## D4D Fund — Work Plan (June 2018)

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### Relevance of macroeconomic data for SDG monitoring
- More than one-third of SDG indicators relate to macroeconomic aggregates.
- Improving macroeconomic statistics increases the reliability and cross-country comparability of SDG indicators over time.
- Enhancing GDP measurement—e.g., by better capturing the informal economy—directly improves reliability and comparability of SDG indicators that depend on the size of the economy.
- Digitalization and new data sources present measurement challenges for national accounts and price indexes, with implications for growth, productivity, inflation, and welfare measurement.
- The D4D Fund will contribute under Module M1 to enhance reliability and comparability of macroeconomic statistics and will foster country reporting under the Financial Access Survey (Module M2) to support the SDG financial inclusion indicator.

### Module M1 — Addressing Data Needs and Quality Concerns: strategy and scope
- Module M1 comprises three submodules: Real Sector Statistics (RSS), External Sector Statistics (ESS), and Fiscal and Debt Reporting (GFS/PSDS).
- Strategic sequencing and geographic focus:
  - Prioritize Fiscal and Debt Reporting, with particular emphasis on public sector debt statistics (PSDS) on a fast track to reach broad coverage and respond to increased debt vulnerabilities.
  - Launch ESS at a slower pace, with initial focus on the Middle Eastern region.
- CD approach core elements:
  - Mix of mutually reinforcing TA and training with peer-to-peer learning and an economic rationale for interventions.
  - Clear baseline identification, country-owned work plans, and country-specific log frames incorporated into IMF Results-Based Monitoring (RBM).
  - CD tailored to be practical, policy-oriented, fit-for-purpose, coordinated with IMF country teams, focused on data dissemination consistent with IMF guidelines, and open to using big data and machine-to-machine readable technology.
- Coordination and complementarities:
  - Coordinate D4D Fund interventions with other IMF CD vehicles (RTACs, FSSF, bilateral projects) and other CD providers; potential for blended resources and shared workshops using field-based infrastructure.

### Module M1 — Real Sector Statistics: Residential Property Price Indices (RPPIs)
- Policy rationale:
  - RPPIs inform macro‑prudential and monetary policy and detect systemic risks from real estate cycles.
- Baseline and coverage:
  - Estimated eight LLMICs (one-tenth) have compiled and disseminated a RPPI.
  - Around ten countries (one-eighth) are currently working on compiling a RPPI.
  - Around four-fifths of eligible countries have no RPPI available.
- Capacity-building objectives and delivery modes:
  - For the one-tenth with basic RPPIs: TA to align with the RPPI Handbook; short-term methodological improvements and longer-term source-data development.
  - For the one-eighth working on RPPI: increase staff capacity, improve source data and compilation methods, and develop capacity for robust methodologies.
  - For the four-fifths without RPPI: regional workshops on source data needs and methodology, with follow-up TA if basic data collection progresses.
- Implementation plan (first 18 months and FY scheduling):
  - Two regional workshops: one for AFR in FY2019 and one for MCD in FY2020.
  - TA missions in six countries; specific TA as follow-ups to workshops and IMF surveillance requests.
  - Selected FY2019–FY2020 CD activities: AFR and MCD workshops; RPPI TA in Vietnam, Mongolia, Indonesia, Bolivia, Bangladesh, and Vietnam again.

### Module M1 — Real Sector Statistics: High-frequency Indicators (HFIs)
- Strategic objectives:
  - HFIs help policy-makers assess cyclical position and adjust fiscal and monetary policy to smooth cyclical swings and reduce volatility.
- Baseline and quantitative targets:
  - Currently about two-thirds of LLMIC compile some type of monthly or quarterly economic activity indicator.
  - Work stream aims:
    - Support at least 10 countries currently not producing HFIs to compile and disseminate an indicator for a significant activity/sector.
    - Assist at least 15 additional countries to strengthen compilation and dissemination of well-defined HFIs.
- Delivery modalities:
  - Two main activities: (i) regional opening workshops to undertake country assessment, define baselines, and develop country-specific work plans; and (ii) support via tailored single-country TA missions (and multi-country TA where synergies exist).
  - Regional workshop schedule:
    - FY2019: two regional opening workshops (one for AFR first group; one in APD), followed by FY2020 events for MCD and a second AFR group.
  - Country-specific TA missions:
    - Expected to be conducted to about 25 targeted countries during the five-year D4D Fund period.
    - During FY19, three two-week potential missions planned; Jordan confirmed; discussions for one AFR and one MCD country.
- Target country groupings (selected):
  - AFR (first group): Ethiopia, Kenya, Rwanda, Tanzania, Uganda, The Gambia, Ghana and Nigeria.
  - APD: Bhutan, Cambodia, India, Indonesia, Lao's Republic, Mongolia, Philippines, Sri Lanka, and Vietnam.
  - MCD: Armenia, Egypt, Kyrgyz Republic, Morocco, Tajikistan, Tunisia, Uzbekistan, and West Bank and Gaza.
  - AFR (second grouping): Burundi, Cabo Verde, Cameroon, Cote d'Ivoire, Madagascar, Mauritania, Mozambique, and Senegal.

### Module M1 — Improved Source Data and Intermediate Statistics
- Aim and priorities:
  - Develop and use source data to compile annual and quarterly GDP estimates and Services Producer Price Indices (SPPIs).
- Expected benefits:
  - Enhanced GDP coverage and accuracy, improved estimates of the informal and digital economy, support for rebasing, improved sectoral decomposition, and better SDG reporting.
- Digital economy focus:
  - Emphasize areas salient in LLMICs such as rapidly growing mobile money services.
  - Assist on price statistics focusing on services; many LLMICs limit price statistics to goods.
- SPPI objective:
  - Support compilation and dissemination of an SPPI to differentiate productivity-driven price changes from general inflationary changes.
  - Around ten countries with large and fast-growing mobile money components are natural SPPI candidates.
- Findings on current practice and baselines:
  - Some one-third of IMF member countries have not rebased national accounts for more than 10 years (best practice: every five year or less).
  - About a quarter of LLMICs use tax data for national accounts compilation but often not fully due to confidentiality, cooperation, or capacity issues.
  - About one-fifth of eligible countries collect regular business survey information.
  - An IMF survey from 2017: about half of LLMICs include estimates for the informal economy; only one-fifth substantiate it through informal sector surveys.
  - Very few LLMICs estimate technological change impacts, explore non-traditional data sources, or compile an SPPI.
- Measurable indicators and country-level targets:
  - Improvements in availability and use of source data; reducing discrepancies between production- and expenditure-based compilations; monitoring rebasing revision sizes; assessing availability of measures for technological change or SPPI.
- Planned FY2019–FY2020 engagements:
  - FY2019: six TA missions on sectoral composition of GDP; five TA missions on source data availability; one regional workshop on non-observed economy estimates; one workshop to assist in developing an SPPI.
  - FY2020: two workshops in AFR and APD on use of source data and informal economy estimates.

### Module M1 — External Sector Statistics (ESS): focus and targets
- Focus and rationale:
  - Improve current and financial accounts of the balance of payments to address gaps in goods, services, income, remittances and investments.
  - Gaps impair reliability of balance of payments statistics and policy use to detect external risks and vulnerabilities.
- Globalization and data sources:
  - Global value chains and big data (e.g., mobile money transactions) require adjustments and offer new sources to improve remittance and trade statistics.
- Strategic objectives and baselines for the five-year period:
  - Improve goods and services statistics in at least 15 countries to better assess global value chains; currently only a quarter of eligible countries report goods for processing and/or merchanting data.
  - Strengthen coverage of financial and remittance flows in at least 15 countries.
  - Address errors and omissions: regional averages of net errors and omissions relative to gross current account flows reported as 1.7-1.9 percent for APD, MCD and WHD; 3.1 percent for AFR; and 1.2 percent for EUR. Except for EUR, more than half of countries in other regions exceeded 1 percent for the indicator.
- Phased CD delivery and prioritization:
  - Activities stepped up in the last three years of the D4D Fund.
  - Current bilateral ESS projects and some RTAC coverage together cover around 44 percent of the LLMICs; initial priority to MCD countries with lesser existing CD coverage.
  - Delivery mix: regional workshops and country TA missions targeting countries with incomplete accounts or large/volatile net errors and omissions.
- First 18 months objective:
  - Deliver one regional workshop and ten country TA missions.
  - First workshop primarily for MCD countries to scope current account source data and compilation issues.
- FY2019 country TA examples:
  - The Gambia: improving data sources for current and financial account compilation.
  - Kenya: improving financial account by addressing source data gaps.
  - Uzbekistan: establishing balance of payments compilation focusing on current account components.
  - Vanuatu: implementing new surveys to capture cross-border transactions and building direct investment statistics.
- FY2020 examples:
  - Madagascar: improving current account by addressing data gaps for unrecorded trade.
  - Uzbekistan: improving financial account by engaging new data sources.
- Targeted countries (selected): Afghanistan, The Gambia, Egypt, Jordan, Kiribati, Kenya, Madagascar, Morocco, The Philippines, Solomon Islands, Tunisia, Uzbekistan, Vanuatu, and West Bank and Gaza.

### Module M1 — Fiscal and Debt Reporting (GFS/PSDS)
- Strategic objectives and rationale:
  - Provide policy-makers with improved high-frequency GFS and comprehensive, timely, and cross-country comparable PSDS to enhance debt sustainability analyses and transparency.
- Current assessment:
  - Survey of 45 Sub‑Saharan African countries: fiscal data of more than 30 countries do not cover activities beyond budgetary central government.
  - Comprehensive stock data to measure indebtedness unavailable in some 40 countries.
- Allocation over five years:
  - About two‑thirds devoted to PSDS (stocks) and one‑third to GFS (flows).
- PSDS objectives and delivery:
  - Improve institutional and instrument coverage, timelines, periodicity, and contingent liabilities in roughly three‑quarters of eligible LLMICs.
  - Organize regional workshops to establish country-owned work plans; follow-up TA missions largely funded by D4D, potentially blended with RTACs and bilateral projects.
  - Country selection based on demand and priority for countries with sharp increases in debt-to-GDP ratios and large PSDS risks.
- CD delivery in an 18‑month period:
  - Five regional PSDS workshops and about 20 TA missions (work split roughly two‑thirds PSDS and one‑third GFS).
  - PSDS workshops: FY2019 two regional PSDS workshops (Anglophone and Lusophone AFR); FY2020 three regional PSDS workshops covering APD, Francophone AFR, and MCD.
  - PSDS technical assistance: about 15 one‑week TA missions planned in the 18‑month period; scale-up to cover about twelve countries in first nine months of FY2020.
- GFS technical assistance:
  - About 5 two‑week TA missions planned in the 18‑month period.
  - FY2019 two‑week GFS TA missions to Comoros and Ghana: Comoros to enable regular TOFE compilation with expanded coverage; Ghana to eliminate internal inconsistencies and compile data on nonfinancial public corporations.
  - First nine months of FY2020: an additional three GFS TA missions planned.

### Module M2 — Financial Access Survey (FAS)
- Aim and relevance:
  - Ensure continued annual production and dissemination of the FAS to provide long time series on financial access and inclusion.
  - FAS is a supply-side financial inclusion database launched in 2009 with close-to-universal country coverage based on administrative data from central banks and other regulators.
- Role in SDG monitoring:
  - FAS provides the monitoring basis for SDG financial inclusion indicator 8.10.1 by contributing two indicators: (i) the number of commercial bank branches and (ii) the number of automated teller machines per 100,000 adults.
  - Strategic objective: continue providing indicators that cover at least 90 percent of the world adult population, with data regularly published on the UN SDG Indicators Global Database.
- Reporting enhancement strategic objectives:
  - Increase reporting of the number of commercial bank institutions from 86 percent in 2017 to 95 percent of the IMF membership by the end of the D4D Fund cycle.
  - Increase gender‑disaggregated data reporting by two‑fold compared to the 2017 benchmark of 28 reporting jurisdictions.
  - Increase by 50 percent the number of economies reporting indicators of innovative channels of financial access compared to the 2017 benchmark of 45 reporting jurisdictions.
- Outputs and delivery:
  - FAS conducted annually with country reporting validated by IMF staff; data disseminated on a rolling basis on the IMF website.
  - Planned regional workshop in Africa in March 2019 targeting Angola, Botswana, Cabo Verde, The Gambia, Ghana, Kenya, Mozambique, Namibia, Nigeria, Rwanda, Swaziland, Uganda, Zambia, and Zimbabwe.
  - Predecessor Asia workshop in September 2018 funded by a bilateral donor.

### Module M3 — Online Learning
- Objective and rollout:
  - Develop and roll out a comprehensive online learning curriculum with free access to high-quality training, including eight fundamental statistics courses (English and up to five other languages).
  - Passing fundamental online courses will become a precondition to participate in face-to-face intermediate and advanced courses.
  - Converting one face-to-face fundamental statistics course into an online course requires around a year.
  - Expected participant completion time: around 6-8 weeks per fundamental course.
  - Post-launch support: interactive sessions with a statistics expert and online forums.
  - Translation to start after one year of online operation; translation to up to five languages dependent on funding.
- Staffing and costs:
  - Planned hires under D4D: two contractual staff to support economists in course development and facilitation.
  - Some services outsourced (filming and editing).
  - Estimated cost per course: around USD 0.75 million, excluding translation.
  - Target: increase STA training reach by at least 50 percent by the end of the D4D Fund period.

### Module M4 — Statistical Information Management
- Objective and pilot activities:
  - Provide advice on statistical information management practices, governance structures, tools, technical standards, and statistical information models to address data management challenges.
  - Pilot workshop with the Central Bank of Kenya in 2017; formal launch readiness for an Economic Data Warehouse (EDW) implementation project at CBK.
  - Planned pilots for Lebanon and Egypt or Tunisia; two additional pilots planned to assess resource intensity and indicator selection.
  - Establish a knowledge base and a practitioner network for peer-to-peer learning.
- FY2019 planned CD activities:
  - Lebanon: structures and standards for automated data exchange.
  - Egypt or Tunisia: governance and data structures for internal data management and dissemination.

### Indicative budget (next 18 months) — totals and module allocations
- Total work program budget (including 7 percent trust fund management fee): USD 6.85 million (Total: USD 6,851,241).
- Subtotal (before TF management fee): USD 6,403,029.
- TF Management Fee (7%): USD 448,212.
- Module-level allocations (Total USD):
  - Module M1 (Addressing Data Needs and Quality Concerns): USD 3.13 million (Total USD 3,123,631)
    - Real Sector Statistics: USD 0.75 million (USD 745,566)
    - External Sector Statistics: USD 0.63 million (USD 628,388)
    - Fiscal and Debt Reporting: USD 1.75 million (USD 1,749,677)
  - Module M2 (Financial Access Survey): USD 1.12 million (USD 1,124,150)
  - Module M3 (Online Learning): USD 1.64 million (USD 1,635,373)
  - Module M4 (Statistical Information Management): USD 0.17 million (USD 169,338)
  - RM Project Manager: USD 0.35 million (USD 350,537)
- Table 10 summary (FY19 / FY20 / Total):
  - Module 1 - Addressing Data Needs and Quality Concerns: 1,089,995 / 2,033,636 / 3,123,631
    - Real Sector Statistics: 216,366 / 529,200 / 745,566
    - External Sector Statistics: 358,864 / 269,524 / 628,388
    - Fiscal and Debt Reporting: 514,765 / 1,234,912 / 1,749,677
  - Module M2: 586,746 / 537,404 / 1,124,150
  - Module M3: 598,680 / 1,036,693 / 1,635,373
  - Module M4: 83,460 / 85,878 / 169,338
  - RM Project Manager: 169,672 / 180,865 / 350,537
  - Sub total: 2,528,553 / 3,874,476 / 6,403,029
  - TF Management Fee (7%): 176,999 / 271,213 / 448,212
  - Total: 2,705,552 / 4,145,689 / 6,851,241
- Table 11 summary (Budget by Activity; FY19 / FY20 / Total):
  - Project Manager: 169,672 / 180,865 / 350,537
  - HQ Staff: 1,061,448 / 1,555,337 / 2,616,785
  - TA missions: 298,462 / 600,783 / 899,245
  - HQ Delivery: 96,845 / 140,810 / 237,655
  - STX: 201,617 / 459,973 / 661,590
  - Workshops: 479,867 / 703,577 / 1,183,444
    - HQ Delivery (workshops): 144,701 / 146,573 / 291,274
    - STX (workshops): 45,166 / 114,534 / 159,700
    - Participants: 290,000 / 442,470 / 732,470
  - Language Services: 70,000 / 261,375 / 331,375
  - Security (officials traveling to a third location): 40,000 / 36,015 / 76,015
  - Exceptional: 105,000 / 117,675 / 222,675
  - STA Project Management: 274,368 / 348,909 / 623,277
  - STA Backstopping: 29,736 / 69,940 / 99,676
  - Sub total: 2,528,553 / 3,874,476 / 6,403,029
  - TF Management Fee (7%): 176,999 / 271,213 / 448,212
  - Total: 2,705,552 / 4,145,689 / 6,851,241

### Fundraising and financial status (as of May 31, 2018)
- Total raised to date: about US$18 million of the US$33 million targeted in the Program Document.
- Specific contributions and pledges:
  - Luxembourg: signed LOU for €4 million (reported as 4.8 million U.S. dollars in the table).
  - Switzerland: pledge CHF 4 million (pending).
  - European Commission: pledge €2 million (pending).
  - The Netherlands: pledge €3.5 million (pending).
  - Korea: pledge US$1.7 million (pending).
  - China: pledge US$1 million (pending).
- Table-level figures (as reported):
  - Under Negotiation Total: 13.2 (in Millions)
  - Grand Total: 18.0 (in Millions)
  - Program Document Budget: 33.1 (in Millions)
  - Funding Gap: 15.1 (in Millions)
- Work plan financing and cash position projections:
  - Steering Committee endorsable work plan of US$ 6.85 million based on available resources, including pledged amounts.
  - Based on current estimated disbursements, the subaccount would have a US$3.16 million balance at the end of calendar year 2019 (the end point of the current D4D Fund work plan).
  - Fund-raising efforts expected to advance in the second half of 2018 as partners secure budgetary allocations; additional partners expected to formalize pledges into signed LOUs.

### Annex I — Strategic logframe: impact, objectives, and indicators
- D4D’s Strategic Objective:
  - Assist LLMICs in strengthening national statistical systems to cope with challenging policy environments, promote transparency and accountability, and offer efficient CD solutions.
  - Impact outcome: More and better data available for decision-makers and analysts to inform economic policies and support SDG monitoring.
  - Key impact indicator domains: improvements across all macroeconomic and financial statistical domains.
  - Data sources for monitoring: NSDPs, IMF and/or World Bank databases, country web sites, IMF Article IV and program reports, and follow-up IMF CD assessments.
- Module-specific objectives and five-year targets summarized for RSS, ESS, GFS/PSDS, FAS, Online Learning, and Statistical Information Management as detailed above.

### Annex II — Proposed Operational Guidance Note: governance and processes
- Overview:
  - D4D Fund is an IMF multi-partner thematic fund starting operations in June 2018 to put more and better data in the hands of decision-makers and support SDG achievement.
- Steering Committee (SC):
  - Provides strategic guidance, sets priorities, and endorses the work plan and updates.
  - Composition: representatives from each Contributor of the D4D subaccount and the IMF; Chair and Vice-Chair elected by consensus for one-year terms.
  - Decisions by consensus; meetings in person annually; ad hoc meetings convened by Chair as needed.
- Work plan management:
  - IMF staff consult informally with SC members; work plan distributed three weeks before SC meetings.
  - Strategic changes and budget adjustments handled via non-objection/lapse-of-time email procedures; standard LOT approval period is fifteen working days.
- Reporting and evaluation:
  - SC endorses the annual report.
  - IMF provides detailed module descriptions, annual assessments, work plan adjustments, and resource utilization updates on Partners Connect no later than three months after endorsement of summaries.
  - Activities financed under the D4D Fund subject to an external, independent evaluation; SC endorses TOR and methodology for evaluation.

*Source: IMF Statistics Department — D4D Fund work plan (June 2018).*

### Box 1. Relevance of Macroeconomic Data in Monitoring SDGs ..............................................................

### Box 1. Relevance of Macroeconomic Data in Monitoring SDGs

### Importance of macroeconomic data for SDG monitoring
- More than one-third of SDG indicators relate to macroeconomic aggregates.
- Developing a sound basis for macroeconomic statistics will substantially enhance SDG monitoring because many SDG indicators relate to the size of the economy.
- Improving macroeconomic statistics increases the reliability and cross-country comparability of SDG indicators over time.

### Implications of GDP measurement and related statistics
- Enhancing the quality of GDP measurement—e.g., by better capturing the informal economy—directly improves the reliability and cross-country comparability of many SDG indicators that depend on the size of the economy.
- Digitalization and new data sources present measurement challenges for national accounts and price indexes, with implications for growth, productivity, inflation, and welfare measurement.

### D4D Fund contributions to SDG monitoring
- The D4D Fund will make important contributions to enhancing the reliability and cross-country comparability of macroeconomic statistics, especially under Module M1 (Addressing Data Needs and Quality Concerns).
- The D4D Fund will ensure direct reporting to the international community for the SDG financial inclusion indicator by fostering country reporting under the Financial Access Survey (Module M2).

### Broader context and operational implications
- The SDGs require production of some 230 indicators to monitor progress under the 2030 Agenda, posing a modernization challenge for national statistical systems, especially in low- and lower middle-income countries (LLMICs).
- Strengthened macroeconomic statistics empower fiscal, monetary, and structural policy analysis and formulation, inform IMF surveillance, and enable private- and public-sector decision-makers and stakeholders to better assess opportunities and risks.

*Source: IMF Statistics Department — D4D Fund work plan (June 2018).*

### 11.      Within Module M1, the submodule on fiscal and debt reporting, with a particular emphasis on

### D4D Fund — Module M1: Addressing Data Needs and Quality Concerns (excerpt)

### Strategic sequencing and geographic focus
- Module M1 prioritizes the submodule on fiscal and debt reporting, with a particular emphasis on public sector debt statistics (PSDS), to be pursued on a fast track to reach broad geographical coverage and respond to increased debt vulnerabilities identified by the international community.  
- The submodule on external sector statistics (ESS) will be launched at a slower pace; initial ESS work will focus on the Middle Eastern region where particular ESS challenges exist.  
- Module M1 comprises three submodules: Real Sector Statistics (RSS), External Sector Statistics (ESS), and Fiscal and Debt Reporting (GFS/PSDS).

### The Financial Access Survey (FAS) — role and empirical points
- The FAS is a supply-side financial inclusion database launched in 2009 with close-to-universal country coverage, based on administrative data from central banks and other regulators sourced from financial service providers (commercial banks, mobile network operators, insurance companies).  
- The FAS offers cost-effective, higher-frequency data collection with broader population coverage compared with demand-side surveys (e.g., World Bank’s Global Findex), and has been flexibly adjusted to capture mobile money services and other changes in financial sector architecture.  
- Empirical observations cited:
  - Sub-Saharan Africa has on average five times fewer bank branches and ATMs per adult than in the rest of the world, with fragile states rated particularly poorly.  
  - Afghanistan: there are now more than six times as many mobile money agents than ATMs, facilitating direct deposit of payroll for civil servants through mobile phones.  
- The FAS has been widened to cover mobile money and has piloted gender-disaggregated financial access statistics to measure the financial access gender gap with sufficiently granular and high-frequency data.

### Fundraising and financial status (D4D Fund, as of May 31, 2018)
- Total raised to date: about US$18 million of the US$33 million targeted in the Program Document.  
- Specific contributions and pledges reported:
  - Luxembourg: signed LOU for €4 million (reported as 4.8 million U.S. dollars in the table).  
  - Switzerland: pledge CHF 4 million (pending).  
  - European Commission: pledge €2 million (pending).  
  - The Netherlands: pledge €3.5 million (pending).  
  - Korea: pledge US$1.7 million (pending).  
  - China: pledge US$1 million (pending).  
- Table-level figures (as reported):  
  - Under Negotiation Total: 13.2 (in Millions)  
  - Grand Total: 18.0 (in Millions)  
  - Program Document Budget: 33.1 (in Millions)  
  - Funding Gap: 15.1 (in Millions)  
- Work plan financing and cash position projections:
  - The Steering Committee is able to endorse the work plan of US$ 6.85 million based on available resources, including pledged amounts.  
  - Based on current estimated disbursements, the subaccount would have a US$3.16 million balance at the end of calendar year 2019 (the end point of the current D4D Fund work plan).  
  - Fund-raising efforts are expected to advance during the second half of 2018 as partners secure budgetary allocations; additional partners are expected to join and formalize pledges into signed LOUs.

### CD approach under Module M1
- Core elements of the CD approach:
  - Mix of mutually reinforcing technical assistance (TA) and training with strong peer-to-peer learning and transfer of knowledge on the economic rationale of the CD intervention.  
  - Clear identification of baseline situations and the development of country-owned work plans and country-specific log frames incorporated into the IMF’s Results-Based Monitoring (RBM) system.  
  - CD tailored to be: (i) highly practical with hands-on training using authorities’ own data; (ii) heavily policy-oriented and “fit-for-purpose”; (iii) delivered in close consultation with IMF country teams to test data usability; (iv) focused on encouraging data dissemination and publication consistent with IMF guidelines; and (v) open to using big data (e.g., mobile money and credit card data) and machine-to-machine readable technology where appropriate.  
- Coordination and complementarities:
  - D4D Fund interventions will be coordinated with other IMF CD vehicles (RTACs, FSSF, bilateral projects) and other CD providers, with potential for blended resources and shared workshops using field-based infrastructure (RTACs or IMF Regional Training Centers).

### Real Sector Statistics — Residential Property Price Indices (RPPIs)
- Policy rationale:
  - RPPIs inform macro-prudential and monetary policy and help detect systemic risks from real estate cycles; they are important inputs to IMF surveillance and financial stability analysis.  
- Baseline and coverage:
  - Estimated eight LLMICs (one-tenth) have compiled and disseminated a RPPI.  
  - Around ten countries (one-eighth) are currently working on compiling a RPPI.  
  - Around four-fifths of eligible countries have no RPPI available but economic analysis requires better real estate price data.  
- Capacity-building objectives and delivery modes:
  - For the one-tenth of countries with a basic RPPI: provide TA to align compilation and dissemination with the Handbook on Residential Property Price Indices (RPPI Handbook), with short-term methodological improvements and longer-term development of data sources and sophisticated techniques.  
  - For the one-eighth of countries currently working on RPPI: increase staff capacity to improve source data, compilation methods, and dissemination; develop capacity for robust though less sophisticated methodologies and explore better source data in the longer term.  
  - For the roughly four-fifths without RPPI: regional workshops on source data needs, methodology, compilation methods, and assessment of potential for developing source data, complemented by follow-up TA if basic data collection progresses.  
- Implementation plan (first 18 months and FY scheduling):
  - Two regional workshops envisaged: one for AFR in FY2019 and one for MCD in FY2020.  
  - TA missions in six countries; specific TA planned as follow-ups to prior regional workshops and requests arising from IMF surveillance (e.g., Vietnam, Bolivia).  
  - Table of CD activities (selected entries):  
    - FY2019 AFR Workshop: Training, baselines, and work plans  
    - FY2019 MCD Workshop: Training, baselines, and work plans  
    - FY2019 Vietnam: Residential Property Price Indices  
    - FY2019 Mongolia: Residential Property Price Indices  
    - FY2020 Indonesia: Residential Property Price Indices  
    - FY2020 Bolivia: Residential Property Price Indices  
    - FY2020 Bangladesh: Residential Property Price Indices  
    - FY2020 Vietnam: Residential Property Price Indices  
  - Target country lists presented for AFR and MCD would be submitted to the next Steering Committee for confirmation.

### Real Sector Statistics — High-frequency Indicators (HFIs)
- Strategic objectives:
  - HFIs help policy-makers assess cyclical position and adjust fiscal and monetary policy to smooth cyclical swings and reduce volatility, which supports inclusive growth.  
- Baseline and quantitative targets:
  - Currently about two-thirds of LLMIC compile some type of monthly or quarterly economic activity indicator.  
  - Work stream aims:
    - Support at least 10 countries currently not producing HFIs to compile and disseminate an indicator for a significant activity/sector.  
    - Assist at least 15 additional countries to strengthen the compilation and dissemination of well-defined HFIs of economic activity.  
- CD scope:
  - Development of suitable source data, compilation techniques, and statistical and analytical frameworks so participating countries compile new indicators for national policy-making and external users (including the IMF).

*Source: D4D Fund work plan (June 2018), Statistics Department, International Monetary Fund.*

### 29.      The HFI work stream will be developed mainly by the following two activities: (i) opening

### D4D Fund Work Plan (June 2018) — HFI, Improved Source Data, and External Sector Statistics

### HFI work stream: objectives and delivery modalities
- The HFI work stream will be developed mainly by two activities: (i) opening regional workshops to undertake a country assessment and baseline definition and to develop country-specific work plans; and (ii) offering support on a single-country basis through tailored TA missions. In some instances, TA on a multi-country basis may be provided when synergies are warranted.
- Regional workshop schedule and scope:
  - In FY2019, two regional opening workshops will be organized: one benefitting a first group of IMF’s African Department (AFR) countries and one in the APD region, followed by similar events in FY2020 for MCD and a second group of AFR countries.
  - The workshops will aim to: (i) explain the rationale of, and need for, HFIs; (ii) provide basic methodological training and guidance on data sources and the use of administrative data; (iii) derive countries’ baselines; and (iv) develop country-owned work plans for developing, enhancing, or improving HFIs.
- Country-specific TA missions:
  - Country-specific TA missions are expected to be conducted to about 25 targeted countries during the five-year D4D Fund period.
  - During FY19, three two-week potential missions have been planned, with Jordan already confirmed and discussions ongoing to include one AFR and one MCD country.
- Targeted country groupings (footnoted in the plan):
  - AFR (first group): Ethiopia, Kenya, Rwanda, Tanzania, Uganda, The Gambia, Ghana and Nigeria.
  - APD: Bhutan, Cambodia, India, Indonesia, Lao's Republic, Mongolia, Philippines, Sri Lanka, and Vietnam.
  - MCD: Armenia, Egypt, Kyrgyz Republic, Morocco, Tajikistan, Tunisia, Uzbekistan, and West Bank and Gaza.
  - AFR (second grouping): Burundi, Cabo Verde, Cameroon, Cote d'Ivoire, Madagascar, Mauritania, Mozambique, and Senegal.

### Work stream: Improved Source Data and Intermediate Statistics — purpose and priorities
- Aim: develop and use source data to compile annual and quarterly GDP estimates as well as services producer price indices (SPPIs).
- Expected benefits:
  - Enhanced coverage and accuracy of GDP estimates, including better estimates of the informal economy and the digital economy.
  - Support for countries’ ongoing and future rebasing exercises.
  - Facilitation of sectoral decomposition and cross-sectoral linkages in the national accounts.
  - Improvement in the quality of SDG reporting.
- Digital economy focus:
  - Efforts will emphasize areas particularly relevant in the LLMIC context, such as rapidly growing mobile money services.
  - Assistance on price statistics will focus on the services sector; many LLMICs currently limit price statistics to goods, resulting in a measurement omission.
- SPPI objective:
  - Support on the compilation and dissemination of an SPPI will help differentiate productivity-driven price changes versus general inflationary price changes.
  - The work stream objective will focus on eligible countries with sizable mobile money activity; currently, around ten countries have financial sectors with a large and fast-growing mobile money component and are natural SPPI candidates.

### Findings on current practice and baselines (heterogeneity and data gaps)
- GDP rebasing context:
  - Recent rebasing in LLMICs has often resulted in significant—generally upward—revisions to headline GDP.
  - Some one-third of IMF member countries have still not rebased their national accounts for more than 10 years (it is best practice to undertake a rebasing exercise every five year or less).
- Baseline diagnostics and specific data-use patterns:
  - About a quarter of LLMICs use tax data for national accounts compilation, but often not to their full potential due to legal confidentiality requirements, lack of inter-agency cooperation agreements, or insufficient capacity in the national statistics office.
  - Some statistically sophisticated LLMICs are developing sectoral decompositions of their national accounts to support detailed sector analysis and linkages.
  - About one-fifth of eligible countries collect regular business survey information; many LLMICs face insufficient funding to conduct these surveys essential for GDP compilation.
  - An IMF survey from 2017 indicates about half of the LLMICs include estimates for the informal economy in their national accounts but only one-fifth of them can substantiate this estimate through informal sector surveys used in the compilation process.
  - A very small number of LLMICs estimate the impact of technological changes on GDP, explore non-traditional data sources (e.g., big data from mobile banking), or compile an SPPI.

### Measurable indicators and country-level targets
- Country intervention indicators could comprise:
  - (i) improvements in the availability and use of source data;
  - (ii) reducing the discrepancy between different elements of national accounts (production- versus expenditure-based compilation);
  - (iii) monitoring the size of necessary revisions in the rebasing of national accounts; and/or
  - (iv) assessing the availability of measures to estimate technological change in GDP or of an SPPI.
- Planned CD engagements (FY2019–FY2020) include:
  - FY2019: six TA missions on supporting the sectoral composition of GDP; five TA missions on enhancing source data availability (including cooperation with tax authorities and design/conduct of business surveys, with emphasis on informal sector and digital economy data); one regional workshop to improve estimates on the non-observed economy, including the informal economy; and one workshop to assist in developing an SPPI, with particular reference to digital services.
  - FY2020: two workshops in the AFR and APD regions to guide countries on the use of source data and estimates of the informal economy.
- Projected medium-term trend: the volume of D4D-funded CD activities is projected to increase over the medium-term to offset the winding down of bilateral donor-funded projects focusing on development of source data in Africa and the Middle East region.

### Country-level CD activities (selected entries from Table 5)
- FY 2019 country TA: Macedonia; Honduras; Uganda; Kosovo — all focused on developing source data for sectoral decomposition and linkages of accounts.
- FY 2020 planned activities include:
  - APD workshop: Regional workshop on the use of source data and estimates of the informal economy.
  - AFR workshop: Regional workshop: Services producer price index for countries with intensive use of mobile banking.
  - Moldova and Kosovo: Developing source data for sectoral decomposition and linkages of accounts (follow-up).
  - Liberia, Nigeria, Zimbabwe, Malawi: Increasing use of administrative data; improvement of surveys including informal economy and the digital economy for the national accounts.
  - Uganda: Developing source data for sectoral decomposition and linkages of accounts.
  - Nigeria: Increasing use of administrative data; improvement of surveys including informal economy and the digital economy for the national accounts.
  - Zimbabwe and Malawi: Increasing use of administrative data; improvement of surveys including informal economy and the digital economy for the national accounts.

### CD approach and modes of delivery for source data work stream
- The launch will benefit from existing diagnostics of country needs identified through other CD interventions (RTACs and bilateral projects).
- Delivery modes will include regional workshops and country TA missions, with country selection based on internal needs assessments (in consultation with IMF area departments) and unmet TA/training requests.
- The work stream will define a baseline and quantitative targets for each country intervention, recognizing differences in country priorities (e.g., informal economy measurement in one country versus tax authority cooperation in another).

### Submodule: External Sector Statistics (ESS) — focus and strategic objectives
- Focus: current and financial accounts of the balance of payments to address gaps in coverage of goods, services, income, remittances and investments.
- Rationale: gaps impair reliability of balance of payments statistics and policy use to detect and address external risks and vulnerabilities, including cross-border spillovers; important for monetary, fiscal and exchange rate policies and structural reform assessment—especially in LLMICs which tend to be more open to the rest of the world.
- Globalization and data sources:
  - Global value chains change trade and investment conduct and require adjustments to balance of payments compilation.
  - Big data (e.g., mobile money transactions) offers new sources to improve accuracy of statistics such as remittances.
- Strategic objectives and baselines for the five-year D4D Fund period:
  - Improve the scope of goods and services statistics in at least 15 countries to better assess the impact of global value chains on their current account. Currently, only a quarter of countries eligible under the D4D Fund report transactions on goods for processing and/or merchanting data in their balance of payments statistics.
  - Strengthen coverage of financial and remittance flows data in at least 15 countries. Financial account data in some LLMICs are constrained for components including direct investment and private sector debt; remittance measurement issues persist due to informal transmission channels and growth of electronic transfer modes (“mobile money”).
  - Address errors and omissions to enhance data relevance: regional averages of net errors and omissions in relation to gross current account flows are reported as 1.7-1.9 percent for APD, MCD and WHD countries; 3.1 percent for AFR; and 1.2 percent for EUR. Except for EUR, more than half of countries in each of the other regions exceeded 1 percent for the indicator.
- CD delivery and prioritization:
  - A phased approach will be used, with activities stepped up in the last three years of the D4D Fund.
  - Current bilateral ESS projects and some RTAC coverage combined currently cover around 44 percent of the LLMICs; priority for CD will initially be given to MCD countries that are benefiting from existing CD programs to a lesser extent.
  - Delivery mix: regional workshops and country TA missions. Country-specific missions will target countries with incomplete current and/or financial accounts and/or balance of payments with large or volatile net errors and omissions.
- Data development emphasis:
  - Improve coverage and reliability of goods and services statistics, remittances and financial account flows by tackling source data development and examining prospects for harnessing big data and administrative data.
  - Leverage complementary CD initiatives to strengthen cross-border positions (stocks) data to enhance the quality of recorded financial account flows.

*Source: IMF D4D Fund work plan (June 2018), Statistics Department.*

### 45.      For the first 18 months of the D4D Fund period, the ESS submodule aims to deliver one

### Baseline and strategic objectives in line with the program log frame

### External Sector Statistics (ESS)
- For the first 18 months of the D4D Fund period, the ESS submodule aims to deliver:
  - one regional workshop and ten country TA missions.
- The first workshop will target primarily MCD countries to scope source data and compilation issues on the current account as a basis for future CD engagement under the D4D.
- FY2019 planned CD activities on External Sector Statistics (excerpted):
  - MCD and selected countries workshop: Regional workshop on current account issues aimed at (i) scoping country-specific baselines; and (ii) providing multi-country training on key compilation issues.
  - Country TA scopes:
    - The Gambia: Improving data sources for compiling current and financial account.
    - Kenya: Improving the financial account by addressing source data gaps.
    - Uzbekistan: Establishing the balance of payments compilation system, focusing on current account components.
    - Vanuatu: Implementing new surveys to capture cross-border transactions, and building direct investment statistics.
- FY2020 planned CD activities on External Sector Statistics (excerpted):
  - Madagascar: Improving the current account by addressing data gaps for unrecorded trade in goods and services.
  - Uzbekistan: Improving the financial account by engaging new data sources.
- Targeted countries (footnote): Afghanistan, The Gambia, Egypt, Jordan, Kiribati, Kenya, Madagascar, Morocco, The Philippines, Solomon Islands, Tunisia, Uzbekistan, Vanuatu, and West Bank and Gaza.

### Submodule: Fiscal and Debt Reporting (GFS/PSDS)
- Strategic objectives and rationale:
  - Aim: provide policy‑makers with improved high‑frequency government finance statistics (GFS) and public sector debt statistics (PSDS) to address data gaps and weaknesses.
  - Expected results: improved quality, frequency, and timeliness of GFS used by policy‑makers and the IMF in surveillance; comprehensive, timely, and cross‑country comparable PSDS to enhance debt sustainability analyses; improved transparency and accountability via dissemination of GFS and PSDS.
- Current assessment:
  - A survey among IMF country teams of 45 Sub‑Saharan African countries revealed that fiscal data of more than 30 of those countries do not cover activities beyond budgetary central government.
  - Comprehensive stock data to measure the extent of indebtedness are unavailable in some 40 countries.
- Allocation of D4D CD over five years:
  - About two‑thirds devoted to PSDS (stocks) and one‑third to GFS (flows).
- PSDS objectives:
  - Expected to achieve improvements in institutional coverage, instrument coverage, timelines, periodicity, and/or data on contingent liabilities in roughly three‑quarters of eligible LLMICs.
  - Use D4D Fund resources to organize a series of regional workshops to establish country‑owned work plans, in close consultation with IMF area departments.
  - Follow‑up TA missions largely funded by D4D Fund resources, potentially blended with RTACs, bilateral CD projects, and the FSSF work stream on balance sheet analysis.
  - Note: “starting points” differ by country; pace depends on country capacity. (Footnote: More than one TA mission may be needed in such cases.)
- GFS objectives:
  - Targeted CD to close fiscal data gaps (e.g., high‑frequency fiscal data, data on state‑owned enterprises, improved timeliness, and expanded scope of flows and stock positions).
  - Improve transparency and accountability through data dissemination in about a third of eligible LLMICs.
- Selection and coordination:
  - Country selection based on country demand with input from IMF area departments; priority to countries with sharp increases in debt‑to‑GDP ratios and large PSDS risks as evidenced in debt sustainability analyses.
  - PSDS CD missions to be fielded alongside, or adjacent to, area departments’ surveillance missions where appropriate.
  - PSDS CD to be coordinated with the Debt Management Fund (DMF) and exploit synergies with existing GFS CD.
- CD delivery over an 18‑month period:
  - Five regional PSDS workshops and about 20 TA missions in PSDS and GFS.
  - Work split roughly two‑thirds PSDS and one‑third GFS.
- PSDS workshops (objectives and schedule):
  - Objectives: (i) develop country‑owned work plans based on PSDS data gaps and baseline analysis; (ii) establish or strengthen a reporting channel of PSDS to deliver timely PSDS primarily to area departments and other stakeholders; also promote peer‑to‑peer learning.
  - FY2019: two regional PSDS workshops—one for Anglophone African and one for Lusophone LLMICs.
  - FY2020: three regional PSDS workshops covering Asia and Pacific Islands LLMICs, Francophone LLMICs, and Middle Eastern/Central Asian LLMICs.
  - Note: As most WHD LLMICs are CAPTAC beneficiaries, a PSDS workshop for those countries would be organized through CAPTAC in FY2019.
- PSDS technical assistance:
  - Draft work plans prepared jointly with country authorities and IMF area department teams; TA needs addressed through one or more TA missions.
  - About 15 one‑week TA missions are planned for the 18‑month period.
  - FY2019: PSDS TA to at least three countries that participated in the workshops, organized alongside or adjacent to Article IV missions to inform debt sustainability analyses.
  - Expected scale‑up to cover about twelve countries in the first nine months of FY2020.
- GFS technical assistance:
  - About 5 two‑week TA missions planned for the 18‑month period.
  - FY2019: two‑week GFS TA missions to Comoros and Ghana.
    - Comoros: enable regular, timely compilation of a statement of government operations (TOFE in French) with expanded coverage extending to the local islands.
    - Ghana: eliminate internal data inconsistencies hampering fiscal policy‑making and IMF surveillance; compile data on nonfinancial public corporations to capture potential fiscal risks.
  - First nine months of FY2020: an additional three GFS TA missions planned based on country demand and area department guidance.
- Tabled FY2019 and FY2020 CD activities on GFS and PSDS (selected entries):
  - FY2019:
    - Anglophone AFR PSDS Workshop: Training, baselines and work plans.
    - Lusophone AFR PSDS Workshop: Training, baselines and work plans.
    - Zambia: PSDS TA.
    - Zimbabwe: PSDS TA.
    - Sierra Leone: PSDS TA.
    - Comoros: GFS TA.
    - Ghana: GFS TA.
  - FY2020:
    - APD PSDS Workshop; Francophone AFR PSDS Workshop; MCD PSDS Workshop: Training, baselines and work plans.
    - Multiple workshop follow‑up country PSDS TA entries across APD, Lusophone AFR, MCD, and Francophone AFR regions.
    - Country 1 GFS TA; Country 2 GFS TA; Country 3 GFS TA.

### Module II: Financial Access Survey (FAS)
- Aim:
  - Ensure continued annual production and dissemination of the FAS, providing policy‑makers and stakeholders with long time series on financial access and inclusion.
- Relevance:
  - High‑quality supply‑side financial inclusion indicators support policy analysis and macro‑prudential policies in LLMICs.
  - Close monitoring required as vulnerabilities may arise with new players, products, and infrastructures.
- Role in SDG monitoring:
  - FAS provides the monitoring basis for the SDG financial inclusion indicator, contributing two indicators to the global monitoring framework: (i) the number of commercial bank branches and (ii) the number of automated teller machines per 100,000 adults.
  - Strategic objective: continue providing indicators that cover at least 90 percent of the world adult population, with data regularly published on the UN SDG Indicators Global Database.
- Reporting enhancement strategic objectives:
  - Raise the number of economies reporting the most quoted FAS series—the number of commercial bank institutions—from 86 percent in 2017 to 95 percent of the IMF membership by the end of the D4D Fund cycle.
  - Increase the reporting of gender‑disaggregated data by two‑fold compared to the 2017 benchmark of 28 reporting jurisdictions.
  - Increase by 50 percent the number of economies reporting indicators of innovative channels of financial access—mainly mobile money‑related indicators—compared to the 2017 benchmark of 45 reporting jurisdictions.
- Outputs and delivery:
  - FAS data used to create a global financial inclusion index and feature in IMF reports on financial inclusion.
  - Module commitments: (i) FAS conducted annually; (ii) country reporting benefits from close IMF follow‑up and validation; (iii) data dissemination on a rolling basis on the IMF’s external website.
- Resource allocation and activities over the next 18 months:
  - Mix of HQ‑based work, outreach activities, and a regional workshop.
  - Bulk of resources devoted to HQ‑based FAS activities: securing high response rates, performing data validation, following up with countries, disseminating data, producing SDG indicators, preparing analytical and research outputs, and enhancing survey methodology to capture innovations.
  - Outreach in collaboration with partners such as the Alliance for Financial Inclusion (AFI).
- Regional workshops:
  - Planned regional workshop in Africa in March 2019 targeting: Angola, Botswana, Cabo Verde, The Gambia, Ghana, Kenya, Mozambique, Namibia, Nigeria, Rwanda, Swaziland, Uganda, Zambia, and Zimbabwe.
  - A predecessor workshop will be organized in Asia in September 2018 (targeting specific Asian countries) funded by a bilateral donor and not reported under the D4D activities.
- Note on related events:
  - AFI’s Global Policy Forum (September 5–7, 2018) in Sochi, Russia noted as a key forthcoming event to showcase financial inclusion progress and promote the FAS; IMF participation to be funded by a bilateral donor.

### Module III: Online Learning
- Objective:
  - Substantially enhance the reach of IMF statistics training by developing and rolling out a comprehensive online learning curriculum that provides free access to high‑quality training anytime and anywhere.
- Rationale:
  - STA is the second‑largest training provider at the IMF, reaching close to 2,500 government officials every year; face‑to‑face courses are popular and over‑subscribed.
  - Online learning broadens participation and allows participants to get certified.
- Target and approach:
  - Develop and launch eight fundamental statistics courses (English and up to five other languages).
  - Build on a basic online training course that is close to being rolled out (the basic course is the entry level that participants must graduate from before proceeding).
  - Leverage technology to increase the number of participants in STA training by at least 50 percent by the end of the D4D Fund period.
- Evidence of feasibility:
  - ICD’s experience with online training has been highly successful, with particularly high participation and graduation in LLMICs.

*Source: Statistics Department — D4D Fund work plan.*

### 61.      Passing the fundamental online courses will become a precondition to participate in the face-

### Data for Decisions (D4D) — Work Plan (June 2018) — Online Learning, Module IV, and Indicative Budget

### Online fundamental courses: design, delivery, and prerequisites
- Passing the fundamental online courses will become a precondition to participate in the face-to-face intermediate and advanced courses.
- Topical intermediate and advanced courses will be recalibrated once the online training courses are up-and-running, and will focus on practical application and peer-to-peer learning on specific topics.
- Converting one face-to-face fundamental statistics course (usually two weeks) into state-of-the-art online courses will require around a year.
- Expected participant completion time: participants are expected to take around 6-8 weeks to complete a fundamental online course.
- Post-launch support: STA will offer, at certain times, a period of interactive sessions with a statistics expert who will answer questions and facilitate discussions through online forums.
- Translation strategy: translation should start after the courses have been online for a year to incorporate feedback and potential changes before translation starts; translation in up to five languages will depend on the availability of funding.

### Online course development process and resource needs
- Course structuring: a development plan will structure the course into sub-sections devoted to different learning objectives.
- Instructional design elements:
  - Visualized learning content with graphic design solutions to aid comprehension.
  - Separate learning activities with questions aimed at applying the learning objectives.
  - Completion of video scripts, studio filming, and extensive post-filming editing to integrate interactive elements.
  - Online availability: once online, courses will be available 24/7.
- Staffing and outsourcing:
  - Under the D4D Fund, planned hires: two contractual staff to support economists in topical divisions in preparing development plans, designing visuals and learning content, writing scripts, and facilitating online discussions.
  - Some services outsourced to specialized companies (e.g., filming and editing).
- Estimated cost per course: Costs associated with an online course are estimated at around USD 0.75 million, excluding translation.
- Planned rollout: rolling completion of eight fundamental online learning courses during the next five years (Module M3).

### Module IV: Statistical Information Management — objectives and pilot activities
- Objective: provide advice on statistical information management practices and related technical environments to address challenges in statistical data management (M4).
- Rationale: lack of clearly defined frameworks and poor technological systems hamper data compilation and dissemination (stand-alone systems, different data formats, reconciliation time, increased error risk).
- Focus of CD: explain best practices in statistical data and metadata management, governance structures, tools, technical standards, and statistical information models to enable recipient agencies to design and implement state-of-the-art statistical information management structures and tools.
- Technology guidance: discuss technology options available to meet specific needs without recommending specific tools or technology.
- Pilot activity status and planned pilots:
  - Pilot workshop with the Central Bank of Kenya in 2017 provided insights and led to formal launch readiness for an Economic Data Warehouse (EDW) implementation project at the CBK.
  - Similar workshops planned for Lebanon and Egypt or Tunisia (requests received from the three countries; agreement exists with Lebanon on the fielding of the mission; discussions ongoing with the other two countries).
  - Two additional pilots planned to assess resource intensity and guide selection of indicators to measure progress.
- Peer-to-peer learning: intend to establish a knowledge base of practices and a network of practitioners to facilitate peer-to-peer learning.
- FY 2019 planned CD activities on Statistical Information Management (Table 9):
  - Lebanon: Structures and standards for establishing an automated data exchange within the national statistical system and with international organizations.
  - Egypt or Tunisia: Governance and data structures for internal data management and data dissemination.

### Indicative program budget (next 18 months) — totals and module-level allocations
- Total work program budget for the next 18 months (including the 7 percent trust fund management fee): USD 6.85 million.
- Subtotal (before TF management fee): USD 6,403,029.
- TF Management Fee (7%): USD 448,212.
- Total: USD 6,851,241.

Module-level allocations (FY19-FY20; totals)
- Module M1 (Addressing Data Needs and Quality Concerns): USD 3.13 million (Total USD 3,123,631)
  - Real Sector Statistics: USD 0.75 million (USD 745,566)
  - External Sector Statistics: USD 0.63 million (USD 628,388)
  - Fiscal and Debt Reporting: USD 1.75 million (USD 1,749,677)
- Module M2 (Financial Access Survey): USD 1.12 million (USD 1,124,150)
- Module M3 (Online Learning): USD 1.64 million (USD 1,635,373)
  - Note: assumed costs for developing and rolling out one fundamental online course estimated at about USD 0.75 million.
- Module M4 (Statistical Information Management): USD 0.17 million (USD 169,338)
- RM Project Manager: USD 0.35 million (USD 350,537)

Table 10 summary (Budget by Module; FY19 / FY20 / Total)
- Module 1 - Addressing Data Needs and Quality Concerns: 1,089,995 / 2,033,636 / 3,123,631
  - Submodule Real Sector Statistics: 216,366 / 529,200 / 745,566
  - Submodule External Sector Statistics: 358,864 / 269,524 / 628,388
  - Submodule Fiscal and Debt Reporting: 514,765 / 1,234,912 / 1,749,677
- Module M2: Financial Access Survey: 586,746 / 537,404 / 1,124,150
- Module M3: Online Learning: 598,680 / 1,036,693 / 1,635,373
- Module M4: Statistical Information Management: 83,460 / 85,878 / 169,338
- RM Project Manager: 169,672 / 180,865 / 350,537
- Sub total: 2,528,553 / 3,874,476 / 6,403,029
- TF Management Fee (7%): 176,999 / 271,213 / 448,212
- Total: 2,705,552 / 4,145,689 / 6,851,241

Table 11 summary (Budget by Activity; FY19 / FY20 / Total)
- Project Manager: 169,672 / 180,865 / 350,537
- HQ Staff: 1,061,448 / 1,555,337 / 2,616,785
- TA missions: 298,462 / 600,783 / 899,245
- HQ Delivery: 96,845 / 140,810 / 237,655
- STX: 201,617 / 459,973 / 661,590
- Workshops: 479,867 / 703,577 / 1,183,444
  - HQ Delivery (workshops): 144,701 / 146,573 / 291,274
  - STX (workshops): 45,166 / 114,534 / 159,700
  - Participants: 290,000 / 442,470 / 732,470
- Language Services: 70,000 / 261,375 / 331,375
- Security (officials traveling to a third location): 40,000 / 36,015 / 76,015
- Exceptional: 105,000 / 117,675 / 222,675
- STA Project Management: 274,368 / 348,909 / 623,277
- STA Backstopping: 29,736 / 69,940 / 99,676
- Sub total: 2,528,553 / 3,874,476 / 6,403,029
- TF Management Fee (7%): 176,999 / 271,213 / 448,212
- Total: 2,705,552 / 4,145,689 / 6,851,241

### Issues for information and endorsement (selected budget implications)
- Module 1, Submodule Real Sector Statistics: USD 0.75 million
- Module 1, Submodule External Sector Statistics: USD 0.63 million
- Module 1, Submodule Fiscal and Debt Reporting: USD 1.75 million
- Module 2: Financial Access Survey: USD 1.12 million
- Module 3: Online Learning: USD 1.64 million
- Module 4: Statistical Information Management: USD 0.17 million
- Program Manager: USD 0.35 million
- Endorsement of D4D Fund Operational Guidance Note: n/a

*Source: Statistics Department, Data for Decisions (D4D) Fund work plan.*

### Annex I. D4D Fund Strategic Logframe

### Annex I. D4D Fund Strategic Logframe

### D4D’s Strategic Objective
- The D4D Fund aims to assist low-income and lower-middle-income countries (LLMICs) in strengthening national statistical systems to cope with a challenging national and international policy environment, promote transparency and accountability, and offer efficient solutions to capacity development.
- Impact outcome: More and better data are available for decision-makers and analysts, with the ultimate objective of better informing economic policies and supporting monitoring of the SDGs.
- Key impact indicator domains: improvements across all macroeconomic and financial statistical domains.
- Data sources for impact and outcome monitoring: Dissemination on National Summary Data Pages (NSDPs), IMF and/or World Bank databases, and/or country web sites; IMF’s Article IV and program reports; follow-up assessments through IMF CD activities.

### Objective Module 1 — Policy-makers and the public have access to more and better data in three main statistical domains (real, external, and fiscal and debt statistics)
- Purpose: support policy analysis and formulation, detect economic risks and vulnerabilities, and enhance transparency and accountability.

Real Sector Statistics — Objective 1: Residential Property Price Indices (RPPI)
- Rationale: RPPIs provide information about price trends in real estate important for assessing banking-sector balance-sheet risks.
- Outcome indicator: Strengthened compilation and dissemination of RPPIs, including improvements in statistical infrastructure, source data, serviceability and metadata.
- Five-year D4D period targets and approaches:
  - for the around one-tenth of eligible countries that already have a basic RPPI:
    - Compilation and dissemination brought in line with guidelines and best practices in the Handbook on Residential Property Price Indices;
    - Staff capacity increased through CD on source data, compilation methods, and dissemination.
  - for the around one-eighth of eligible countries currently working on RPPI compilation:
    - Follow-up assessments through IMF CD activities, including assessments during bilateral TA missions or workshop “before and after” quizzes/exams.
  - for the around four-fifths of eligible countries where no RPPI is available but economic analysis requires better real estate price data:
    - Regional workshops for training on data needs and methodology, with follow-up TA missions if sufficient progress in basic data collection occurs.
- Dissemination channels: NSDPs, IMF databases, and/or country web sites.

Real Sector Statistics — Objective 2: High Frequency Indicators (HFIs) of economic activity
- Rationale: HFIs inform policy-makers on the cyclical position to adjust policy mixes and ease economic volatility.
- Outcome indicator: Strengthened compilation and dissemination of well-defined HFIs.
- Baseline: Currently about two-thirds of LLMICs compile some type of a monthly or quarterly economic activity indicator.
- Five-year D4D period targets:
  - supported at least 10 countries currently not producing HFIs to compile and disseminate an indicator for a significant activity/sector; and
  - assisted at least 15 additional countries to strengthen compilation and dissemination of well-defined HFIs.
- Follow-up: assessments through IMF CD activities.
- Dissemination: NSDPs, IMF databases, and/or country web sites.

Real Sector Statistics — Objective 3: Improved source data and intermediate statistics for national accounts and price statistics
- Intended contributions:
  - improved national accounts data, including estimates of the informal economy and the digital economy;
  - diminished large revisions during periodic national accounts rebasing exercises;
  - improved sectoral decompositions and cross-sectoral linkages;
  - development of a Services Producer Price Index (SPPI) series to differentiate productivity-driven price changes from general inflationary changes.
- Baseline constraints among LLMICs:
  - about a quarter use tax data for national accounts compilation, often not to full potential;
  - some LLMICs are developing sectoral decompositions;
  - about one-fifth of eligible countries collect regular business survey information;
  - about half of LLMICs include estimates for the informal economy in national accounts, with only about one-fifth substantiating them through an informal sector survey;
  - a few LLMICs estimate the impact of technological change on national accounts;
  - a few LLMICs have explored non-traditional sources of data (e.g., big data from mobile banking) or compile SPPIs.
- Indicators to be defined:
  - assess improvements in availability, quality and use of source data;
  - monitor discrepancies between different elements of national accounts (production versus expenditure);
  - monitor size of necessary revisions in rebasing;
  - determine availability of sectoral decomposition and cross-sectoral linkages;
  - assess availability of measures to estimate technological change in GDP or of an SPPI.
- Follow-up: assessments through IMF CD activities.

External Sector Statistics
- Objective: Compile and disseminate high-quality balance of payments statistics to allow monitoring of cross-border risks and vulnerabilities and to facilitate analysis of global trade, digitalization and financial integration.
- Outcome focus areas:
  - More accurate and comprehensive data on international trade in goods and services to inform analysis of global trends, global value chains and the digital economy.
    - Five-year target: provide more accurate and comprehensive trade data for at least 15 eligible countries.
    - Progress indicators:
      - targeted countries develop and utilize new data sources to improve data quality;
      - new and/or improved data compiled and disseminated to facilitate analysis of global value chains and the digital economy;
      - improved coverage of goods, including measurement of informal cross-border transactions.
    - Follow-up assessments through IMF CD activities; dissemination on NSDPs, IMF databases, and/or country web sites.
  - Strengthened analysis of cross-border financial risks via improved scope of financial account components and remittances.
    - Five-year target: provide more accurate and comprehensive coverage of the financial account and remittances in at least 15 eligible countries.
    - Progress indicators:
      - targeted countries develop and utilize new data sources to improve financial account scope and remittance coverage;
      - coverage of private sector external debt transactions widened;
      - financial account data improved, evidenced by greater consistency between stocks and flows.
    - Follow-up assessments through IMF CD activities; dissemination on NSDPs, IMF databases, and/or country web sites; IMF Article IV and program staff reports.
- Note on measurement: Addressing gaps should improve balance of payments accuracy measured by the errors and omissions metric, though this indicator may not show a linear trend.

Fiscal and Debt Reporting
- Objective: Improved Government Finance Statistics (GFS) and Public Sector Debt Statistics (PSDS) to support fiscal policy-making, assessment and monitoring of fiscal risks and debt sustainability, and transparency.
- GFS outcomes and targets (for around one-third of LLMICs, depending on risk-based needs assessments):
  - frequency improved from annual to quarterly or from quarterly to monthly;
  - high-frequency GFS follow latest GFS manual including classifications and presentation of summary fiscal data;
  - expanded institutional coverage to resolve policy-relevant fiscal risks;
  - improved internal consistency (e.g., reduction of statistical discrepancy);
  - improved scope of transactions/stock positions to capture policy-relevant items for fiscal risk identification;
  - regular and sustained compilation and dissemination of high-frequency GFS to the public with improved timeliness;
  - dissemination of adequate metadata and business-process documentation to enhance fiscal transparency and accountability.
  - Follow-up assessments: IMF CD activities; dissemination on NSDPs, IMF databases, and/or country web sites; IMF Art. IV and program staff reports.
- PSDS outcomes and targets (for around half of LLMICs, depending on risk-based needs assessments):
  - frequency improved from annual to quarterly or from quarterly to monthly;
  - high-frequency PSDS follow PSDS Guide classifications (by instrument, sector of counterparty, currency, maturity, residence) and present summary debt data;
  - expanded institutional coverage to identify fiscal risks (e.g., include state-owned enterprise debt);
  - improved scope of stock positions to capture contingent liabilities and arrears;
  - regular and sustained compilation and dissemination of high-frequency PSDS to the public with improved timeliness;
  - dissemination of adequate metadata and business-process documentation to enhance fiscal transparency and accountability.
  - Follow-up assessments: IMF CD activities; dissemination on NSDPs, IMF databases, and/or country web sites; IMF Art. IV and program staff reports, including debt sustainability analyses.

### Objective Module 2 — Financial Access Survey (FAS): high-quality statistics on financial inclusion
- Outcomes and operational features:
  - Continued production of the FAS to provide access to long time series on financial access.
    - The FAS survey is sent annually to all IMF members.
    - Data are validated by IMF staff according to reporting guidelines, with close follow-up with respondents.
    - Data are disseminated on a rolling basis immediately following validation.
    - Data source: IMF FAS website.
  - Production of new data series to address rapidly changing data needs, with broader coverage and scope.
    - Five-year targets:
      - The annual response rate to the FAS is increased to 95 percent of the IMF membership;
      - The number of participating jurisdictions providing information on the gender breakdown of FAS is increased by two-fold compared to the 2017 benchmark;
      - The number of participating jurisdictions providing indicators of innovative channels of financial access is increased by 50 percent compared to the 2017 benchmark.
    - Data source: IMF FAS website.
  - Provide monitoring basis for SDG financial inclusion indicator 8.10.1:
    - Provide the number of commercial bank branches and ATMs per 100,000 adults annually, covering at least 90 percent of the world population.
    - Data published on the UN SDG Indicators Global Database.
  - Contribute to research and policy on financial inclusion:
    - FAS data used to create a global financial inclusion index;
    - FAS data featured in IMF reports and analytical publications on financial inclusion.
    - Data sources: IMF FAS website; published IMF reports and analytical publications.

### Objective Module 3 — Expand global reach of statistics training via online learning
- Outcomes and targets:
  - Development and implementation of a new online training curriculum covering eight fundamental statistical topical courses.
  - Translation in up to 5 languages, depending on resource availability.
  - Certification from online training established as entry requirement to improve efficiency of face-to-face intermediate and advanced training.
  - Phasing in of online courses: one coming on-stream during Year 1, two in Year 2-4, and one in Year 5; priority to most oversubscribed face-to-face courses.
  - Target: Increase reach of STA training by at least 50 percent by the end of the D4D Fund period.
  - Data source: IMF tracking system for online learning.

### Objective Module 4 — Statistical information management: streamline, standardize, automate
- Outcomes and scope:
  - Disseminate and facilitate implementation of best practices in statistical data and metadata management and related international frameworks, including:
    - transferring knowledge on governance structures;
    - information on suitable technical standards and statistical information models;
    - advice on project design.
  - Enable recipient agencies to design and implement state-of-the-art statistical information management structures and tools to facilitate joining IMF data dissemination standards and reduce reporting burdens.
  - Pilot projects: pilots in Kenya (2017), and planned pilots in Lebanon, Egypt and/or Tunisia (planned for FY 2019) will guide the selection of indicators for this module.
  - Follow-up assessments: IMF CD activities.

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### Annex II. Proposed Operational Guidance Note — Data for Decisions (D4D) Fund Operational Guidelines

### Overview
- The D4D Fund is an IMF multi-partner initiative to put more and better data in the hands of decision-makers to enhance evidence-based macroeconomic policies and support achievement of the sustainable development goals.
- The thematic fund will start operations in June 2018.

### Steering Committee (SC)
- Role: provide strategic guidance, assist in setting priorities, and endorse the D4D Fund work plan and updates.
- Composition: representatives from each Contributor of the D4D subaccount and the IMF.
- Chair and Vice-Chair:
  - The SC will be chaired by a donor with strong interest in contributing to D4D operations; the IMF, as secretariat, will propose a Chair and Vice Chair.
  - Chair and Vice Chair elected by consensus; term is one year, after which the Vice Chair becomes Chair.
  - Chair presides over SC, consulted on agenda and urgent/contentious issues; Chair convenes decisions outside meetings by email circulation and non-objection period; Vice Chair assumes Chair role when Chair is absent.
- Decisions:
  - SC decisions made by consensus; each party has one voice.
  - If consensus is not possible, the proposal is postponed or withdrawn.
  - SC approves minutes prepared by the IMF.
  - Decisions outside meetings made by email circulation with a notification of a non-objection period if applicable.
- Meetings:
  - SC meets in person annually.
  - Chair may convene ad hoc meetings.
  - Observers may be invited on a case-by-case basis at SC invitation; SC decides which observers and which meeting parts they attend.

### Work Plan
- Preparation: IMF staff will consult informally with SC members in early stages; a work plan will be distributed three weeks before the relevant SC meeting.
- Changes:
  - Strategic changes to the work plan sent to SC by email for endorsement on a non-objection/lapse-of-time basis; strategic changes include changes in objectives that leave the budget unchanged.
  - Budget adjustments of less than +/- 10 percent of the originally endorsed modules and sub-modules’ budget can be made without recourse to the SC.
  - For urgent cases, amendments to CD activities in the SC-endorsed work plan and new CD activities may be proposed between meetings with circulation of summaries on a non-objection/lapse-of-time basis.
  - Standard lapse-of-time (LOT) approval period is fifteen working days, adjustable under special circumstances.

### Reporting
- The SC will be asked to endorse the annual report.
- The IMF will provide on the Partners Connect platform (accessible to all D4D donors):
  - detailed modules and sub-modules descriptions no later than three months after endorsement of summaries;
  - annual modules and sub-modules assessments, any adjustments to the work plan, and updates on resource utilization;
  - end-of-modules and sub-modules assessments as projects are completed.

### Evaluation
- Activities financed under the D4D Fund will be subject to an external, independent evaluation.
- The SC shall endorse the terms of reference and methodology to be used in the independent evaluation.

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_Source: https://www.imf.org/-/media/files/capacity-developement/d4d/d4d-work-plan-june-2018.pdf_