 through 3.1.3 (comprehensive collection programs; source data approximate required definitions; timeliness).
  - 3.2 Assessment of source data: 3.2.1 (routine assessment of censuses, surveys, administrative records).
  - 3.3 Statistical techniques: 3.3.1 and 3.3.2 (sound statistical techniques for compilation and other procedures).
  - 3.4 Assessment and validation: 3.4.1 through 3.4.3 (validation, assessment of discrepancies, investigations).
  - 3.5 Revision studies: 3.5.1 (routine studies and analyses of revisions).
- Serviceability (4):
  - 4.1 Periodicity and timeliness: 4.1.1 and 4.1.2 (follow dissemination standards).
  - 4.2 Consistency: 4.2.1 through 4.2.3 (consistency within dataset, over time, and reconcilable with other sources).
  - 4.3 Revision policy and practice: 4.3.1 through 4.3.3 (regular transparent schedule, identification of preliminary/revised data, public revision studies).
- Accessibility (5):
  - 5.1 Data accessibility: 5.1.1 through 5.1.5 (presentation, dissemination media, preannounced release schedule, impartial availability, data on request).
  - 5.2 Metadata accessibility: 5.2.1 and 5.2.2 (documentation available and adapted to audience).
  - 5.3 Assistance to users: 5.3.1 and 5.3.2 (publicized contact points; catalogs of publications and services).

### Appendix III — GDDS-Anglophone Africa DFID Project (overview and outcomes)
- Project sponsors and execution:
  - Sponsored by DFID and executed jointly by the IMF and the World Bank.
- Development objective:
  - Ensure more effective design, implementation, and monitoring of macroeconomic policy and poverty reduction strategies by improving quality of key macroeconomic and sociodemographic statistics.
- Phase 1 (2001–2006):
  - Involved 15 countries: Botswana, Eritrea, Ethiopia, Ghana, Kenya, Lesotho, Liberia, Malawi, Namibia, Nigeria, Sierra Leone, Sudan, Swaziland, Zambia, and Zimbabwe.
  - Project addressed three key areas:
    - quality of data;
    - development plans for a statistical system (detailed diagnosis, plan identifying inputs and actions, tracking progress); and
    - dissemination of data.
  - Outcomes during Phase 1 included effective use of technical assistance, promoted closer contact and coordination among agencies producing statistics, GDDS workshops to bring together users and providers, and promotion of regional cooperation and south–south cooperation.
- Phase 2: “GDDS Project Phase 2: Modules for Strengthening Statistics” (2006–2009):
  - DFID agreed to sponsor an expanded successor project following overwhelming endorsement by participating countries to continue the project.
  - Expanded to include seven more countries: The Gambia, Mauritius, Mozambique, Seychelles, South Africa, Tanzania, and Uganda.
  - Focus and approach:
    - Introduce internationally accepted methodologies and good practices.
    - Focus on results and regional interaction through defined technical assistance modules that can be planned, implemented, and assessed in a coordinated manner.
    - Sustained capacity building through measurable improvements in agreed areas (modules).
    - Assure mutual commitment to results and ownership from participating countries and TA providers.
    - Results-driven TA delivery includes expert visits, hands-on training, and country group workshops to share experiences and best practices.
    - Encourage alignment of activities to national priorities, enhanced coordination, effective use of intra-agency arrangements, and close work with subregional and regional agencies and other TA providers.

*Source: _wp07255 - Appendix V). Assistance was provided to the Democratic Republic of the Congo with (PDF).*

### Appendix IV. GDDS/PRSP Module: Improving Planning and Execution of Statistical

### Appendix IV. GDDS/PRSP Module: Improving Planning and Execution of Statistical Reforms Using the GDDS

### Expected output
- A medium-term revolving plan for improvement in statistics:
  - Integrated with the General Data Dissemination System (GDDS) plans for improvement, which are posted on the IMF’s Dissemination Standards Bulletin Board (DSBB).
  - Integrated into the Poverty Reduction Strategy Paper (PRSP), Statistical Master Plan (SMP), National Strategy for Development of Statistics (NSDS), and/or other committed, funded multiyear statistical improvement program.
  - Facilitating the monitoring of the PRS and supporting national policymaking through the enhancement of data transparency by disseminating the data on a national website and developing an advance release calendar.

### Context and purpose of the module
- Rationale:
  - African countries increasingly have access to technical assistance (TA) from national governments and providers such as DFID, aid agencies of other countries, AfDB, PARIS21, and the World Bank, but often lack a framework for negotiating a committed, funded statistical business plan with a good chance of execution over the medium term.
  - Committed, funded multiyear statistical plans require agreement between the government and TA providers as a group on objectives and broad modalities, consistent with the PRS or comprehensive national development plan.
  - Such negotiated plans make a stronger business argument for attracting TA and funding, and are reinforced by enhancing data transparency through internet dissemination.
- The module focuses on:
  1. Developing a good plan for statistics within an enhanced GDDS plans for improvement framework that enjoys support from decision makers in national governments and from external providers of technical and financial resources.
  2. Creating a national data page available for use by national governments, other policymakers, and external providers of technical and financial resources and an advance release calendar.

- Participating countries (note in text): Lesotho, Malawi, Seychelles, Sudan, and Zambia.

### Capacity requirements for participating countries
- Revolving plans for improvement require:
  1. A description and periodic update of the existing state of affairs; and
  2. A set of planned tasks collectively achieving a set of well-defined objectives.
- Internet-based data dissemination requires:
  1. An agency website;
  2. A structured data page; and
  3. A coordinating agency/body to ensure the timely update of the website.
- Human resource and institutional roles:
  - Technical staff—statisticians (or economists) having technical and methodological knowledge—are required to draft and update GDDS metadata.
  - Statistical agency managers are required to negotiate, with the assistance, as needed, of the module manager and consultants, overall objectives with government decision makers and external providers of funding and assistance.
  - Statisticians and economists work out the steps (plans for improvement) each reform scenario requires; the metadata are the product of a one-time periodic process, but the planning process is iterative.
  - The website initiative needs support from local IT specialists.

### Planned execution of the module
- Initial regional workshop (planned for May 2007) to provide:
  - An overview of the elements of the new GDDS developmental framework and the enhanced GDDS plans for improvement.
  - An overview of linkages between the enhanced GDDS plans for improvement and the World Bank’s SMP and PARIS21’s NSDS.
  - A stylized process of designing and updating the statistical business plan while negotiating its funding over the medium term through multilateral meetings including statistical agencies and external providers of assistance and funding.
  - An opportunity for participants to discuss the advantages of data transparency and the use of the internet to disseminate data as a service to the public.
- Follow-up technical assistance:
  - Countries will receive technical assistance missions to help address priority issues identified in the workshop.
  - The module manager will organize technical assistance to update GDDS plans for improvement in consultation with the government and to create a publicly available set of data along with advance notice on when these data will be released.
  - The end product is a set of data available on the Internet to monitor the progress in the PRS, support national policymaking, and GDDS plans for improvement owned by the country, with the understanding and concurrence of external providers, that is “in the critical path” of the process for monitoring and evaluation of project execution.
  - The plans move into the critical path through, for example, incorporation into the medium-term public expenditure plan, the PRSP, and the SMP, as these are prerequisites for various types of statistical program financing.
- Typical mission profile and cross-country learning:
  - Two or three missions per country are the norm in this module.
  - The module will benefit from commonality between countries, so that experiences from one can be applied to another, both through the technical assistance mission and through direct contact between country agencies.
- Closing workshop:
  - A closing workshop will be held at the end of the module, confirming the achievement of the planned outputs and identifying common problems.
  - The workshop will conclude with countries discussing future improvements.

### Template for costing and integration into the MTEF (overview)
- A template is provided for costing and integrating a Statistical Development Action Plan into the MTEF with columns labeled:
  - Cost (In thousands of U.S. dollars)
  - Internal Financing (National Budget)
  - External Financing (Aggregate of Donors' Contributions)
  - Financing Gap (= Cost - Internal Financing - External Financing)
- The template organizes statistical sector items and data categories/governmental agencies across years labeled 2006, 2007, 2008, 2009 and totals.
- The template covers a wide set of statistical domains including (as listed in the template):
  - National accounts; Industrial production index (Manufacturing; Primary commodity; Agricultural); Price indices (Real; Consumer price index; Producer price index); Labor market indicators (Employment; Unemployment; Wages/salaries); Public sector operations (Budgetary central government; Extrabudgetary agencies; Social security; Consolidated central government; State governments; Local governments; Nonfinancial public sector; Public sector); Fiscal (Public sector debt; General improvements for public sector debt; Budgetary central government debt; State and local government debt; General government debt; Nonfinancial public sector corporations debt); Financial corporations survey (Depository corporations survey; Central bank survey; Other depository corporations survey; Other financial corporations survey; General improvements for financial corporations); Financial (Interest rates; Stock market); Balance of payments (Merchandise trade; Services; Income; Current transfers; Capital account; General improvements for the balance of payments); External (Financial account; International investment position; General improvements for international investment position; External debt; International reserves; Other indicators of the international investment position); Exchange rate; Population (Population other than census; Census); Education; Health; Socio-demographic / Poverty; Statistical agency; Central bank; Ministry of finance; Other governmental agencies.
- The template as shown in the source contains numeric placeholders of "0" across the year columns for the listed items and agencies.

*Source: Appendix IV. GDDS/PRSP Module: Improving Planning and Execution of Statistical Reforms Using the GDDS (IMF Statistics Department).*

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