International Development Association

FOR OFFICIAL USE ONLY Report No: PAD3206 Public Disclosure Authorized INTERNATIONAL DEVELOPMENT ASSOCIATION

PROJECT APPRAISAL DOCUMENT

ON PROPOSED GRANTS

TO THE BURKINA FASO IN THE AMOUNT OF SDR 21.7 MILLION (US$30.0 MILLION EQUIVALENT) REPUBLIC OF LIBERIA IN THE AMOUNT OF SDR 10.9 MILLION (US$15.0 MILLION EQUIVALENT) REPUBLIC OF SIERRA LEONE IN THE AMOUNT OF SDR 21.7 MILLION (US$30.0 MILLION EQUIVALENT) Public Disclosure Authorized REPUBLIC OF TOGO IN THE AMOUNT OF SDR 10.9 MILLION (US$15.0 MILLION EQUIVALENT) AFRICAN UNION IN THE AMOUNT OF SDR 1.9 MILLION (US$2.5 MILLION EQUIVALENT) ECONOMIC COMMUNITY OF WEST AFRICAN STATES IN THE AMOUNT OF SDR 5.5 MILLION (US$7.5 MILLION EQUIVALENT)

AND PROPOSED CREDITS

TO THE BURKINA FASO IN THE AMOUNT OF EUR 26.8 MILLION (US$30.0 MILLION EQUIVALENT) REPUBLIC OF CABO VERDE IN THE AMOUNT OF SDR 10.9 MILLION (US$15.0 MILLION EQUIVALENT) REPUBLIC OF CÔTE D'IVOIRE IN THE AMOUNT OF EUR 49 MILLION (US$54.0 MILLION EQUIVALENT) Public Disclosure Authorized REPUBLIC OF GHANA IN THE AMOUNT OF SDR 109.0 MILLION (US$150.0 MILLION EQUIVALENT) REPUBLIC OF LIBERIA IN THE AMOUNT OF SDR 10.9 MILLION (US$15.0 MILLION EQUIVALENT) REPUBLIC OF TOGO IN THE AMOUNT OF EUR 13.4 MILLION (US$15.0 MILLION EQUIVALENT)

FOR A

HARMONIZING AND IMPROVING STATISTICS IN WEST AFRICA PROJECT

March 5, 2020

Poverty and Equity Global Practice Africa Region Public Disclosure Authorized This document has a restricted distribution and may be used by recipients only in the performance of their official duties. Its contents may not otherwise be disclosed without World Bank authorization.

CURRENCY EQUIVALENTS Exchange Rate Effective as of December 31, 2019 for Burkina Faso, Liberia, Sierra Leone, Togo US$1.00 = SDR 0.723 US$1.00 = EURO 0.890

Exchange Rate Effective as of January 31, 2020 for African Union, Cabo Verde, Côte d’Ivoire, ECOWAS, Ghana US$1.00 = SDR 0.726 US$1.00 = EURO 0.906

Currency Units: CFA BCEAO Francs (XOF) Burkina Faso Cabo Verde Escudo (CVE) Cabo Verde CFA BCEAO Francs (XOF) Côte d'Ivoire Ghanaian Cedi (GHS) Ghana Liberian Dollar (LRD) Liberia Sierra Leonean Leone (SLL) Sierra Leone CFA BCEAO Francs (XOF) Togo United States Dollar (US$) African Union United States Dollar (US$) ECOWAS

FISCAL YEAR January 1 - December 31 (AU, Cabo Verde, Burkina Faso, Côte d’Ivoire, ECOWAS, Ghana, Liberia, Sierra Leone, Togo)

Regional Vice President: Hafez M. H. Ghanem Country Directors: Nathan Belete, Coralie Gevers, Soukeyna Kane, Pierre Laporte Regional Integration Director: Deborah L. Wetzel Global Practice Director: Carolina Sanchez Regional Directors: Asad Alam, Elisabeth Huybens Practice Managers: Andrew L. Dabalen, Pierella Paci Prospere Backiny-Yetna, Alejandro De la Fuente, Ayago Task Team Leaders: Esmubancha Wambile, Franck M. Adoho

ABBREVIATIONS AND ACRONYMS

AFRISTAT Economic and Statistical Observatory of Sub-Saharan Africa AGRISurvey Agricultural Integrated Survey AUC African Union Commission BP Bank Procedure CAPI Computer assisted Personal Interviewing CCMP Commission de Contrôle des Marchés Publics (Public Procurement Control Commission) CPF Country Partnership Framework CPI Consumer Price Index CPMD Coordination and Program Management Directorate CPMP Commission de la Passation des Marchés Publics (Public Procurement Commission) D4P Data for Policy DCMEF Direction du Contrôle des Marchés et des Engagements Financiers (Department for the Regulation of Public Procurement and Finance) DG Director General DGESS Direction Générale des Etudes et des Statistiques Sectorielles (General Directorate of Sectoral Studies and Statistics) DHS Demographic and Health Survey DNP Direção Nacional do Plano (National Directorate for Planning) DSF Déclaration Statistique et Fiscale (Statistical and Tax Declarations) ECOWAS Economic Community of West African States EHCVM Enquête Harmonisée sur les Conditions de Vie des Ménages (Harmonized Household Survey) ENSEA Ecole Nationale Supérieure de Statistique et d’Economie Appliquée EPA Enquête Permanente Agricole (Annual Agricultural Survey) ESMP Environmental and Social Management Plan EUR Euro FAO Food and Agriculture Organization FM Financial Management GIFMIS Government Integrated Financial Management Information System GLSS Ghana Living Standards Survey GSDP Ghana Statistics Development Project GSS Ghana Statistical Service HIES Household Income and Expenditure Survey HPC Housing and Population Census IBES Integrated Business Establishment Survey ICI Institutional Capacity Index ICT Information and Communications Technology IDA International Development Association IFR Interim financial report IMF International Monetary Fund INE Instituto Nacional de Estadística (National Institute of Statistics) INS Institut National de la Statistique (National Institute of Statistics) INSD Institut National de la Statistique et de la Démographie (National Institute of Statistics and Demography) INSEED Institut National de la Statistique et des Etudes Economiques et Démographiques

(National Institute for Statistics, Economic and Demographic Studies) IPSAS International Public Sector Accounting Standards IT Information Technology LFS Labor Force Survey LISGIS Liberia Institute of Statistics and Geo-Information Services MACs Ministries, agencies, and commissions MDAs Ministries, departments, and agencies MDTF Multi-donor Trust Fund MICS Multiple Indicator Cluster Survey NSDS National Strategy for the Development of Statistics NSO National Statistics Office NSS National Statistical System OC Oversight Committee OP Operational Policy PFMU Project Financial Management Unit PPCA Public Procurement and Concessions Act PDO Project Development Objective PIU Project implementation unit PPA Project Preparation Advance PSC Project Steering Committee PTSD Procurement, Travel, and Stores Division RCU Regional Coordinating Unit REDISSE Regional Disease Surveillance Systems Enhancement RGPH Recensement Général de la Population et de l'Habitat (Housing and Population Census) SCI Statistical Capacity Index SDG Sustainable Development Goal SHaSA2 Strategy for Harmonization of Statistics in Africa SLIHS Sierra Leone Integrated Household Survey SNA System of National Accounts STATAFRIC Pan-African Institute for Statistics STD Statistical and Tax Declarations STEP Systematic Tracking of Exchanges in Procurement TC Technical Committee ToR Terms of Reference UGPE Unidade de Gestão de Projetos Especiais (Special Projects Management Unit) UNECA United Nations Economic Commission for Africa US$ US Dollars WAEMU West Africa Economic and Monetary Union

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

TABLE OF CONTENTS DATASHEET ...... 1 I. STRATEGIC CONTEXT ...... 12 A. Regional and Country Context ...... 12 B. Sectoral and Institutional Context ...... 13 C. Relevance to Higher Level Objectives ...... 17 II. PROJECT DESCRIPTION ...... 18 A. Project Development Objective ...... 18 B. Project Components ...... 20 C. Project Beneficiaries ...... 37 D. Results Chain ...... 38 E. Rationale for World Bank Involvement and Role of Partners...... 39 F. Lessons Learned and Reflected in the Project Design ...... 40 III. IMPLEMENTATION ARRANGEMENTS ...... 41 A. Institutional and Implementation Arrangements ...... 41 B. Results Monitoring and Evaluation Arrangements...... 44 C. Sustainability ...... 44 IV. PROJECT APPRAISAL SUMMARY ...... 45 A. Technical, Economic, and Financial Analysis ...... 45 B. Fiduciary ...... 45 C. Safeguards ...... 47 V. KEY RISKS ...... 49 VI. RESULTS FRAMEWORK AND MONITORING ...... 51 ANNEX 1: Implementation Arrangements and Support Plan ...... 69 ANNEX 2: The Data for Policy Package ...... 86 ANNEX 3A: Summary of Core Social and Economic Statistics in Sub-Saharan Africa ...... 87 ANNEX 3B. Summary of Core Social and Economic Statistics in Beneficiary Countries ...... 89 ANNEX 4: Statistical Capacity Index, Africa, 2018...... 91 ANNEX 5: Planned Core Social and Economic Statistics in Project Countries, 2020-2029 ...... 92 ANNEX 6: Project Cost for Planned Core Social and Economic Statistics in Project Countries ...... 94 ANNEX 7: Modified Statistical Capacity Index Methodology ...... 98

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

TABLES Table 1: Country and regional project cost allocation (US$ million) ...... 21 Table 2: Auditing Arrangements ...... 73 Table 3: Disbursement Arrangements ...... 75 Table 4: FM Action Plan ...... 76 Table 5: Implementation Support Plan ...... 78 Table 6: AUC Matrix of Risk and Risk Mitigation Measures ...... 83

FIGURES Figure 1: Theory of Change ...... 38 Figure 2: Funds flow mechanism ...... 75

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

DATASHEET

BASIC INFORMATION BASIC INFO TABLE Country(ies) Project Name

Africa, Burkina Faso, Cote d'Ivoire, Cabo Harmonizing and Improving Statistics in West Africa Verde, Ghana, Liberia, Sierra Leone, Togo

Project ID Financing Instrument Environmental Assessment Category

Investment Project P169265 B-Partial Assessment Financing

Financing & Implementation Modalities [ ] Multiphase Programmatic Approach (MPA) [ ] Contingent Emergency Response Component (CERC) [ ] Series of Projects (SOP) [✓] Fragile State(s) [ ] Disbursement-linked Indicators (DLIs) [ ] Small State(s) [ ] Financial Intermediaries (FI) [ ] Fragile within a non-fragile Country

[ ] Project-Based Guarantee [ ] Conflict [ ] Deferred Drawdown [ ] Responding to Natural or Man-made Disaster [ ] Alternate Procurement Arrangements (APA)

Expected Approval Date Expected Closing Date

26-Mar-2020 31-Dec-2025

Bank/IFC Collaboration

Proposed Development Objective(s)

Strengthen the statistical systems of participating countries and regional bodies in Africa to harmonize, produce, disseminate and enhance the use of core economic and social statistics.

Page 1 of 100

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Components

Component Name Cost (US$, millions) Regional component: Harmonization, Data Collection, Quality Improvement, 334.21 Dissemination and Use of Core Social and Economic Statistics Country-Specific Component: Improving and modernizing physical and statistical 27.79 infrastructure

Project Management and Monitoring and Evaluation 17.00

Organizations

Borrower: Republic of Sierra Leone Republic of Ghana Republic of Liberia Republic of Cote d'Ivoire Republic of Togo Economic Community of West African States Burkina Faso Republic of Cabo Verde African Union Commission Implementing Agency: Ghana Statistical Service Liberia Institute of Statistics and Geo-Information Services (LISGIS) Statistics Sierra Leone (Stats SL) Togo Institut National de la Statistique et des Etudes Economiques et Démographiques (INSEED) Cote d'Ivoire L'Institut national de la statistique (INS) Burkina Faso Institut National de la Statistique et de la Démographie (INSD) Cabo Verde National Institute of Statistics (Instituto Nacional de Estadística, INE) and the Nationa

PROJECT FINANCING DATA (US$, Millions)

SUMMARY-NewFin1

Total Project Cost 379.00

Total Financing 379.00

of which IBRD/IDA 379.00 Financing Gap 0.00

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

DETAILS-NewFinEnh1

World Bank Group Financing

International Development Association (IDA) 379.00

IDA Credit 279.00

IDA Grant 100.00

IDA Resources (in US$, Millions)

Credit Amount Grant Amount Guarantee Amount Total Amount Burkina Faso 30.00 30.00 0.00 60.00 National PBA 10.00 10.00 0.00 20.00 Regional 20.00 20.00 0.00 40.00

Cote d'Ivoire 54.00 0.00 0.00 54.00 National PBA 18.00 0.00 0.00 18.00 Regional 36.00 0.00 0.00 36.00

Cabo Verde 15.00 0.00 0.00 15.00 National PBA 5.00 0.00 0.00 5.00 Regional 10.00 0.00 0.00 10.00

Ghana 150.00 0.00 0.00 150.00 National PBA 50.00 0.00 0.00 50.00 Regional 100.00 0.00 0.00 100.00

Liberia 15.00 15.00 0.00 30.00 National PBA 5.00 5.00 0.00 10.00

Regional 10.00 10.00 0.00 20.00

Sierra Leone 0.00 30.00 0.00 30.00 National PBA 0.00 10.00 0.00 10.00

Regional 0.00 20.00 0.00 20.00

Togo 15.00 15.00 0.00 30.00 National PBA 5.00 5.00 0.00 10.00

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Regional 10.00 10.00 0.00 20.00

Africa 0.00 10.00 0.00 10.00 Regional 0.00 10.00 0.00 10.00

Total 279.00 100.00 0.00 379.00

Expected Disbursements (in US$, Millions)

WB Fiscal Year 2020 2021 2022 2023 2024 2025 2026

Annual 10.00 20.00 40.00 65.00 80.00 90.00 74.00 Cumulative 10.00 30.00 70.00 135.00 215.00 305.00 379.00

INSTITUTIONAL DATA

Practice Area (Lead) Contributing Practice Areas Poverty and Equity

Climate Change and Disaster Screening This operation has been screened for short and long-term climate change and disaster risks

SYSTEMATIC OPERATIONS RISK-RATING TOOL (SORT)

Risk Category Rating

1. Political and Governance  Moderate

2. Macroeconomic  Moderate

3. Sector Strategies and Policies  Moderate

4. Technical Design of Project or Program  High

5. Institutional Capacity for Implementation and Sustainability  Substantial

6. Fiduciary  Substantial

7. Environment and Social  Moderate

8. Stakeholders  Moderate

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

9. Other

10. Overall  Substantial

COMPLIANCE

Policy Does the project depart from the CPF in content or in other significant respects?

[ ] Yes [✓] No

Does the project require any waivers of Bank policies?

[ ] Yes [✓] No

Safeguard Policies Triggered by the Project Yes No

Environmental Assessment OP/BP 4.01 ✔ Performance Standards for Private Sector Activities OP/BP 4.03 ✔ Natural Habitats OP/BP 4.04 ✔ Forests OP/BP 4.36 ✔ Pest Management OP 4.09 ✔ Physical Cultural Resources OP/BP 4.11 ✔ Indigenous Peoples OP/BP 4.10 ✔ Involuntary Resettlement OP/BP 4.12 ✔ Safety of Dams OP/BP 4.37 ✔ Projects on International Waterways OP/BP 7.50 ✔ Projects in Disputed Areas OP/BP 7.60 ✔

Legal Covenants

Sections and Description Cote d'Ivoire, Schedule 2, Section I, A. 1. Steering Committee: (a) Not later than six (6) months after the Effective Date or any later date agreed upon in writing with the Association, the Recipient shall cause the PIE to establish, and thereafter maintain at all times during the implementation of the Project, a Steering Committee, with a composition, mandate, and resources satisfactory tothe Association.

Sections and Description

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Cote d'Ivoire, Schedule 2, Section I, A. 2. To ensure successful Project implementation, the Recipient shall, not later than six (6) months after the Effectiveness Date, or at any later date agreed upon in writing with the Association, establish, and thereafter maintain at all times during Project implementation, a Technical Committee, under terms of reference and with staff, resources and representation satisfactory to the Association.

Sections and Description Cote d'Ivoire, Schedule 2, Section I, A. 3. Not later than six (6) months after the Effective Date or any later date agreed upon in writing with the Association, the Recipient shall establish, and thereafter maintain, through the PIE, a Project Implementation Unit, with functions, staffing and resources satisfactory to the Association. The Project Implementation Unit shall be composed inter alia of a Project coordinator, a monitoring and evaluation specialist, a financial management specialist, a procurement specialist and an administrative assistant.

Sections and Description Cote d'Ivoire, Schedule 2, Section I, A. 4. Not later than three (3) month after the Effective Date, or at a later date agreed upon in writing with the Association, the Recipient shall recruit for the PIU: (i) a Project Coordinator; (ii) an internal auditor, (iii) an external auditor, and (iv) a financial management specialist; (v) an accountant; and (vi) a procurement specialist; all with terms of reference, qualifications and experience satisfactory to the Association.

Sections and Description Cote d'Ivoire, Schedule 2, Section I, A. 5. Not later than five (5) months after the Effective Date, or at a later date agreed upon in writing with the Association, the Recipient shall enter into a memorandum of understanding with the PIE to facilitate cooperation and collaboration between the Recipient and the PIE under the Project to establish the arrangements necessary to allow the Inspection Générale des Finances to conduct regular internal audit missions.

Sections and Description Cote d'Ivoire, Schedule 2, Section I, A. 5. Not later than five (5) months after the Effective Date, or at a later date agreed upon in writing with the Association, the Recipient shall have acquired, installed and customized an accounting software for the Project, with specifications and in a manner satisfactory to the Association.

Sections and Description Burkina Faso, Schedule 2, Section I, A, 2. Not later than one (1) month after the Effective Date, or at any later date agreed upon in writing with the Association, establish, and thereafter maintain, a Technical Committee, under terms of reference and with staff,resources and representation satisfactory to the Association. The Technical Committee shall provide technical coordination and guidance to the PIE, be vested with the responsibility to review the AWP&B, and monitoring its implementation, all in accordance with the provisions of this Agreement and the Project Operations Manual.

Sections and Description Burkina Faso, Schedule 2, Section I, A, 4. Not later than one (1) month after the Effective Date, or at any later date agreed upon in writing with the Association, establish, and thereafter maintain, a Project Implementation Unit, with functions, staffing and resources satisfactory to the Association. At a minimum, and throughout Project

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

implementation, the Project Implementation Unit shall be composed of a Project Coordinator, a Project manager, a statistics specialist, a financial management specialist, an accountant, a procurement specialist and an administrative assistant, all with terms of reference, experience and qualifications satisfactory to the Association.

Sections and Description Burkina Faso, Schedule 2, Section I, A, 5. Not later than one (1) month after the Effective Date, or at any later date agreed upon in writing with the Association, the Recipient, through the PIE, shall: (i) recruit or appoint a Project manager; and (ii) recruit aprocurement specialist; with qualifications, experience and terms of reference acceptable to the Association

Sections and Description Burkina Faso, Schedule 2, Section I, A, 6. Not later than three (3) months after the Effective Date, or at any later date agreed upon in writing with the Association, the Recipient, through the PIE, shall recruit for the Project: (i) an external auditor; (ii) a financial management specialist, and (iii) an accountant; all with qualifications, experience and terms of reference acceptable to the Association and in accordance with the Procurement Regulations.

Sections and Description Ghana, Schedule 2, Section I, A, 2. Not later than two (2) months after the Effective Date or any later date agreed upon in writing with the Association, operationalize and thereafter maintain at all times during the implementation of the Project, the Technical Committee within the PIE, under terms of reference and with staff, resources and representation satisfactory to the Association. The Technical Committee shall be tasked with reviewing the Project implementation progress, addressing any critical issues, reviewing Project work programs, budgets, procurement plans, financial, and monitoring and evaluation reports.

Sections and Description Ghana, Schedule 2, Section I, A, 1. Not later than two (2) months after the Effective Date or any later date agreed upon in writing with the Association, operationalize, and thereafter maintain at all times during the implementation of the Project, a Project Oversight Committee, with a composition, mandate, and resources satisfactory to the Association. The Project Oversight Committee shall be responsible for providing overall oversight and governance, including reviewing and endorsing for approval by the Association of the Annual Work Plans and Budgets, and ensuring their consistency with the Project Operations Manual.

Sections and Description Ghana, Schedule 2, Section I, A, 4. No later than three (3) months from the Effective Date, or at any later date agreed upon in writing with the Association, recruit or engage an external auditor for the Project, with qualifications, experience and terms of reference acceptable to the Association.

Sections and Description ECOWAS, Schedule 2, Section I, A, 1. Not later than 3 months after the Effective Date or any later date agreed upon in writing with the Association, the Recipient shall establish, and thereafter maintain throughout Project implementation, the Regional Coordination Unit (RCU) within ECOWAS, under terms of reference, resources and representation satisfactory to the Association, and with staff including inter alia a Project coordinator, two statistics specialists, a financial management specialist, and an assistant, all with terms of reference, qualifications and experience satisfactory to the Association. The RCU shall provide day-to-day oversight over the implementation of Parts 1.1(B) and 3 of the Project, including fiduciary and procurement, and shall be vested with responsibility for

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

providing technical design of tools and management documents, developing and concurring with the AWP&B, and monitoring its implementation.

Sections and Description ECOWAS, Schedule 2, Section I, A, 2. (i) No later than three (3) months after the Effective Date or at a later date agreed upon in writing with the Association, appoint an external auditor pursuant to the Procurement Regulations;

Sections and Description ECOWAS, Schedule 2, Section I, A, 2. (ii) no later than six (6) months after the Effective Date or at a later date agreed upon in writing with the Association, recruit a procurement specialist, with terms of reference, qualifications and experience satisfactory to the Association.

Sections and Description Liberia, Schedule 2, Section I, A, 5. Without limiting the foregoing, the Recipient shall cause the PIE to, no later than three (3) months after the Effective Date, or at any later date agreed upon in writing with the Association: (A) recruit an external auditor, in accordance with terms of reference acceptable to the Association; (B) recruit a procurement specialist, with terms of reference, qualifications and experience satisfactory to the Association.

Sections and Description Liberia, Schedule 2, Section I, A, 3. Not later than 3 months after the Effective Date, or any later date agreed upon in writing with the Association, the Recipient shall cause the PIE to establish and thereafter maintain at all times during the implementation of the Project, a Project Technical Committee, with a composition, mandate, and resources satisfactory to the Association. The Project Technical Committee shall be responsible for all technical aspects of implementation of Parts 1.2, 1.3, 1.4, 1.5, 1.7, 1.8 (B), 2.5 and 3 of the Project.

Sections and Description Liberia, Schedule 2, Section I, A, 4. Not later than 3 months after the Effective Date, or any later date agreed upon in writing with the Association, the Recipient shall cause the PIE to establish and thereafter maintain at all times during the implementation of the Project, a Project Implementation Team, with a composition, mandate, and resources satisfactory to the Association. The Project Implementation Team shall be responsible for day-to-day administration of overall planning, coordination, technical, procurement, preparation and consolidation of AWP&B, monitoring, evaluation, reporting and communication activities under Parts 1.2, 1.3, 1.4, 1.5, 1.7, 1.8 (B), 2.5 and 3 of the Project, all in accordance with the provisions of this Agreement and the Project Operations Manual.

Sections and Description Togo, Schedule 2, Section I, A, 1, (a) Not later than three (3) months after the Effective Date, or at any later date agreed upon in writing with the Association, the Recipient shall cause the PIE to establish and thereafter maintain at all times during the implementation of the Project, a Co-ordination Committee, with a composition, mandate, and resources satisfactory to the Association.

Sections and Description

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Togo, Schedule 2, Section I, A, 2, (a) maintain, at all times during the implementation of the Project, the PIE, and shall, not later than three (3) months after the Effective Date, or at any later date agreed upon in writing with the Association, establish, and thereafter maintain, through the PIE, a Project Implementation Unit, with functions, staffing and resources satisfactory to the Association, including inter alia, a Project coordinator, a focal point, a statistics specialist for monitoring and evaluation, a procurement specialist, a financial management specialist¸ and an accountant. Without limitation to the provisions of Section I.A.1 of this Schedule, the PIU shall have responsibility for the day-to-day administration of overall planning, coordination, implementation, technical, fiduciary, procurement, preparation of the AWP&B, coordination, monitoring, evaluation, reporting and communication activities under the Project, all in accordance with the provisions of this Agreement and the Project Operations Manual;

Sections and Description AU, Schedule 2, Section I, A, 2. Not later than three (3) months from the Effective Date or at a later date agreed upon in writing with the Association, the Recipient shall: (a) recruit or assign appropriate and agreed upon with the Association, for the PIT: (i) a procurement specialist; (ii) a contract management staff, and (iii) a financial management specialist; all with terms of reference experience and qualifications satisfactory to the Association; (b) recruit for the Project an external auditor, in accordance with the Procurement Regulations; and (c) confirm to the satisfaction of the Association that the Recipient’s internal audit directorate is adequately staffed.

Sections and Description Cabo Verde, Schedule 2, Section I. A (b) No later than three (3) months from the Effective Date, or any later date agreed upon in writing with the Association: (i) recruit for the Project Management Unit, (A) a Project manager, (B) an accountant, (C) an internal auditor, (D) an external auditor and (E) a procurement specialist; all with qualifications, experience and terms of reference acceptable to the Association. (ii) customize for the Project Management Unit, an accounting software with features and of quality satisfactory to the Association.

Sections and Description Sierra Leone, Schedule 2, Section I, A, 3. No later than three (3) months from the Effective Date, or any later date agreed upon in writing with the Association: (i) recruit for the Project Fiduciary Management Unit, an external auditor, in accordance with Procurement Regulations and, assign a financial management specialist and procurement specialist with terms of reference, qualifications and experience satisfactory to the Association; and (ii) cause the PIE to recruit or appoint for the Project, a Project coordinator, and an environmental safeguards specialist, with terms of reference, qualifications and experience satisfactory to the Association.

Conditions

Type Description Effectiveness Cabo Verde, Article V, Section 5.01. (a) The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Program Implementing Entity under terms and conditions satisfactory to the Association.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Type Description Effectiveness Cabo Verde, Article V, Section 5.01. (b) The Recipient, through the Project Implementing Entity, shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Effectiveness Cote d'Ivoire, Article V, Section 5.01. (a) The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Program Implementing Entity under terms and conditions satisfactory to the Association

Type Description Effectiveness Cote d'Ivoire, Article V, Section 5.01. (b) The Recipient, through the Project Implementing Entity shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Disbursement Cote d’Ivoire, Schedule 2, Section III, B.1 (b) under Category (2), until and unless the Association has received satisfactory evidence, for purposes of implementation of Parts 1.2 (B) and (C) of the Project, of: (i) a detailed program of activities in accordance with the Project Operations Manual; and (ii) sufficient budgetary resources within the PIE to conduct said activities.

Type Description Disbursement Cote d’Ivoire, Schedule 2, Section III, B.1 (c) under Category (3), until and unless the Association has received a list of the Young Professional Program Beneficiaries to be recruited under Part 1.8 (A) of the Project in form and substance satisfactory to the Association, including, inter alia, the verification of the qualifications of said Young Professional Program Beneficiaries and the adequacy with the procedures and criteria established in the Project Operations Manual.

Type Description Effectiveness Burkina Faso, Article V, Section 5.01. (a) The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Project Implementing Entity under terms and conditions satisfactory to the Association.

Type Description Effectiveness Burkina Faso, Article V, Section 5.01. (b) The Recipient, through the Project Implementing Entity, shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Effectiveness Burkina Faso, Article V, Section 5.01. (c) The Recipient shall appoint for the Project a Project Coordinator, with terms of reference, qualifications and experience satisfactory to the Association.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Type Description Effectiveness Ghana, Article V, Section 5.01, (a)The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Project Implementing Entity under terms and conditions satisfactory to the Association.

Type Description Effectiveness Ghana, Article V, Section 5.01, (b) The Recipient, through the PIE, shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Effectiveness Sierra Leone, Article V, Section 5.01, (a). The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Project Implementing Entity under terms and conditions satisfactory to the Association.

Type Description Effectiveness Sierra Leone, Article V, Section 5.01, (b).The Recipient through the PIE shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Effectiveness Liberia, Article V, Section 5.01, (a).The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Project Implementing Entity under terms and conditions satisfactory to the Association.

Type Description Effectiveness Liberia, Article V, Section 5.01, (b) The Recipient, through the PIE shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Effectiveness Togo, Article V, Section 5.01, (a) The Subsidiary Agreement has been duly executed on behalf of the Recipient and the Project Implementing Entity under terms and conditions satisfactory to the Association.

Type Description Effectiveness Togo, Article V, Section 5.0,1 (b) The Recipient, through the PIE, shall have adopted the Project Operations Manual, in form and substance satisfactory to the Association.

Type Description Effectiveness AU, Article V, Section 5.01.The Recipient shall have adopted the Project Operations Manual under terms and conditions acceptable to the Association.

Type Description Effectiveness ECOWAS, Article V, Section 5.01. The Recipient shall have adopted the Project Operations Manual under terms and conditions acceptable to the Association.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

I. STRATEGIC CONTEXT

A. Regional and Country Context

1. Although Africa1 has made significant progress on poverty in recent decades, substantial challenges remain. The poverty rate declined from 54 percent in 1990 to 41 percent in 2015, but because of rapid population growth, the number of people living in poverty increased from 278 million to 413 million over the same period (Beegle and Christiaensen 2019)2. The region has struggled to achieve prosperity. Natural disasters, conflict, and displacement affect large sections of the population. Although high commodity prices for oil, minerals, and agriculture drive good economic performance in many African countries, the region faces many challenges in diversifying its economies, which offers better prospects for inclusive growth.

2. These regional trends are also seen in the seven countries that this project has targeted. All of these countries have seen a significant decrease in poverty since 2000, but four of them have seen an increase in the number of poor. In all the participating countries, poverty rates are higher in rural areas, and agriculture accounts for a significant share of gross domestic product and a large share of the labor force. Most of these countries rely on a few key commodities for export earnings (cotton and gold in Burkina Faso, iron ore and rubber in Liberia, cocoa in Côte d'Ivoire, oil, gold and cocoa in Ghana, iron in Sierra Leone). Cabo Verde depends heavily on tourism. Reliance on climate-sensitive activities renders many of these countries vulnerable to climate variability and change, which is expected to manifest in higher temperatures, extreme weather events such as heavy rains, and rising sea levels. The increasing variability and the incidence of extreme weather events can be expected to have a negative impact on crop production and households’ livelihood. An increase in maximum temperature and an increase in the likelihood of drought will contribute to land degradation and herd mortality rates, which will have negative effects on pastoralist activities in the region. Sierra Leone suffers recurrent flash floods, as does northern Burkina Faso in the Sahel (one of the most vulnerable regions globally to climate change) with droughts. The archipelago country of Cabo Verde is also highly susceptible to extreme natural phenomena. The Ebola epidemic of 2014-2015 hit Sierra Leone and Liberia hard. Sierra Leone and Liberia face high inflation and low growth. Burkina Faso faces a challenging security situation with increasing terrorist attacks. Côte d'Ivoire is experiencing political tensions ahead of planned elections in 2020. These countries also face significant social and economic gender gaps; the nature and magnitude of gender inequality varies from country to country. Gender equality in Burkina Faso, Côte d’Ivoire, and Togo ranks in the bottom 10 percent of the world according to the Global Gender Gap Indicator of the World Economic Forum (129th, 131st, and 134th, respectively). Whereas other countries in this group do not perform well (Liberia, 97; Ghana,107; and Sierra Leone, 111), Cabo Verde is ranked 52nd.

3. Good data are essential to address the challenges facing the region in general and the seven countries in this project in particular. Good statistics can inform policy making and enable efficient allocation of scarce resources by governments facing numerous challenges and are necessary to track progress and assess the effect of policies. Good statistics improve the transparency and accountability of policy making, which is essential for good governance. Good-quality, harmonized statistics can also support closer regional integration as a way to address some of the challenges facing countries in the region. Having more-disaggregated data will also improve understanding of the exclusion of specific groups to support formulation of inclusive policies and development interventions.

1 Throughout this document, “Africa” refers to sub-Saharan Africa. 2 Beegle, Kathleen; Christiaensen, Luc. 2019. Accelerating Poverty Reduction in Africa. Washington, DC: World Bank.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

B. Sectoral and Institutional Context

4. There has been progress in the production of statistics over the last 20 years in Africa. From the early 2000s, strategic planning through National Strategies for the Development of Statistics (NSDS) has been adopted, with most African countries having implemented one or more strategies by 2015. These have helped countries improve their legal framework with new statistical laws and strengthen the status of their national statistical offices (NSOs). Several countries use the 2008 System of National Accounts (SNA) (Annex 1). The geographic coverage and timeliness of the consumer price index (CPI) has also improved. External trade statistics are harmonized in many countries, and most of the countries use the same software, EUROTRACE. The number of household surveys that collect data on monetary and nonmonetary dimensions of poverty has increased, thanks to donor-funded programs such as the Demographic and Health Survey (DHS) and the Multiple Indicator Cluster Survey (MICS).

5. Since 2015, the World Bank has committed to increasing the statistical capacity of low-income countries, given also the multiple challenges in terms of the available statistics to monitor the World Bank twin goals of ending extreme poverty and promoting shared prosperity. Initially, the World Bank focused on household surveys, helping low-income countries conduct at least one household survey every three to five years through standalone projects, sizeable statistical components in other projects, and trust funds. There has been a significant increase in the availability of household-level data since 2015. Between 2016 and 2018, 44 countries in sub-Saharan Africa conducted household surveys. Only three countries (Central African Republic, Equatorial Guinea, Eritrea) have not conducted a survey since 2010.

6. The increase in the World Bank Statistical Capacity Indicator (SCI)3 confirms the overall progress in statistical capacity building in Africa, but the continent still lags other regions. The SCI provides a grade for every country in the world on the methodology, data sources, and periodicity and timeliness of core economic and social statistics. The SCI for Africa increased from 55 in 2004 to 62.4 in 2018. There have been improvements in all three dimensions of the SCI: methodology, data sources, and, periodicity and timeliness. Despite this progress, the SCI for Africa is still the lowest among developing regions. Data deprivation, data quality, comparability over time and between countries, data accessibility, and the limited use of data to inform policy are among the weaknesses of statistical systems in Africa, although there is considerable variation between countries within Africa (Annex 4)4.

7. Institutional weaknesses and inconsistent financing limit the quality of statistics in Africa. NSOs do not always have the autonomy to recruit staff or design incentives. Administrative and technical coordination of NSOs is often inadequate or even nonexistent. Financing mechanisms of NSOs are unreliable and insufficient in many African countries, leading to infrequent data collection and inadequate human resources. Although these institutional challenges are different from country to country, they largely explain weak performance. The African Union in 2013 made a diagnostic on statistics for the region5 and discovered institutional weaknesses, including a low level of political support for statistics, low priority and inadequate funding for statistics, inadequate human resources, inadequate coordination, and insufficient use of data for policy (D4P) and decision-making; organizational weaknesses, namely inability to produce adequate data, poor knowledge management, data quality problems, unsatisfactory data management, analysis, and reporting, poor dissemination of and access to information; and

3 The World Bank’s SCI is a composite score assessing a country’s statistical system based on a diagnostic framework assessing methodology, data sources, and periodicity and timeliness. Countries are scored on 25 criteria in these areas using publicly available information and country input. The overall SCI score is calculated as the average of all three area scores on a scale of 0 to 100. 4 The countries participating in the project have varied SCI score with most having above average rating. Paragraph 22 states the reasons for selecting these countries to be part of the project. 5 Africa Union, Agenda 2063. 13

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

inability to produce data for emerging problems such as HIV and AIDS, environment and climate change, and more recently, the food and financial crises.

8. As a consequence, there are important data gaps in many areas. Based on the 2012 United Nations Economic Commission for Africa (UNECA) report, 15 countries did not conduct a population census for the 2000 round (1995 to 2004), and six did not conduct one during the 2010 round (2005-2014). In countries without a recent census, out- of-date sampling frames must be used for surveys (e.g., household, agriculture), which affects the quality of the data. Population censuses are not the only area of social statistics with data gaps. Many countries do not conduct household surveys with the recommended frequency (Annex 3), and data on some critical social concerns, such as disability, are insufficient. As for economic statistics, agricultural and enterprise censuses are irregular in many countries, and the quality of economic statistics is problematic. Approximately 16 countries have not conducted an agricultural survey or census in the last eight years (Annex 3). Geographic coverage of CPI data is incomplete in many countries because the data cover only urban areas (e.g. Sierra Leone) and sometimes only the capital city (e.g. in Liberia). Problems with CPI also include old base years (e.g. Sierra Leone) and the use of different software which are not standardized (PRIMA, Phoenix etc.). Input/output tables6 are not produced each time national accounts are produced. In many English-speaking countries, basic data (particularly on enterprises) to produce national accounts are not detailed. In many French-speaking countries, more data are available, though quality is affected by incomplete coverage.

9. Lack of relevant gender statistics hinders the region’s effort to track progress on gender inequality and design policies to address it. Gender data are important because they help stakeholders understand the extent of gender gaps and design interventions to address them. Gender statistics must reflect the many areas in which women and men do not have the same opportunities (e.g., the labor market) or where women’s and men’s lives may be affected in different ways (e.g., gender-based violence). The Inter-Agency and Expert Group on Gender Statistics prepared the minimum list of gender indicators as a guide for the national production and international compilation of gender statistics. In addition, NSOs of countries in the region have not been disseminating relevant gender statistics through official channels. Therefore, support to statistical system development in the region will also increase availability of relevant gender statistics, specifically the indicators listed under the minimum list.

10. Data standards are outdated, access to data is weak, and there is insufficient use of D4P making. Not all countries use the most recent international standards for national accounts7 or recent base years for national accounts and CPI. Many countries use outdated international standards or unharmonized methodologies to calculate poverty and other indicators of wellbeing, as well as macroeconomic statistics. Poverty and macroeconomic trends are also often inconsistent because of methodological changes in household surveys. Although most NSOs have increased the visibility of their statistical products through websites where reports (and sometimes methodologies) are accessible, few websites allow interactive access to data, which allows policy makers to quickly find the statistics they need. If microdata sets are available, it is often through platforms such as the World Bank microdata platform, which international researchers and organizations are more likely to use than national organizations or policy makers. In addition to problems with standards and access, there is insufficient use of D4P making, leading to lack of demand for data and reluctance of policy makers to increase funds for statistics.

11. Emerging challenges require a modern, adaptive approach to the rapidly changing data collection environment. Data are traditionally collected through surveys, censuses, and administrative sources. Censuses are conducted only

6 Input/output tables are used to build social accounting matrices and as an input for economic simulations (e.g., distributional effect of macro and fiscal policies). 7 Approximately 34 countries are using the 1993 SNA, five are using the 1998 SNA, and eight are using the 2008 SNA.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

every 10 years and surveys every three to five years at best. Surveys take time to design, implement, and process, so it is difficult to adapt them quickly to an emergency situation. Adapting administrative data collection processes is even more difficult. These traditional forms of data collection are often not possible in situations of fragility (insecurity may prevent survey data from being collected, parts of the country may be outside of effective government control and thus administrative statistics, sampling is difficult in situations in which populations are being displaced) or disease outbreak (again, preventing movement of data collection teams, possibly leading to population movement). New sources of big data —especially data from satellites and call records from phone companies—that are increasingly available in Africa can complement traditional data sources in a number of ways. These sources of data are generated continuously, even in emergency situations, and can be geographically disaggregated to a very fine level. Combined with household survey data, they can be used to provide estimates of welfare that are disaggregated in space (e.g., poverty mapping) or time (e.g., SWIFT —Survey of Well-Being via Instant and Frequent Tracking) estimates of poverty between rounds of a household survey. They provide almost real-time data even in emergency situations, allowing for better understanding of how a situation is developing and better planning of responses.

12. Against this backdrop, the continent has recently made an effort to harmonize, benchmark, and make readily available critical country statistics through the African Union Strategy for Harmonization of Statistics in Africa (SHaSA2) 2017-2026, a continent-wide initiative that the African heads of state have adopted that aims to address the constraints identified above that African statistical systems face and promote the regional integration agenda. SHaSA2 is anchored in four strategic themes: production of better-quality statistics through harmonization of statistical standards and methods; strengthening cooperation between institutions within the African statistical system, establishing effective coordination mechanisms, and setting statistical priorities to support the integration agenda; building sustainable institutional capacity through reform of national statistical systems (NSSs) and establishing an effective technological environment for dissemination and use of data; and promoting a culture of quality decision making.

13. The time is also right within the World Bank to harmonize and benchmark statistics in Africa on a regional basis. With World Bank support, eight West African members of the West Africa Economic and Monetary Union (WAEMU) have worked together to harmonize their surveys since 2016, including questionnaires and poverty methodologies. The first round of surveys has been completed. As part of the World Bank's commitment to increasing the statistical capacity of low-income countries, it has been developing a guidebook based on research standards and field-tested best practices to implement, improve, and modernize nationally representative multitopic household surveys for welfare and poverty monitoring. The good results achieved in household surveys suggest that it would be beneficial to expand harmonization to other areas of statistics.

14. The list of data that are crucial for policy making and in need of harmonization can become long quickly, but a core set of economic, social, and administrative statistics has been identified after the type of data required for monitoring national development plans, the Sustainable Development Goals (SDGs), and legal frameworks from NSOs to coordinate NSSs were reviewed. The World Bank has designed a core set of statistics—the D4P package8—that is aligned with the SHaSA2 initiative in that it aims to help countries produce not only D4P making, but also better- quality statistics through harmonization and use of international standards. The goal of the D4P package is improve five core statistical systems: household-based surveys (and support of population censuses), firm-based surveys (and support to establish censuses and a sufficiently complete and maintained establishment register), agricultural data, price data, and administrative data (with a focus on health, education, and environmental sustainability). The D4P package also includes two complementary data systems: national accounts and big data (Annex 2). Data from

8 In the “IDA19 Second Replenishment Meeting: Special Theme - Governance and Institutions (English)” which includes the description of the Data for Policy and its corresponding policy commitment (pillar 4, paragraphs 72 to 77). 15

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

household-based surveys can be used to obtain sex- and disability-disaggregated and individual-level data on physical and financial assets, employment and labor market outcomes, and (selected) human capital indicators, in line with the World Bank Group gender strategy. An effort will also be made to improve disability data collection, guided by global standards and best practices, such as using the Washington Group’s Short Set of Questions on Disability, which is critical to align with the World Bank’s 10 commitments made in 2018 regarding disability inclusion.

15. There are already initiatives supporting the production of statistics in many of the D4P package areas that the project can consolidate and make use of. The World Bank has been developing a guidebook to implementing household surveys and harmonizing questionnaire modules and the accompanying methodological notes to assess and monitor poverty through initiatives such as WAEMU. The 50 by 2030 initiative9 aims to operationalize an integrated agricultural survey systems, including harmonizing data tools and expanding the World Bank household- based Living Standards Measurement Study–Integrated Surveys on Agriculture and the farm-based Agricultural Integrated Survey (AGRISurvey) that the Food and Agriculture Organization (FAO) has implemented. Economic Community of West African States (ECOWAS) has an ongoing program to help member countries adopt the 2008 SNA. The regional project can piggy-back on and consolidate these initiatives.

16. The D4P package will have a regional approach even though it will be implemented on a country-by-country basis. Africa’s low score on the methodology and data sources dimension of the SCI is mainly due to the countries not adopting the most recent international standards. Efforts have been made across the region to change this; many countries are working to implement the 2008 SNA. A regional project of this type allows for expanding such efforts more cost-effectively and ensures comparability of data across countries.

17. A regional approach on statistics can provide an invaluable public good for regional integration; comparable statistics are instrumental in areas such as promotion of free trade and creation of a unique currency. The African Union has launched the operational phase of the Africa Continental Free Trade Area to establish a single market for goods and services across the continent, allow the free movement of business travelers and investments, and create a continental customs union to streamline trade and attract long-term investment. Good statistics will be necessary to evaluate the progress of regional integration and the effect on the population’s well-being. At a subregional level, progressive move of ECOWAS member states towards a common currency union would also require good statistics to assess the convergence of economic policy, a prerequisite for this goal.

18. A regional approach facilitates coordination among NSOs by introducing and expanding innovations, peer-to- peer reviewing, and learning and can generate positive externalities. Because NSOs rarely have comparable in- country counterparts, they often look to their peers in other countries to innovate, and a regional operational program can facilitate this cross-fertilization. New technologies for data collection or storage, measurement, and analysis can be developed and tested in one country and transferred to others in similar situations, generating low- cost benefits. The adoption of similar standards also creates economies of scale and makes it easier to transfer knowledge (and build capacity) because peers will be familiar with the methods and standards. Adoption of common standards can spread beyond the beneficiaries of the project if they are proven to work, as was the case for the WAEMU household survey harmonization project, whose common methodology has been adopted in at least eight countries. Training can be conducted more efficiently, by organizing a few regional workshops rather than providing training country by country, reducing training costs substantially. Such harmonized statistics also allow for the

9 The objective of the 50 by2030 initiative is to improve the availability, quality, and usability of integrated surveys in 50 low- and lower- middle-income countries by 2030, sharpening the focus on agriculture and moving toward improvement of integrated agricultural surveys. Three tools have been developed: AGRISurvey, a farm-based modular survey covering farm and nonfarm households; the Living Standard Measurement Survey–Integrated Survey on Agriculture, and the Integrated Household and Agriculture Survey.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

creation of a shared pool of skills in the region as the statisticians in the statistical agencies get trained on common standards, methods, and tools.

19. The regional project will use a modular approach (of not having all the same components everywhere) to introduce the D4P package, but the speed and process will be different for each country, recognizing initial institutional and human resource capacities and the amount of already existing core statistics. Sequencing needs will be considered when determining the project's timeline, and the project’s introduction will be phased such that the workload for institutions is distributed over time. Some countries are more advanced than others in terms of data availability. The West African members of WAEMU already have a project to extend coverage of their CPI. Ghana has a good system of household surveys. Some NSOs are also well staffed, whereas others lack qualified staff and therefore do not have the capacity to conduct multiple surveys in the same year. Different donor partners are present in the seven countries. All these factors are taken into account in the design of the project.

20. The project includes activities that stimulate demand for data and increase the capacity of NSOs. As stated earlier, government financing of statistics is low in many African countries. In some countries, the government budget is just enough for staff salaries and very basic data collection activities. Sustainable statistical systems cannot rely on donor financing. The project will work to improve data access and data use for policy making. Accessibility of data to other government agencies and to the research community generates analytical products, which can increase in- country demand for statistics. High-performing statistical systems also require adequate human resources and motivated staff, adequate physical facilities, and institutional autonomy. When NSOs lack human resources, capacity building will be provided according to the training needed in each country. The project will ensure that each country has at least the minimum physical infrastructure, including facilities and information technology (IT) equipment, required for an NSO to operate and be able to collect and process data. All these complementary activities will be implemented at the national level, depending on the situation of each country.

21. Creation of a regional ecosystem of statistics allowing NSOs to improve production and dissemination of core statistics gives an incremental value to this project relative to past World Bank projects on statistics. This ecosystem also facilitates provision of regional public goods that may facilitate regional integration; economies of scale and spillovers in learning and knowledge sharing; and introduction of leapfrogging technologies and new types of data, such as big data.

22. The regional project will start with seven countries (Burkina Faso, Cabo Verde, Côte d’Ivoire, Ghana, Liberia, Sierra Leone, Togo) but is expected to be expanded because many more have expressed interest in joining. There are several reasons to start with a limited number of countries. First, the start-up costs of covering all countries would be large and implementation challenging. Second, other countries have ongoing statistical projects, and it is better to let these projects reach their end. All seven are West African countries with some important similarities, including that they all belong to ECOWAS. Except Cabo Verde, they all have good potential in agriculture and many other natural resources. Following this initial project, there are also efforts to prepare similar projects in the other regional economic communities, including the East African Community and the South African Development Community.

C. Relevance to Higher Level Objectives

23. The regional approach of the project is aligned with SHaSA2, a continent-wide initiative that the African heads of state have adopted that is designed to address the constraints facing the African statistical systems identified above and promote the regional integration agenda. SHaSA2 is one of the core commitments of the heads of state for the Minimum Integration Program. For that reason, its principles guide all African regional organizations, regional

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

integration communities, and regional development organizations, such as UNECA and the African Development Bank, that support statistical development in Africa. It is also timely, because in recent years, African governments and the international community have called for an improved effort to monitor international and regional development commitments, such as SDGs and the African Union’s Vision 2063. It is important to invest in sustainable data systems that countries can maintain over time, taking into account their own financial and human resources

24. The project supports the implementation of ECOWAS’s regional strategy 2019-2023, which is also aligned with SHaSA2. ECOWAS has harmonization of statistics as part of its mandate and can therefore be used as a regional body for implementation of this project. By harmonizing economic statistics, filling the gap on important data, and producing harmonized SDG estimates, the project will be a powerful means of implementing the ECOWAS 2019-2023 strategy. The ECOWAS vision is to mobilize regional resources to improve human capital and create opportunities for sustainable development, to promote peace and security, and to strengthen institutions of democratic governance using appropriate international standards. The overall goal is to raise the living standards of its member country populations. Timely, well-harmonized statistics will be needed to gauge progress toward this goal.

25. The project reflects priorities emphasized in World Bank country strategies. Country Partnership Frameworks (CPF)10 and systematic country diagnostics have identified weaknesses in statistics as a barrier to effective monitoring of strategies of development and SDGs.

26. The project will also help implement the World Bank Regional Integration Assistance Strategy for Sub-Saharan Africa, which is organized around four main pillars: i) generate economic dynamism along regional economic corridors; ii) develop functioning regional markets in priority sectors; iii) scale-up access to quality public services and entrepreneurship through complementary regional solutions; and iv) promote collective action to address risks of regional economic spillovers, fragility, epidemic and climate ‘hot spots’. This project contributes to the second and third pillars by collecting data that help achieve regional economic integration. By generating data critical to national and regional planning and monitoring, the project will also help in attaining an additional objective of the Regional Integration Assistance Strategy for Sub-Saharan Africa: strengthening the connection between regional policy commitments and national planning.

27. Operationalizing the World Bank Group Gender Strategy requires a data-driven approach. The World Bank Group Gender Strategy document for 2016 to 2023 calls for better country-level diagnostics on gender gaps in systematic country diagnostics and country partnership frameworks to “highlight how closing the key gender gaps in endowments, economic opportunities, and voice and agency would boost the attainment of the twin goals.” Improving the quality of national and regional data is essential to pursue this goal as well.

II. PROJECT DESCRIPTION A. Project Development Objective

Project Development Objective Statement

28. Strengthen the statistical systems of participating countries and regional bodies in Africa to harmonize, produce, disseminate and enhance the use of core economic and social statistics.

10 Burkina Faso CPF – Report No. 123712 – BF; Cabo Verde CPF -Report No. 127164-CV; Côte d'Ivoire PLR – Report No. 122566-CI; Ghana draft CPF – expected to be approved in FY21; Liberia CPF - Report No. 130753-LR; Sierra Leone draft CPF – tentatively expected to be approved in FY20; and Togo CPF - Report No. 112965-TG.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

PDO Level Indicators

29. The project will use the following project development objective (PDO) indicators to monitor progress toward achieving the PDO.

30. Strengthening statistical systems. Two indicators are designed to measure the contribution of the project to strengthening the statistical systems of the participating countries: the modified statistical capacity index (SCI 2.0) and the institutional capacity index (ICI), which are composite indices. The first assesses the methodologies for data production and their quality and availability, and the second assesses institutional capacity regarding the human resources, management structure, and knowledge and learning.

a. Modified Statistical capacity index (SCI 2.0) (disaggregated by participating countries) (percentage). The SCI depends on many factors that are beyond the scope of this project, but the project refers to a modified version of the SCI that includes only the indicators related to the activities that the project finances. Although the modified version of the SCI (SCI 2.0) uses a subset of the SCI indicators, it covers the same three categories: methodology, data sources, and periodicity. Other things being equal, improvement in the SCI 2.0 should lead to improvement in the SCI that the World Bank Development Economics Vice Presidency produces. The maximum score for SCI 2.0 is 80 (Annex 7). The baseline for this indicator in the Results Framework is derived from the methodology presented in Annex 7.

b. Share of beneficiary countries (National Statistical Office) that score at least 30 out of 50 for the ICI (percentage). The ICI is designed to conduct systematic functional reviews to identify and analyze an Institution’s capacity across three areas: (i) staffing and human resources policies; (ii) management, incentive, and institutional arrangements; and (iii) knowledge and learning (competencies, learning plans, knowledge systems). Each area is composed of technical indicators that are measured systematically. The maximum score of each area is 50 and the overall ICI is the average the scores of the three areas. The ICI indicator does not apply for all beneficiary countries and not all three areas are covered by the activities of the project. The ICI does not apply to Cabo Verde as the project has no activities that will affect this index.

31. Production and dissemination of harmonized statistics. Two indicators will also be used to monitor production and dissemination activities:

a. Share of comparable core economic and social statistics indicators produced and available for open access (percentage). Statistics are comparable when produced using similar methodologies. The indicators to be considered are the following: (i) Population size by region and areas of residence; (ii) Poverty indices; (iii) Inflation rates; (iv) Production volume of main staple crops; (v) Value added of SMEs and MSMEs; (vi) Gross domestic product growth; and (vii) underemployment rate. Open access means that the information is available on the website.

b. Share of comparable core economic and social statistics datasets produced and available for open access (disaggregated by country) (percentage). Statistics are comparable when produced using similar methodologies. The list datasets include: (1) Anonymized cartography dataset; (2) Anonymized household poverty survey; (3) CPI dataset; (4) Anonymized agricultural census or annual survey dataset; (5) Anonymized updated business registry; (6) Input-output tables; and (7) Anonymized labor force surveys dataset. Open

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

access means that the information is available on the website or upon request.

c. Share of statistical products produced and published by the NSO following international standards and a predetermined release calendar (disaggregated by country) (percentage). Core economic and social statistics include, household poverty survey (poverty indices), CPI (inflation rate), annual agricultural survey (agricultural production), national accounts (GDP growth rate), and labor surveys (underemployment rate). For each statistical output of a subset of the core economic and social statistics, a methodological manual or guideline is produced or applied based on international standards, and a release calendar is set and adopted by all countries.

32. Enhance the use of statistics. National statistical agencies tend to give greater priority to the supply side of statistics than the demand side, speculating that supply creates its own demand in the sense that availability of reliable statistics reveals important matters that public debates and policies focus on. Although the supply of good- quality statistics is a major aspect of this project, the demand side of statistics will also have high priority. Two aspects of the design of the project will enhance the use of statistics.

a. Share of countries that produce and disseminate at least two analytical reports using survey, macro or administrative data (percentage). The project will support agencies involved in poverty analytical work and macroeconomic activities by publishing collaborative analyses on many themes for public scrutiny and organize workshops to stimulate debate.

b. Increase in user satisfaction index (percentage). Users access official statistics through different channels, including press releases, websites and publications. The user satisfaction index will be computed from user surveys. A baseline survey will be conducted the first year of the project and follow-up surveys in years three and five. This indicator will measure the change in percentage points from baseline.

B. Project Components

33. The project has three components: A regional component to produce harmonized tools; collect a core set of social, economic, and administrative statistics while improving their quality; and disseminate and facilitate use of data to improve the institutional environment at the management level and increase human resource capacity. A country-specific component to address shortcomings that are not necessarily common to all countries but that will enable NSSs to leverage regional activities, for instance, filling infrastructure and software needs. A project management component to oversee and supervise the first two components. The World Bank’s support is planned for five years (2020–2024). The estimated cost for the project is US$379 million, to be provided through a combination of credit and International Development Association (IDA) grants from country-specific and regional windows.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Table 1: Country and regional project cost allocation (US$ million)

Burkina Cabo Côte Sierra AU ECOWAS Ghana Liberia Togo Total Faso Verde d'Ivoire Leone Cost estimates 1. Regional Component: Harmonization, Data Collection, Quality

Improvement, Dissemination 2 6 51.5 11.5 50.8 135.91 25 24.5 27 334.21 and Use of Core Social and Economic Statistics 1.1 implementation of the SHaSA2 initiative and regional 2 6 8 harmonization 1.2 household surveys 0 0 12.5 3.65 22.85 89.34 9.5 8.5 14 160.34

1.3 economic statistics 0 0 16 3.1 17.5 24.76 7.4 9 8 85.76

1.4 consumer price index 0 0 0.8 0 0.5 1.44 0.5 1.5 0.5 5.24

1.5 administrative data 0 0 11 2.3 2.85 9.44 2 5 0.5 33.09

1.6 big data 0 0 1 0.5 1 3.73 0 0 1 7.23

1.7 data dissemination 0 0 0.5 0.25 0.5 1.5 0.5 0.5 0.5 4.25

1.8 institutional reforms and 0 0 9.7 1.7 5.6 5.7 5.1 0 2.5 30.3 enhance human capital 2. Country Specific

Components 0 0 6.5 2 1.2 11.09 3 3 1 27.79

3. Project Management and

M&E 0.5 1.5 2 1.5 2 3 2 2.5 2 17.00

Grand Total 2.5 7.5 60 15 54 150 30 30 30 379 Financing IDA Grant 2.5 7.5 30 15 30 15 100 National PBA 10 5 10 5 30 Regional 2.5 7.5 20 10 20 10 70 IDA Credit 30 15 54 150 15 15 279 National PBA 10 5 18 50 5 5 93 Regional 20 10 36 100 10 10 186 Grand Total 2.5 7.5 60 15 54 150 30 30 30 379

Component 1: Regional Component: Harmonization, Data Collection, Quality Improvement, Dissemination and Use of Core Social and Economic Statistics (US$334.21 million equivalent)

34. This component will finance activities designed to support production of harmonized methodologies; production of core economic and social statistics, including national accounts and price statistics; improvement of targeted

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

administrative statistics; training on methodological improvements and building human capacity and supplementary data collection to improve the quality and timeliness of core statistics that NSOs produce; data dissemination and use; and institutional reforms. Training will be provided at three levels: regional for strategic matters such as NSDS and organized in parallel with regional meetings, sub-regional for harmonized methodologies, and national for things such as statistics degree programs.

Subcomponent 1.1. Support implementation of the SHaSA2 initiative by the African Union, support production of harmonized methodologies by the ECOWAS Commission, and improve data access at the regional level (US$8 million equivalent)

35. The African Union introduced the overall SHaSA2 initiative to underpin a regional, harmonized approach to strengthening African NSSs and thus has the responsibility for monitoring it. This component will support the African Union in supervising activities at the sub-regional level and monitoring progress of the project. More specifically, the African Union will advocate for implementation of SHaSA2, work with the regional economic communities to have the standards adopted, organize training on new features of NSDS strategic planning in collaboration with other partners such as PARIS 21, monitor compliance of member countries, and work with development partners to mobilize financing and technical assistance. The African Union will prepare an annual report on implementation of SHaSA2 for the beneficiary countries during implementation of the project. Overall regional support, including coordination of activities in Component 3, is US$10.0 million; the African Union will receive US$2.5 million (US$2.0 million for technical activities in this subcomponent and US$0.5 million for project management and coordination at the regional level in Component 3), and ECOWAS will receive US$7.5 million (US$6.0 million for technical activities described in this subcomponent and US$1.5 million for administrative coordination of the project described in Component 3).

36. The project will produce or support adoption of a harmonized methodology (international standards) on multitopic living standards household surveys, national accounts, and some of the basic statistics used to construct them, such as the CPI. There are particular challenges to harmonizing household surveys because countries already have their practices and are often reluctant to change the design of surveys, questionnaires, and methods of calculation of poverty and other indicators. Three countries (Burkina Faso, Côte d’Ivoire, Togo) are among eight WAEMU members that have worked together to harmonize their surveys; their experience will help the other countries. The African Union can convene a forum that supports countries in discussing and exploring the feasibility of applying a common set of minimum standards that other institutions have developed or applied successfully. The project provides additional support during this transition period to study how adopting harmonized standards affects comparability. For agriculture statistics, the project will rely on the 50 by 2030 Initiative. ECOWAS can lead in convening forums and workshops to inform the countries in the project about this initiative and the materials and guidelines that have been produced and explore with them the feasibility of the adoption or adaptation of those guidelines. Liberia, Sierra Leone, and Togo must align with the 2008 SNA to produce annual economic indicators that are fully internationally comparable and to produce quarterly national accounts. Burkina Faso and Ghana have already moved to the 2008 SNA, and Côte d’Ivoire has started the process; the three countries need to plan their next rebasing exercises to be in line with international recommendations (new base year every five years). International standards will also be set for the CPI (e.g., use of international classification, extending geographic coverage, minimum requirement in term of sample markets).

37. Producing a harmonized methodology in each of the areas referred will also require conducting missions to the seven African countries involved in the project and possibly other ECOWAS member countries (a WAEMU country and a non-WAEMU country) and at least one non-ECOWAS country to assess the quality of the statistics produced,

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

including coverage, timeliness, and alignment with international standards. For each area, the report produced will be used to build a harmonized methodology or apply existing ones to each country. As mentioned before, the harmonized methodology and standards will be submitted for adoption through a workshop that all 15 ECOWAS member states and other partners attend (African Development Bank, Pan-African Institute for Statistics (STATAFRIC), WAEMU, Economic and Statistical Observatory of Sub-Saharan Africa (AFRISTAT)). The harmonized methodology and standards will be applied first to the seven countries benefiting from the project. In each thematic area, some countries are more advanced and may have already met minimum requirements. For lagging countries, the harmonized methodology and standards will become a recommendation, and these countries might require support from further projects. The ultimate objective is to support the 15 ECOWAS member states and other countries in applying the methodology and producing harmonized statistics. The ECOWAS Commission will lead the work in most instances and the African Union in others, always in close coordination with one another.

38. Another set of activities will increase ECOWAS’s capacity to archive and disseminate data; it will also leverage a regional approach to sharing the core package of data collected through a regional platform. ECOWAS has designed a database in ACCESS known as ECOBASE to collect macroeconomic and finance statistics, including national accounts, CPI, public finance, and balance of payments. The database uses harmonized classification to make data easily comparable, but it is not online, some of the classifications used are already outdated, and there is a need for capacity-building activities to produce the relevant skills to populate the database. The project will support these activities. The project will also support ECOWAS in continuing an initiative that started (STATBASE) with the Economic Commission of Africa to create a web portal providing development and policy indicators. The project will also build on experiences from other regional projects on statistics, such as WAEMU in West Africa and the Programa para el Mejoramiento de las Encuestras de Hogares y la Medicion de Condiciones de Vida in Latin America and the Caribbean, to make core data collected under the regional project accessible on a regional platform. The project will engage other regional actors that maintain regional platforms, for instance the African Information Highway, which the African Development Bank maintains to disseminate agricultural statistics, avoid duplication, and consolidate efforts.

39. This component will also support NSSs in using big data to inform public policies. With the penetration of cellphones, the internet, and other electronic devices (e.g., automated teller machines) and social media in Africa, big data will become more available at low cost. In some situations (e.g., conflict, epidemics), these data can complement traditional data and be used to inform policy faster than organizing surveys. The project will support investment in research and development of regional public goods such as new technologies and use of satellite data and innovations in the collection, management, and dissemination of data. The final objective is to produce a handbook on use of big data, build a team at the regional level, and partner with other institutions able to support NSOs in the use of big data to inform policy.

40. The component will support capacity building, including improving management skills for NSOs, strengthening skills of technical staff at NSOs, and instituting institutional reforms. The goal is to have heads of NSOs think beyond data production and about the conditions that are necessary to running efficient, productive organizations or departments. NSO directors will be trained in strategic management, including adapting to change and innovation; producing products to match demand; and managing human resources, including the profile of staff and the role of technical leadership. For technical staff, training on harmonized methodologies will be provided at the regional level at conferences and workshops. For example, before starting the rebasing exercise of their national accounts, specialists in this area can receive training on the core innovations of the 2008 SNA.11 Training will also be provided at the national level in areas where data will be collected, with the goal of immediately applying the knowledge and

11 Particularly on the change to International Standard Industrial Classification of All Economic Activities Rev. 4 and making the tax data compliant.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

skills gained during project implementation. Technical training, along with production of best practice notes, will be focused on topics relevant to implementation of project activities, such as sampling, data curation, data archiving, poverty measurement, and data analysis. Capacity building will mostly be learning by doing during the course of the project and may rely on existing regional training mechanisms, such as those under the leadership of UNECA, in close collaboration with the network of African Statistical Schools. In some instances, the project will support the efforts of NSOs, the African Union (through STATAFRIC), and ECOWAS to hire staff in areas relevant to the project. This will ensure that capacity is retained beyond the lifetime of the project. Such engagement could come in the form of drafting terms of reference (ToR) and supporting recruiting efforts. Regarding institutional reforms, the project will support evaluation of the institutional capacities and legal frameworks of beneficiary countries.

Subcomponent 1.2. Support of Household-Based Surveys at the National Level Using Harmonized Methodologies (US$160.34 million equivalent)

41. This subcomponent will support implementation of a core set of social statistics through household-based surveys. All seven countries have development strategies that outline specific, measurable goals; their monitoring and evaluation systems all require regular household surveys to provide data to track progress. This project will focus on two types of household surveys: multitopic household surveys to measure poverty and socioeconomic status and labor force surveys that explore the constraints that individuals face in entering the labor market and obtaining decent wages. All the seven countries conduct household surveys12 somewhat regularly, but good labor market systems are rare in Africa. Sierra Leone is constrained by lack of human resources, and Cabo Verde already has an annual labor force survey, so a system of labor statistics will be implemented for Burkina Faso, Côte d’Ivoire, and Ghana and at least one labor force survey for Liberia and one baseline survey to strengthen the system in Cabo Verde. Population census are also vital for planning, implementing household surveys, and monitoring development progress. Each of the seven countries is preparing a census (Sierra Leone a midterm census), and the project will partly support these activities in Burkina Faso, Côte d’Ivoire, Ghana, Liberia, Sierra Leone, and Togo.

42. This subcomponent will support implementation of one household survey in each country (US$34.05 million). The project will fund the Cabo Verde Household Income and Expenditure Survey and the Ghana Living Standard Survey in 2021, the Liberia Household Income and Expenditure Survey and Sierra Leone Integrated Household Survey in 2022, and the Enquête Harmonisée des Conditions de Vie des Ménages in Burkina Faso, Côte d’Ivoire, and Togo in 2024 (Annex 5). Togo will also conduct a survey at the commune level to monitor SDGs. An attempt will be made to design any new surveys that take place in the last year of the project using the standards that ECOWAS member states adopted under Subcomponent 1.1 (see paragraph 36). In particular, the questionnaires and survey methods will be reviewed and modified to address gender data gaps and disability in relevant areas such as employment, assets, and income. Moreover, the survey will include a section on shock and coping mechanism to deepen our understanding of households’ vulnerability to shock, particularly, climate changes and natural hazards, and to identify adaptive interventions to support households’ resilience. The inclusion of this section aligns with the Paris Accord’s goals on enhancing adaptive capacity, increasing resilience, and limiting vulnerability that five out of seven countries in the project signed in 2016 (Burkina Faso, Cabo Verde, Côte d’Ivoire, Ghana, and Liberia). The household surveys also support the planning of the Comprehensive Africa Agriculture Development Programme (CAADP) framework as well as the African Forest Landscape Restoration Initiative by providing data evidence on the interlink between agricultural production and climate shocks. Methodological changes to survey design and the transition from paper and pencil interviewing to computer-assisted personal interviewing (CAPI) will make it challenging to compare the new poverty estimates with past poverty numbers. An experiment will be necessary to adjust the former poverty

12 Cabo Verde, Liberia, Sierra Leone, and Ghana have undertaken household surveys in the last three years, and Burkina Faso, Côte d’Ivoire, and Togo in 2018/2019. 24

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

numbers for robust comparability. In Côte d’Ivoire, the household survey will have an expanded focus on migration. The sampling will also be adapted to allow deep analysis of urban poverty. (Detailed cost allocations according to country are provided in Annex 6.).

43. The subcomponent will also support Burkina Faso, Cabo Verde, Côte d’Ivoire, Ghana, Liberia, and Togo in building a system of labor statistics by financing labor force surveys (US$18.95 million). A good labor statistics system must address labor demand (data from enterprises) and labor supply (data from labor force surveys). On the demand side, enterprise surveys will be supported (Subcomponent 1.3). On the supply side, the system of labor statistics will comprise a comprehensive labor force survey and where possible light surveys conducted each year in two interviews (a face-to-face interview and a telephone interview 6 months later). The main products will be a regular labor market bulletin and data information for dynamic labor market analysis.

44. The subcomponent will also support population censuses in six of the seven countries and other sociodemographic surveys (US$107.34 million). As many countries do not have reliable nationwide vital registration system and civil registry administration, population censuses are critical for developing data-driven development strategies and monitoring progress. They provide a sampling frame for household surveys and data for poverty mapping that are useful for targeting social programs; and supply population data for many administrative and national accounts indicators. In six of the seven countries, population censuses are planned in 2020, and in Sierra Leone, a midterm census is planned for 2020. Population censuses are costly, and it usually takes many international organizations to finance them. The project will support a population census, mainly for cartography, data collection, and analytical activities (depending on the specific situation and timeline of each country) in all countries except Cabo Verde, where no IDA funding is required. The 2020 Ghana Population and Housing Census will benefit from the highest level of IDA support at the request of the Government, and much has already been invested toward that goal, including extensive support from other development partners through technical assistance.13 Censuses in Ghana and Côte d’Ivoire are expected to take place in electoral years and will aim to follow good practices to limit risks of confusion between census and political activities; the Statistical Offices are to exercise technical independence in conducting census enumerations no less than 6 months prior to elections and in delivering findings. The Housing and Population Census in Ghana is set for March 2020. In Burkina Faso, Cabo Verde, Ghana, and Togo, a DHS or MICS will also be supported as part of this subcomponent. The sequencing of these activities with the censuses is critical to ensure successful implementation of each of them.

Subcomponent 1.3. Support to the Core Set of Economic Statistics at the National Level Using Harmonized Methodologies (US$ 85.76 million equivalent)

45. The goal of this subcomponent of the project is to improve the quality of enterprise statistics and agricultural statistics to improve national accounts and allow for adoption of the SNA 2008 standard in all countries.

46. The first set of activities of this subcomponent is the design and implementation of a coherent system of enterprise statistics, including surveys and administrative data (US$51.33 million equivalent). Improving national accounts will require a comprehensive system of enterprise surveys in the formal and informal sectors and a good system of agricultural statistics. To make sure that all enterprises will be covered, the first step will be to clarify, using

13 The tablets, vehicles, and other survey-related equipment purchased for the population census in Ghana will later be used for other surveys planned over the course of the project, including the Ghana Living Standard Measurement Surveys, the labor force surveys, the enterprise census and surveys, and agricultural surveys. These will result in overall efficiency gains by reducing the overall costs of the surveys because GSS will not have to purchase tablets or equipment needed for the surveys. Other countries can also use the tablets through a south-south collaboration and can benefit from experience sharing.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

international concepts, the difference between formal and informal enterprises. A comprehensive system of enterprise surveys in the formal sector requires a complete, correct establishment register. Enterprise statistics will also serve to understand constraints on investment and labor demand. Burkina Faso and Liberia conducted enterprise and establishment censuses in 2016-17 and Cabo Verde in 2018; Ghana and Sierra Leone completed enterprise surveys in the last couple of years. Burkina Faso, Côte d’Ivoire and Togo also collect enterprise data from an administrative source, the Statistical and Tax Declarations (STD) known in French as (Déclaration Statistique et Fiscale, DSF), a financial statement that formal enterprises complete annually. The DSF system is a good source of data for enterprise statistics but has many weaknesses, including incomplete coverage, absence of labor demand variables, and an inadequate data processing system. Administrative data are also important to complete the census (because the geographic approach of a census cannot cover all activities well) and to maintain the business register.

47. The project will support implementation of a system of enterprise surveys, based on a census followed by a survey every year or two, depending on country capacity. The system will build on existing economic surveys and improve them to align them with the international standards that the ECOWAS Commission has adopted, including on the use of the most recent international classifications. Burkina Faso, Côte d’Ivoire, and Togo will conduct an enterprise survey in the modern sector every year or two that will build on the DSF in a way that, for large enterprises that completed it, the information available on the DSF is downloaded before enumerators go into the field. For enterprises (small enterprises) that do not complete the DSF, the whole questionnaire is administered in the field. The informal sector requires a different approach, which can be undertaken by coupling an informal sector survey with a labor force survey or conducting a standalone informal sector survey periodically.14 In all cases, the informal sector will be covered every three or four years. The project will also support the three French-speaking countries and their general directorates of taxation to advance the use of online instruments including the development of electronic platforms to allow enterprises to complete their DSF application online. Technical assistance that the World Bank Development Economics Vice Presidency secures through a trust fund for statistical capacity building window (economic surveys and firm-level data) will complement these activities in Côte d’Ivoire, Ghana, Sierra Leone, and Liberia.

48. The second set of activities is the design and implementation of a comprehensive system of agricultural statistics (US$22.09 million equivalent). The project will support collection of comprehensive agricultural data, including censuses and surveys, depending on the situation and demand in each country. The same approach used for enterprise statistics will be developed (a census followed by an annual survey) and, in parallel, reinforce the system of administrative agricultural data. For surveys, the project will explore the potential for relying on the 50 by 2030 Initiative coordinated by the World Bank (Development Economics Data Group), FAO, and International Fund for Agricultural Development developed, which includes the farm-based AGRISurvey, to close the agricultural data gap in low- and low-middle-income countries. Ghana, chosen to pilot the AGRISurvey methodology in 2017-18, will conduct a survey every year. Burkina Faso and Liberia will conduct an agricultural census. In Liberia, a survey will be conducted two years after the census. Sierra Leone will integrate a complete enumeration of agricultural households and businesses into the midterm census and enterprise census and will incorporate a revised agricultural model into the Integrated Household Survey, followed by two annual agricultural surveys. Burkina Faso and Togo have well- established annual agricultural surveys; the project will improve them in line with the AGRISurvey approach (more details provided in Annex 5). The Cabo Verde survey will focus on agriculture and fisheries. It is expected that these data production activities can be complemented with technical assistance supported through trust fund resources from the 50 by 2030 Initiative. The agricultural statistics, such as land quality and land usage, agricultural inputs (fertilizers and equipment), and crops harvest will provide useful insight about farmers’ adaptability to climate

14 The technical approach in French-speaking countries, coupling the informal sector survey with the labor force survey, will be maintained. The costs of the labor force survey include the informal sector surveys.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

changes and serve as inputs to the West African Initiative for Climate Smart Agriculture (WAICSA) which support smallholder farming households to not only improve food security but also mitigate CO2 emissions.

49. The third set of activities is modernization of national accounts in coordination with the International Monetary Fund (IMF), AFRISTAT, and WAEMU (US$12.34 million equivalent). The project will support Cabo Verde, Côte d’Ivoire, Liberia, Sierra Leone, and Togo in moving to the 2008 SNA with a more recent base year. For Burkina Faso and Ghana, the project will support the next rebasing exercise. (National accounts need to be rebased every five years to take into account changes in the structure of the economy.) This exercise will use the methodology that ECOWAS has adopted. Appropriate software for compiling national accounts will be provided. In Cabo Verde, the project will support the change of the base year and construction of satellite accounts in different areas (e.g., tourism, agriculture, culture). The funds will be used to collect some additional administrative data and, in the case of Cabo Verde, Ghana, and Togo, construct different indices, including the Industrial Producer Price Index, Industrial Production Index, and Turnover Index.

Subcomponent 1.4. Support the Modernization of the CPI at the National Level Using Harmonized Methodologies (US$5.24 million equivalent)

50. The goal of this subcomponent of the project is to improve the quality and timeliness of the CPI in coordination with IMF, WAEMU, and AFRISTAT. Burkina Faso, Côte d’Ivoire, and Togo are involved in a regional initiative under the supervision of the WAEMU Commission and have a harmonized consumption price index, but coverage is limited to urban areas, particularly the biggest cities. In Ghana, Liberia and Sierra Leone, the CPI will be updated following the model that the WAEMU Commission uses. Improving the CPI entails adopting a common methodology based on international standards that ECOWAS developed under Subcomponent 1.1; adopting a more recent base year, for Sierra Leone; extending geographic coverage for Liberia,15 Sierra Leone, Burkina Faso, Côte d’Ivoire, and Togo;16 and financing price data collection, including implementation through CAPI. The methodology must be adapted to the context of each country, price data must be collected and processed. ECOWAS will explore appropriate software to be used, by engaging international price experts and price experts from NSOs in the region. The expected outcome is an integrated national CPI series to be produced monthly and made available on NSO websites.

Subcomponent 1.5. Support the Improvement of Administrative Data Sources (US$33.09 million equivalent)

51. The project will support a variety of improvements in data from administrative sources, depending on initial conditions and capacities in each country. Three types of activities will be conducted: introduction of international standards; building a system of administrative statistics, especially for education and health; and extending administrative statistics to other priority sectors of the economy in the country.

52. The project will support use of international standards and training on processing administrative data. In some countries, the quality of statistics from administrative sources is poor, for many reasons: international standards are not used; the tools used for data capture are not adapted for statistical purposes; paper rather than electronic devices is used to collect data; and data processing, analysis, and archiving skills are weak in line ministries. The project will support these activities in the seven countries. In Cabo Verde, various tools for improving the quality of administrative data have been tested and can be shared with others. The project will also support dissemination of statistics from administrative data sources, particularly the General Data Dissemination System of the IMF, and expanded relationships with users, universities and research institutions, media, nongovernmental organizations, international

15 The initial step will be to improve collection of data on prices in Monrovia and then in other regional markets. 16 In Burkina Faso, Côte d’Ivoire, and Togo, coverage extension will involve the smallest cities (semi-urban).

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

organizations (as users), and the public to better integrate them with NSSs to promote a culture of data-sharing in NSSs.

53. The project will improve administrative data for health and education. Support on health and education statistics through the project is based on country-specific demands. For example, the project is supporting Sierra Leone on health statistics at the request of Statistics Sierra Leone. The project will support Burkina Faso, Liberia, and Ghana in gathering data on education. In Burkina Faso, the project will help modernize data collection and data entry processes at the Ministry of Education by equipping the 488 basic education constituencies, provinces, and regions with computers, data entry software, and internet access; providing primary schools and possibly secondary schools with tablets or smartphones; and internet access for the General Directorate of Sectoral Studies and Statistics (Direction Générale des Etudes et des Statistiques Sectorielles (DGESS)) of the Ministry of Education at the central level. In Burkina Faso and Ghana, the project will provide support for the ministry to conduct school censuses and reporting, and in Liberia, the project will provide capacity-building activities, including training on how to improve the quality of administrative data at the Ministry of Education. In the health sector, Ghana and Sierra Leone will be targeted. In Sierra Leone, three research sites will be established as part of a Comprehensive Health and Epidemiological Surveillance System. Researchers will comprehensively track all individuals at these sites to capture data on population demographic characteristics, nutritional status of children and women, causes of mortality, prevalent morbidity, and health system use and barriers to use and monitor new health threats. Establishment of such sites will complement the activities of the Regional Disease Surveillance Systems Enhancement (REDISSE; a regional program focusing on human and animal health surveillance). Although not nationally representative, the data produced from intensive community studies of the Comprehensive Health and Epidemiological Surveillance System can deepen understanding of health and population dynamic, and thus inform development of components for the REDISSE system, as well as for household surveys such as MICS and DHS. In Burkina Faso, the government has started to modernize data collection with a pilot project in two of the country’s 70 health districts. Modernization involves replacing paper with tablets for data collection, providing equipment such as computers and software, and providing training activities. The subcomponent will support extension of this modernization.

54. The project will support administrative statistics in other sectors than education and health, particularly in Burkina Faso, Côte d’Ivoire, Cabo Verde, Ghana, Liberia, and Sierra Leone. In Ghana, the project will prioritize administrative data collection, compilation, and reporting, focusing on twelve selected implementing ministries, departments, and agencies (MDAs), and provide technical training support to the other seven, particularly those producing administrative data relevant for the national accounts.17 The focus of this subcomponent in Liberia includes production of consistent administrative data by ministries, agencies, and commissions (MACs) and collaboration with MACs on a strategy for use of administrative reports and records as part of production of statistics for Liberia (e.g., Liberia Revenue Authority records, Liberia Business Registry). The livestock sector is crucial to the livelihood of the Burkinabe population, but statistics are weak. Another goal of this subcomponent is to build a subsystem of livestock statistics to address these problems by providing technical assistance to help the DGESS of the Ministry of Livestock

17 There are two groups of MDAs that will be supported under the project, one group that receives financial and technical support and a second group that receives technical assistance only, mainly from GSS. The fact that some of the MDAs can raise enough resources to perform their work but require technical support and improvement in coordination with the NSS informed these two groupings. The project will support all of the MDAs in Ghana as described in the NSDS II Strategy. MDAs that are to receive financial and technical support include the Ministry of Education; Ministry of Employment and Labour Relations; Ministry of Gender, Children, and Social Protection; Birth and Death Registry; Registrar-General Department; Ghana Police Service; Ghana Prison Service; Ghana Immigration Service; Ministry of Tourism, Culture, and Creative Arts; Ministry of Health; Ministry of Food and Agriculture; and Ghana Health Service. Those that are to receive technical support include the Ministry of Sanitation and Water Resources, Ministry of Works and Housing, Ministry of Lands and Natural Resources, National Communication Authority, National Road Safety Commission, Environmental Protection Agency, and Ministry of Trade. 28

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

to develop a methodology and design technical tools (e.g., questionnaire, sample) to collect livestock statistics and equipping DGESS with computers, data entry software, internet access, and tablets to support data collection, processing, and dissemination. The Ministry of Agriculture conducts an annual survey and has started to move from paper to electronic data collection. Ten of the 13 regions of the country use tablets for data collection; the project will help finalize this transition by providing tablets to the three remaining regions. In Côte d’Ivoire and Cabo Verde, the project will introduce quality control procedures for administrative data systems to monitor indicators that reflect national development priorities. Quality control mechanisms for administrative data are weak, making it difficult to integrate their statistics into the national framework. Various tools for improving the quality of indicators and administrative data have been tested and adopted under the World Bank–United Nations Development Program assistance program to strengthen Cabo Verde’s national monitoring system. The project will support further development and introduction of these tools.

Subcomponent 1.6. Enhancing the Use of Big Data (US$7.23 million equivalent)

55. Disruptive technologies in data collection and fieldwork monitoring are rapidly becoming more available and cost-effective. The project will work in three areas. First, in all countries except Liberia and Sierra Leone who did not request for this type of support, the project will support the collection of weather data (e.g., rainfall, temperature) at the community level. These data will be combined with household survey data to improve poverty analytical work, for example deepening understanding of vulnerability, shocks, and the interlink between agricultural production and climate. As climate change is expected to increase variability and incidence of extreme weather events (floods, droughts, etc.), it is particularly important to collect data to monitor the level and the changes of rainfall and temperature in the region. In addition, it will shed light on the correlation between such changes in climate and changes in households’ agricultural production, from inputs used (land, fertilizers, etc.) to crop harvest, thereby informing countries about possible approaches to supporting agricultural production in the face of increasing climate change. Second, the project will experiment with the use of high-resolution day-time satellite data and machine- learning approaches in tracking poverty between two household surveys and possibly at an administrative level lower than regional (the level at which results are usually available on household surveys). This experiment will be conducted in Burkina Faso, Côte d’Ivoire, Ghana, and Togo. Third, the Ghana Statistical Service (GSS) has signed an agreement with the mobile phone companies to gain access to and use call record data to supplement official statistics. These data can also be combined with household surveys or other administrative data for analytical work. The project will also support other sources of data, including geospatial data.

Subcomponent 1.7. Enhanced Data Accessibility and Dissemination (US$4.25 million equivalent)

56. This subcomponent will support data accessibility and dissemination through a variety of mechanisms, including redesigning NSO websites, creating national databases, and developing applications that enable the general public to download statistics in user-friendly formats in all countries. This component will make dissemination of statistics faster, equally accessible to all users, and compatible with user needs. It will address existing constraints in the IT infrastructure, including introduction of innovative tools to widen the reach and effect of NSO products. Three distinct groups of users will be targeted: the general public; officials in the various MDAs of the governments of countries and important donor partners; and researchers, academia, and students. To meet the demand for data from these groups, the project will support NSOs in building different types of products, including indicators and reports and their comprehensive metadata; sharing data widely on external data dissemination platforms, such as the World Bank Microdata Catalogue, UNData, and the Integrated Public Use Microdata Series; building an online interface to allow users to calculate their own summary statistics; and making available online anonymized microdata sets. A revised, consistent policy will be put in place regarding sharing and disseminating

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

microdata sets. The human resources needed to support such users of NSO data will also be considered. This subcomponent will also support countries in establishing a calendar for publishing their statistics.

Subcomponent 1.8. Support Institutional Reforms and Enhance Human Capital (US$30.3 million equivalent)

57. The institutional environment of NSSs largely determines their effectiveness. This environment, which is framed in the statistical law, determines the relationship of each NSO with the political authority, its financial autonomy, its autonomy in management of human resources, and its relationships with data users, particularly the sharing of data. In some countries (e.g., Burkina Faso18 and Togo), the statistical law would benefit from being updated to take into account recent features, including the ratification in 2013 of the African Charter on Statistics, the recurrent demand of researchers for access to anonymized individual data, and the rapid development of information and communication technologies that allows rapid processing of big data. In some countries (e.g., Côte d’Ivoire), the status of the National Institute of Statistics (Institut National de la Statistique (INS)) requires it to generate its own resources to finance statistical production; as a result, it does not have adequate resources to fulfill its mission. Moreover, while Western African statistical schools train excellent graduates, many NSS cannot compete with career opportunities offered by other organizations and suffer from insufficient human resources in terms of quantity and skills. This component will support institutional reforms in Burkina Faso, Côte d’Ivoire, and Togo. This work complements the work to be done at the regional level by ECOWAS (evaluating the institutional environment of the other countries). The subcomponent will also enhance human capital resources through formal academic programs and on-the-job training on statistics and advanced analytics.

58. As for the institutional reforms, the following activities will be implemented in Burkina Faso, Côte D’Ivoire, Liberia and Togo (US$3.8 million). In Burkina Faso: finalization and adoption of the new statistical law to take into account changes in the NSS; establishment of a mechanism for financing statistics through the Statistical Development Fund (define the status of the fund, the funding model, and mode of operation); revision of the statute of the National Institute of Statistics and Demography (Institut National de la Statistique et de la Démographie (INSD)) to enable better pay conditions, better management of the professional statisticians of the NSS, and better financial management (FM) procedures; review and design of a new organizational chart of INSD; evaluation of the 2016-2020 NSDS; and design of the 2021-2025 NSDS. In Côte d’Ivoire: adoption of the National Statistical Strategy 2017-2021 and the decrees associated with operationalization of the 2013 Statistics Act (CNStat; institutional relations between INS and sector statistics departments; data dissemination), creation of a statistics fund, and agreeing on provision of adequate public resources for official statistics (possibly in combination with a performance contract) and donor coordination. Other institutional reform activities designed to improve the performance of the statistics office include setting up an annual performance contract between the statistics office and the Ministry of Planning, hiring a director general of the statistics office through a competitive process by the National Council of Statistics, and hiring young statisticians as consultants to support the INS in increasing the number of technical staff in the statistics office. In Togo: review of the 2011 Statistics Act and its alignment with current needs; design of a five-year strategic business plan for the National Institute for Statistics, Economic and Demographic Studies (Institut National de la Statistique et des Etudes Economiques et Démographiques (INSEED)) focused on sustainable financing and results; implementation of a performance-based approach between INSEED and the Ministry of Development, Planning and Cooperation: assessment of human resources policies and design and implementation of new policies covering the entire employment lifecycle in line with INSEED’s strategic objectives; and review of organizational charts (job descriptions and related competency-based, performance-based career framework). In Liberia: review of the progress in implementation of NSDS and preparation of annual plans for LISGIS. The cost is US$0.7 million for Burkina Faso, US$2 million for Côte d’Ivoire each, US$1 million for Togo, and US$0.1 million for Liberia.

18 In Burkina Faso, the law is under revision.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

59. Enhancement of human capital resources through formal academic programs (US$10 million). This subcomponent will increase the skills of staff by creating associate’s, bachelor’s, or master’s degrees or continuing education programs in statistics in Burkina Faso, Côte d’Ivoire, Liberia, and Togo. In Burkina Faso, the subcomponent will support creation of a bachelor’s or master’s degree program and a continuing education program (e.g., curriculum, teaching materials, computer, software, internet connection) in statistics with the support of the Ecole Nationale Supérieure de Statistique et d’Economie Appliquée (National School of Applied Economics and Statistics) of Abidjan or Dakar. In Côte d’Ivoire, the subcomponent will support scholarship to train students at the associate degree program for the NSS. In Liberia, the project will support the University of Liberia in establishing an undergraduate training program and certificate courses in statistics. In addition, the Liberia Institute of Statistics and Geo-Information Sciences (LISGIS) will collaborate with regional statistics schools (e.g., ENSEA of Abidjan, the new African Union statistics school in Tunisia) to provide training. Staff who have the necessary background and a high school certificate can undergo two years of training, receive an associate’s degree in statistics, and be qualified for a job in any public agency. ENSEA has been designated a center of excellence and has experience supporting this type of training in countries such as Niger. In Togo, the main activity will be creation of an associate’s degree program (e.g., curriculum, teaching materials, computer, software, internet connection) in statistics with the support of ENSEA of Abidjan or Dakar (building on a training program developed with the support of the European Union). The cost of these activities is US$5 million for Burkina Faso, US$0.6 million for Côte d’Ivoire, US$3.4 million for Liberia, and US$1 million for Togo.

60. Building capacity through on-the-job training and workshops in data production (US$8.2 million). Weak human resources limit the ability not only of NSOs to produce good-quality statistics, but also of researchers to generate relevant analyses that meet policy makers’ needs. The goal of this subcomponent is to support capacity building in statistics and analytics in NSOs and line ministries in Burkina Faso, Côte d’Ivoire, Ghana and Liberia. In Burkina Faso and Côte d’Ivoire, training will be provided on basic techniques of data collection and data analysis using modern technologies such as tablets for non-statisticians of line ministries, and data management designed for data processing specialists of the line ministries. In Ghana, the project will provide capacity-building training to facilitate data production, management, dissemination, and use, including strengthening the skills of staff at GSS and statistical units at MDAs and the metropolitan, municipal, and district assemblies. Data analysis training will focus on standardized statistical software such as SPSS and STATA; geographic information systems and high-resolution imagery; and depending on need, emerging topics such as use of big data. To meet the needs of staff, the training program will be built upon a thorough assessment of the statistical units of MDAs. Staff skills in office collaborating tools such as email and Microsoft Lync would also be enhanced to facilitate communication among staff. Succession planning has been identified as a critical factor in successful knowledge and leadership transfer. In Liberia, the project will support short-term, on-the-job training for LISGIS staff. After a need assessment, short-term training modules will be prepared to meet specific needs of LISGIS. The cost of this activity will be US$2 million for Burkina Faso, US$0.5 million for Côte d’Ivoire, US$4.7 million for Ghana, and US$1 million for Liberia.

61. Building capacity through on-the-job training and workshops in the use of data and analytics (US$8.3 million). When data are not used, demand for data is low, and governments are not encouraged to finance statistics. The subcomponent will increase the capacity of ministries of finance to conduct macroeconomic analysis to increase the reliability of budget planning. It will also inform policies by providing simulations of the effects of proposed policies on public revenue, poverty, and inequality and will support microeconomic analyses. In Burkina Faso and Côte d’Ivoire, the activities envisaged under this subcomponent include training and technical assistance to the ministries of economics and finance and the ministries of planning on systems for macroeconomic modelling and fiscal

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

simulation (e.g., introduction of customized BOOST modules19 for forecasting (baseline and various scenarios)), technical assistance to support elaboration of two sectoral midterm expenditure frameworks (health and agriculture) and preparation of annual sectoral budgets, construction of a social accounting matrix, and microeconomic analytical work using existing data (annual agricultural survey, employment and informal sector surveys, population censuses, household surveys) and distributional analysis of public policies for statisticians and economists. INSD and INS will collaborate with the economics departments and statistics departments of line ministries and universities to undertake any analytical work relevant for public policies. In Cabo Verde, the project will build the basic econometric skills of researchers and NSO and NSS staff for innovative policy analysis, as well as data interpretation. The goal is to better use survey and other D4P-making purposes, building on the release of anonymized micro-data through the NSO website. In Togo, the project will support increasing the capacity of the Ministry of Planning in macroeconomic forecasting and implementation of program budgeting (required under WAEMU guidelines) in the ministries of finance and planning. In Ghana and Liberia, analytical work will also be conducted. The total cost is US$2 million for Burkina Faso, US$1.7 million for Cabo Verde, US$2.5 million for Côte d’Ivoire, US$1 million for Ghana, US$0.6 million for Liberia, and US$0.5 million for Togo.

Component 2: Country-Specific Component: Improving or modernizing physical and statistical infrastructure (US$27.79 million equivalent)

62. This component identifies activities specific to the seven participating countries. Although this will be a regional project, each country engagement will have a task team leader, in addition to the regional-level co-task team leaders, who will work closely together during implementation. The activities in this component have been designed considering the constraints and needs facing each NSO and what interventions (physical, technological, and statistical infrastructure; human capacity; legal or regulatory frameworks) will be necessary for the NSO to successfully complete the program of activities outlined in Component 1.

Subcomponent 2.1. Burkina Faso: Modernize Technological and Statistical Infrastructure (US$6.5 million)

63. This subcomponent will support modernization of technological and statistical infrastructure in INSD at headquarters and its decentralized directorates, as well as the DGESSes of two line-ministries.

64. Modernization of physical, technological, and statistical infrastructure in INSD, including its regional directorates (US$6.5 million). This subcomponent aims to address the deficient technological infrastructure (e.g., internet connectivity, computers, statistical software and packages, data archiving, generators) at INSD and its regional directorates. INSD headquarters needs equipment such as powerful database software and servers to manage and archive multiple databases. In addition, because INSD plans to expand its headquarters, more modern equipment will be needed. The regional INSD directorates are responsible for collecting administrative data at the regional level, but they lack basic equipment and internet access. The subcomponent will finance modernization of equipment (e.g., computers, servers, internet connectivity, statistical software) in the existing headquarters, in the new headquarters, and in the regional directorates. Tablets will also be acquired for regional directorates for collection of routine data. For INSD, the project will also support acquisition of vehicles for data collection activities to replace old vehicles.

19 The BOOST initiative is based on a data platform that is designed to facilitate access to budget data and promote effective use of data for better decision-making processes and greater transparency and accountability.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Subcomponent 2.2: Cabo Verde: Improving Information and Communications Technology (ICT) Infrastructure (US$2 million equivalent)

65. The goal of this subcomponent is to upgrade ICT infrastructure for data exchange platforms and data access.

66. Building the ICT infrastructure and expansion of a new electronic data platform for budget and results information with a focus on administrative data. The platform is being developed under the existing technical assistance program (which ends in June 2020) to promote interoperability of data systems linking budget, result indicators, and administrative data. Data will be stored and shared with the NSO through webservices and undergo quality control procedures before the NSO releases them as official statistics. The project will support introduction of these data platforms at the national and local level. Implementation will include acquisition of equipment, including infrastructure (e.g., server, laptops), software licenses and programming data platforms, and capacity building and functioning of the NSS network.

Subcomponent 2.3. Côte d’Ivoire : Modernize Technological Infrastructure (US$1.2 million equivalent)

67. The goal of this subcomponent is to support institutional reforms and core statistics through physical infrastructure and equipment.

68. IT infrastructure and equipment (US$1.2 million). INS's material resources are insufficient. The project will provide IT equipment (computers and servers), software, and internet access to establish an enabling work environment and to allow innovations such as data storage in the cloud.

Subcomponent 2.4: Ghana: Modernize Physical and Statistical Infrastructure (US$11.09 million equivalent).

69. Under this subcomponent, the project will modernize physical and statistical infrastructure and strengthen statistical coordination and quality assurance.

70. Support modernization of physical and statistical infrastructure (US$9.09 million equivalent): The goal of the physical infrastructure subcomponent is to provide modest furnishings and refurbishment of GSS offices and implementing MDA statistical units. It will support provision of ICT infrastructure (e.g., tablets, computers, scanners, photocopiers) and reliable internet connectivity to facilitate interoperability of NSS databases and electronic data transfer between different levels and parts of the government. It will include building an indicator tracking platform to serve as a repository for SDG indicators and other country-specific indicators. It will also help provide vehicles for data collection activities. Appropriate statistical software such as SPSS and STATA will also be procured and training provided to the staff of GSS and MDA statistics units to increase their analytical capacity to produce varied statistics to satisfy increasing demand for data for research, decision making, and monitoring and evaluation of development programs.

71. Strengthen statistical coordination and quality assurance (US$2 million equivalent): Although there is a framework in NSDS II that establishes mechanisms for effective coordination, management, and quality assurance of data production, with GSS as the focal point, the framework has not been implemented. The proposed operation will support a set of activities that will strengthen GSS's ability to play its coordination role effectively, as well as its ability to provide quality assurance and professional service functions to MDAs to harmonize statistical programs, processes, and systems according to national and international guidelines. Sensitization campaigns and workshops will be organized to increase effective generation, coordination, and management of statistics at MDAs. In particular, the

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

project will support development and implementation of a country-specific quality assessment framework for statistical products, reestablish the National Committee of Producers and Users of Statistics and its technical subcommittees, strengthen the NSS’s ability to oversee all statistical activities in the country, strengthen and maintain the GSS Resource and Data Centre, enhance use in MDAs of the geographic information system housed at GSS, strengthen the management information system of NSS by building a cloud- or web based solution for NSS, familiarize noninstitutional data suppliers with the importance of their role in producing quality statistics, and enhance monitoring and evaluation of NSS statistical activities. The project will also support coordination with NSS, including support to MDAs and metropolitan, municipal, and district assemblies.

Subcomponent 2.5: Liberia: Improving Physical and Statistical infrastructure (US$3.0 million equivalent)

72. The goal of this subcomponent is to improve the physical and statistical infrastructure within LISGIS and across the regional county offices. The project will improve the deficient technological infrastructure at LISGIS (e.g., computers, statistical software, internet connectivity, storage and archiving data system) and address the weak logistical arrangements. It will also provide office furnishings and minor refurbishment of the office space, particularly given that there is planned relocation of LISGIS to another office building by early 2020, and improve physical and statistical infrastructure at the regional county offices (This does not include major construction or physical renovation of office buildings.)

Subcomponent 2.6: Sierra Leone: Rehabilitation of Statistics Sierra Leone’s Physical Infrastructure (US$3 million equivalent)

73. Improve physical and statistical infrastructure (US$2 million). The Statistics Sierra Leone office was damaged during the war and never fully repaired; additional damage to the facility was sustained from flooding in August 2017. The new administration has addressed some of the most pressing infrastructure needs, but decades of insufficient maintenance due to funding constraints means that the building is in need of comprehensive rehabilitation. The project will support comprehensive renovation of the facilities, including replacing all the electrical wiring and providing systems for a smooth transition from the main power supply to back-up generators and installing a modern local area network. Combined with better internet connectivity, this will support more efficient management of data internally and better public dissemination of data. Essential repairs to the roof and windows will also be made to provide a comfortable work environment and ensure safe storage of IT equipment and statistical records. The project will also support expansion of the facilities within the existing footprint, in particular to provide space for planned internal and regional training and workshops. A dedicated classroom space will be constructed and equipped for ongoing training. The project will provide well-equipped conference facilities to host international workshops and conferences, especially for NSOs in the Mano River Union states of West Africa for which Statistics Sierra Leone will coordinate capacity-building activities. All physical projects will incorporate disability designs and accessible features.

74. The proposed rehabilitation and expansion of Stats Sierra Leone Headquarters will be done to ensure climate resilience so that it has the capacity for a socio-ecological system that will absorb stresses and maintain function in the face of external stresses imposed upon it by climate change and adapt, reorganize, and evolve into more desirable configurations that improve the sustainability of the system, leaving it better prepared for future climate change impacts. The everyday effects of climate change, such as rising temperatures, longer heat waves, and increased flooding, will have direct impacts on the building and staff. The rehabilitation will therefore ensure the refurbished building will be made more resilient to extreme weather and better prepared for the consequences of climate change.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

75. The project will improve the deficient technological infrastructure (US$1 million). The project will also equip Statistics Sierra Leone with computers, statistical software, internet connectivity, and a data storage and archiving system to address the weak logistical arrangements.

Subcomponent 2.7. Togo: Building Capacity and Modernizing Technological, Statistical, and Physical Infrastructure (US$1 million equivalent)

76. The goal of this subcomponent is to improve the performance of the NSS by providing physical infrastructure and equipment and strengthening the demand side of statistics.

77. Activity 1: Physical infrastructure and equipment (US$0.75 million). The project will support acquisition of office equipment, upgrading of the digital infrastructure (e.g., computers, servers, software, internet access), and design of an archiving system to increase the visibility of the statistics office. These activities will benefit INSEED headquarters in Lomé and offices in the regions.

78. Activity 2: Demand side strengthening (US$0.25 million). Samples for phone interviews will be set up under the data production component, which INSEED, civil society, or the media can use to conduct opinion polls. These types of polls will provide feedback to the government, provide interesting and engaging statistics to the public, and expose media houses to the use of data in their reporting. All of these initiatives will increase interest in and use of statistics and data by the public, the media, and civil society.

Component 3: Project Management and Monitoring and Evaluation (M&E) (US$17 million equivalent equivalent)

79. The goal of this component is to strengthen and develop NSOs’ institutional capacity in project management, coordination, and monitoring and evaluation, including preparation of project documentation (US$15 million). NSOs will be the main implementing agencies of the project in each country and will be responsible for its technical management and coordination. The project management team in each country will coordinate project activities, manage reporting and auditing activities, and ensure compliance with fiduciary policies and procedures. This component would cover the cost of staff related to the project and costs related to project coordination (steering committee), operating costs, and other expenses needed to make the project successful. Outputs of this component include the operations manual, annual work plans, bi-annual updates on the results framework, audits, procurement plans, and interim financial reports (IFRs).

80. The statistics unit at ECOWAS will be involved in sub-regional coordination (US$1.5 million), and the African Union will be involved at the regional level (US$0.5 million). ECOWAS will support institutional strengthening activities of NSOs, including preparation of baseline assessments of the capacity of each NSO at the start of the project; building strategic knowledge partnerships with regional statistical schools that cover ECOWAS countries, such as those in Côte d’Ivoire, Senegal, Benin, and Cameroon, but also extend those partnerships to other regional schools such as those in Rwanda and Tanzania; and providing technical inputs to capacity-building and other activities under country-specific subprojects. The Project Management Team at the African Union Commission (AUC) will coordinate project activities in relation to implementation of SHaSA2 at the regional level, manage reporting and auditing activities for project resources allocated to the African Union, and ensure compliance with fiduciary policies and procedures. The outputs will be annual work plans, bi-annual updates on project results, audits, procurement plans, and IFRs.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

81. The goal of this component is to strengthen overall management and leadership skills at NSOs. A technical committee composed of members of the NSOs of each of the seven countries and the coordinating unit at ECOWAS will be formed three months after project effectiveness. Coordinators for each of the NSOs will also be part of the committee, which will meet at least twice a year at the ECOWAS Commission or on a rotating basis in each country.

Retroactive Financing

82. Burkina Faso: All eligible expenditures incurred on or after February 1, 2020 until the date of the signing of the financing agreement, and up to an aggregate amount of Euro 1 million, would be eligible for retroactive financing. This retroactive financing is intended to finance hiring an international or national consultant to prepare the manual of operations, organizing a workshop to review and finalize the manual of operations, costs of hiring project implementation unit (PIU) staff, implementing activities related to processing the data from the population census, and activities related to the preparation of the DHS.

83. Côte d’Ivoire: All eligible expenditures that would be incurred on or after January 1, 2020 up to the date of the signing of the financing agreement, and up to an aggregate amount not to exceed Euro 9.8 million would be eligible for retroactive financing. This retroactive financing is intended to finance the following activities: inter alia, (a) analysis of cartography results; (b) recruitment and training of census field staff; (c) servicing of national, regional and district PHC committees; (d) procurement of logistics, IT solutions and software; (e) implementing publicity activities; (f) hiring international, national, regional and district consultants and census staff; (g) transportation, storage and communication; and (h) data quality monitoring.

84. Ghana: All eligible expenditures incurred on or after January 1, 2020, until the date of the signing of the financing agreement and up to an aggregate amount of SDR 32.7 million will be eligible for retroactive financing. This retroactive financing is intended to finance recruitment and training of census field staff; servicing of national, regional, and district PHC committees; procurement of logistics, IT solutions, and software; conducting publicity activities; hiring international, national, regional, and district consultants and census staff; transportation, storage, and communication; and data quality monitoring.

85. Sierra Leone: All eligible expenditures incurred on or after February 1, 2020, until the date of the signing of the financing agreement, and up to an aggregate amount of US$1,545,000 will be eligible for retroactive financing. This retroactive financing is intended to finance cartography; servicing of Census Secretariat; procurement of logistics, IT solutions and software; implementing publicity activities; and hiring international, national, regional and district consultants and census staff.

86. ECOWAS: All eligible expenditures incurred on or after February 1, 2020, until the date of the signing of the financing agreement, and up to an aggregate amount of US$500,000 will be eligible for retroactive financing. This retroactive financing is intended to finance recruitment of additional PIU staff members, and to complete the project operations manual.

Project Preparation Advance

87. Project Preparation Advance: Project Preparation Advance (PPA) provided to Côte d’Ivoire (US$6 million), Ghana (US$6 million), Liberia (US$1.2 million) and Togo (US$0.57 million) for project preparatory activities.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

88. Côte d’Ivoire: The World Bank has provided US$6 million to the Government of Côte d’Ivoire to finance the following activities: (a) Population census: Analysis of the cartography data and preparation of the enumeration; (b) Household surveys: Preparatory activities for the household survey; (c) Economic statistics: Preparatory activities for the enterprise census and surveys, and the informal trade survey; (d) Big data and implementation of a poverty monitoring system and other social indicators; (e) Macroeconomic modeling and forecasting; and (f) Project implementation and monitoring and evaluation; (g) Preparation of administrative and financial procedures manuals and recruitment of staff for the PIU.

89. Ghana: PPA from the Project Preparation Facility (PPF) in an amount of US$6 million to the Republic of Ghana has been approved to finance project preparation activities including; (a) training of enumerators and supervisors; data collection monitors and equipment; stationary for enumerators, field logistics, and ICT supplies.

90. Liberia: PPA from the Project Preparation Facility (PPF) in an amount of US$1.2 million to the Republic of Liberia has been approved to finance project preparation activities including; (a) technical assistance to carry out pre-census activities and national population census mapping to include: (i) enumeration; (ii) cartography; (iii) GIS mapping; and (iv) review of statistics degree, certificate and diploma programs for the University of Liberia; (b) Technical assistance to review administrative data across the Recipient's ministries, agencies, commissions and LISGIS regional officers; (c) Carrying out of Training to strengthen and develop institutional capacity of NSOs in Project management, coordination, monitoring and evaluation (M&E) and Project document preparation; and (d) Operationalization of the proposed PIU, including the acquisition of office equipment and hiring of key staff.

91. Togo: from the Project Preparation Facility (PPF) in an amount of US$0.36 million to the Republic of Togo has been approved to finance project preparation activities including: (a) rebasing of national accounts (data processing of the enterprise census and the informal cross border trade survey); (b) elaborate an institutional diagnostic of the NSS; (c) Prepare the manual of procedures of the project.

C. Project Beneficiaries

92. The direct beneficiaries of the proposed project will be partner NSOs of the respective countries, research or statistics units at MDAs and MACs, and statistical units at the African Union and ECOWAS commissions. Other ECOWAS member countries will benefit from regional trainings and adoption of agreed-upon harmonized methodologies across member states.

93. Beyond the direct beneficiaries, there will be positive externalities because the project will enhance the existing community of practice on statistics anchored on SHaSA2 (which includes NSOs and regional and continental bodies) by providing public goods such as microdata, data platforms, and statistics bulletins, which will benefit a larger audience, including universities, researchers, students, and the general public. By generating data harmonization tools, guidelines, and platforms, project support will go well beyond the seven participating countries to other countries in the region.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

D. Results Chain

94. Figure 1 illustrates how planned project activities will lead to better outcomes for regional, sub-regional, and NSSs. It shows linkages between critical project activities, outputs, outcomes, and the PDOs. Figure 1: Theory of Change

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

E. Rationale for World Bank Involvement and Role of Partners

95. The World Bank promotes good quality statistics as a critical input for evidence-based policy making. The project combines several elements of the World Bank's strategy to strengthen such an outcome: capacity building and institutional reforms to achieve sustainability; promotion of the use of statistics in policy design, monitoring, and evaluation; and commitment to production of frequent and relevant data to inform a country’s development goals. The World Bank also has deep knowledge of measurement of major development outcomes from its perspective as a major user of economic and social statistical information. It has used its financing options (including Development Policy Loan operations) to gradually push institutional reforms and transform good data into good policy.

96. The World Bank has extensive experience in assisting countries in the development and use of statistical methodologies, survey design and implementation, and poverty analysis. It has a global perspective and substantial experience through administration of investment loans and grants (e.g., Statistical Capacity Building Program, Trust Fund for Statistical Capacity Building) on what it will take to build high-performing NSSs. The Poverty and Equity Global Practice staff work in many countries and have extensive experience coordinating support of statistical capacity through partnerships with other parts of the World Bank Group (other global practices, Development Economics Data Group, Development Economics Research Group) and outside partners. The Development Economics Data Group and Development Economics Research Group are also active in areas such as national accounts and enterprise statistics. The Living Standards Measurement Study team has demonstrated over time the ability to collect and disseminate reliable welfare and agricultural data in a timely manner, including in settings where capacity is limited, and its long-term commitment to countries adds invaluable capacity within statistical institutions. The World Bank is also a leading source of knowledge and analysis of development challenges, including statistical standards, methodologies, and training. The value added comes also from the fact that the World Bank has implemented statistical projects and therefore has built experience and understanding of problems, challenges, needs, and weaknesses.

97. The World Bank is working closely with other development partners on this project, involving them in areas in which they have a comparative advantage. For example, for national accounts and CPI, the project will involve the IMF, which through IMF AFRITAC West, IMF AFRITAC West 2, and IMF headquarters already provides technical assistance in these areas to several countries, including Burkina Faso and Sierra Leone. The project will work on activities related to population censuses with the United Nations Population Fund, which is already involved in Burkina Faso, by providing technical assistance through a World Bank project. The 50 by 2030 financed through a Multi-Donor Trust Fund jointly managed by the World Bank–FAO–International Fund for Agricultural Development will provide technical and financing support to at least 50 countries by 2030 to build systems for collecting agricultural statistics.

98. In Liberia, the World Bank works closely with other developments partners in statistical development agenda of the country. Previously a Multi-donor Trust Fund (MDTF) was fundamental to implementing the statistical agenda in the country, especially in financing the Household Income and Expenditure (HIES) surveys. Engagement with other development partners will continue through this regional project, including possibly through technical assistance support.

99. EU is involved in capacity building activities in Burkina Faso and Togo. The two countries intend to create schools of statistics respectively at a Bachelor-Degree and Associate Degree levels. EU is also involved in these countries in strengthening capacities of those already on the job.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

100. The EU is involved in capacity-building activities in Burkina Faso and Togo that are intended to create schools of statistics at bachelor’s degree and associate degree levels, respectively. In Burkina Faso, the European Union has already financed an identification mission and feasibility study that can serve as input for project activities in this area. The European Union is also involved in these countries to strengthen the skills of individuals already on the job.

F. Lessons Learned and Reflected in the Project Design

101. The World Bank has funded a regional household survey harmonization project (P153702)20 covering eight West African countries, three of whom are part of this project. Moreover, all seven beneficiary countries under this regional project have implemented World Bank–supported projects, specifically statistical projects, supporting specific surveys (under the Living Standards Measurement Study program or others) or statistical capacity building in general. The lessons learned from these projects have informed the design and will inform implementation of the project.

102. The activities of the household survey harmonization regional project (henceforth WAEMU household project) started with a 15-month delay, and there were some delays at critical stages of the project, for example in transferring funds. Lengthy delays were the result of lengthy procedures that the WAEMU Commission enforced, lack of familiarity of the commission with World Bank procedures, and delays in hiring project staff. For the WAEMU household project, the financial agreement was signed between the World Bank and the WAEMU Commission, and subsidiary agreements were signed between the WAEMU Commission and each NSO. Beneficiary countries depended on the WAEMU Commission to start their activities. The current project has been designed differently. A specific agreement will be signed with each country and with the regional bodies, so delays at the regional level will not fully affect individual countries that can manage their activities with a certain level of autonomy.

103. Other problems common to many statistical projects is low capacities in procurement skills, the use of the World Bank’s Systematic Tracking of Exchanges in Procurement (STEP) system, and in some countries, FM. In most statistical capacity-building projects, the volume of procurement activities is limited, and there is no need for a dedicated procurement specialist. For this project, the situation must be assessed country by country; in countries where the NSO does not have a procurement specialist, or where the specialist is involved in many other activities, a dedicated person will be hired for the project. In addition, regional trainings will be organized before start of activities to strengthen competence in this domain; trainings will also be organized during implementation if necessary.

104. Collaboration with stakeholders is critical in the design and implementation of successful projects. For instance, in Ghana, involvement of stakeholders in implementing the activities of the Ghana Statistics Development Program (GSDP-P118858) improved lateral and vertical coordination. In Liberia, following the practice of the just- concluded MDTF, donor coordination with quarterly meetings and updates was useful in discussing progress of statistical support provided to LISGIS. These same models will be implemented in each country. First, a steering committee comprising the NSO and all the other agencies that benefit from the project will meet regularly, at least twice a year, to discuss the progress of the project, identify problems, and find solutions. Second, a donor coordination mechanism will meet regularly to discuss project activities. Such a mechanism already exists in many of these countries, and in countries where it does not, the task team leader can work with the Country Management Unit to create it. Other lessons learned are country specific.

20 The Household Survey Harmonization and Modernization Project covers Benin, Burkina Faso, Cote d’Ivoire, Guinea Bissau, Mali, Niger, Senegal and Togo. It has been approved in 2016 and started its activities in 2017. The project is expected to close in 2021.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

105. In Ghana, delay in project approval is a major concern given previous experience with the Ghana Statistical Development Program (GSDP - P118858). Lessons learnt from GSDP have informed the design of this project and we do not expect to experience in delays in the approval of this project.

106. In the case of Sierra Leone, learning by doing in statistical operations has been more successful at building skills than training and workshops. This project, including its capacity-building components, are all organized around the production of specific economic data. Various resident advisors will be hired as part of the process, providing day- to-day mentoring and training as improved systems are designed and implemented. Given the recent high staff turnover at Statistics Sierra Leone, many of the capacity-building efforts in household surveys (World Bank) and CPI and national accounts (IMF) will have to be started over.

III. IMPLEMENTATION ARRANGEMENTS A. Institutional and Implementation Arrangements

107. The project will be implemented over a five-year period. The project implementation team at STATAFRIC under the Commission for Economic Affairs at the African Union and the regional coordinating unit (RCU) in the Statistics division of the Directorate of Macroeconomic Policy and Economic Research of ECOWAS will coordinate the implementation of the regional program. However, governments of the seven participating countries will implement country-level tasks. IDA funds will be made available to the African Union and ECOWAS through a direct regional IDA grant of US$10 million: US$2.5 million for the African Union and US$7.5 million for ECOWAS. The World Bank will sign separate financial agreements with the African Union and ECOWAS, and with each participating member country.

108. The role of the project coordinating team at STATAFRIC will primarily be to provide a convening platform for high-level discussions, monitor and report on the status of implementation of SHaSA2 at the continental level, and supervise activities at the subregional entities and monitoring the progress. The African Union will prepare an annual report on implementation of SHaSA2 for the beneficiary countries during implementation of the project. The project will also support operationalization of the STATAFRIC mandate to lead coordination and promotion of harmonized, high-quality statistics in the region.

109. The RCU at ECOWAS will provide a convening platform at the subregional level and support country NSOs by making harmonization tools (protocols, standards and concepts) and platforms (data warehouses, communication tools) available; provide training activities and workshops to facilitate peer learning and institutional cooperation; and lead subregional data dissemination, communication, and use. For these activities, the RCU will be responsible for safeguards and fiduciary management (procurement, FM). For the subregional activities under component 1, the RCU will monitor, report on, and provide technical assistance to country implementation units as necessary, including support for training on leadership for the director generals and their assistants; knowledge management; dissemination, communication, and use of data; and for all other cross-cutting activities leading to the necessary regional alignment and harmonization. The RCU will have fiduciary responsibilities for activities under Subcomponent 1.1 only. The PIUs of each of the seven participating countries will be responsible for the rest of the activities under Component 1, and the RCU will coordinate at the subregional level.

110. In each country, a national PIU will be established and will implement and supervise the project. The following country-specific arrangements will be put in place.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

111. Burkina Faso: The implementation agency will be the INSD. In Burkina Faso, each project belongs to one of the Government’s budget programs and the Coordinator of the respective budget program is de facto the Coordinator of the project. This statistics project falls under the Budget Program called “Macroeconomic Management” and its Coordinator is the Director General (DG) of Economics and Planning. However, this project is special because it is regional and aims to support the implementation of SHaSA2. For that reason, the Ministry of Economy, Finance and Development has granted an exemption for the project to be under the administrative and technical responsibility of INSD instead of the DG of Economics and Planning. This exemption is confirmed in an administrative act after the financial agreement is signed. The DG of INSD will have fiduciary responsibility for the project and will be responsible for day-to-day management. At a minimum, and throughout Project implementation, the PIU will be composed of a Project Coordinator, a Project manager, a statistics specialist, a FM specialist, an accountant, a procurement specialist, and an administrative assistant. To ensure successful implementation, the project will cover operating management costs for the PIU staff, the preparation of annual work plans and budgets, project monitoring and evaluation, preparation of progress reports, and all fiduciary responsibilities. Since the project involves other agencies (Direction general of Economics, Directions of Statistics of the ministries of Basic Education, Agriculture, Livestock), in each of the agency there will be a focal point and a Technical Committee (TC) where all the beneficiaries are represented will be established.

112. Cabo Verde: The implementing agencies are the National Institute of Statistics (Instituto Nacional de Estadística, INE) and the National Directorate for Planning in the Ministry of Finance (Direção Nacional do Plano, DNP/MF). INE is headed by a President while a Director is the head of DNP. INE, in coordination with DNP, will select a project manager no later than three months from effectiveness to be funded by the project who will coordinate implementation. Fiduciary aspects of the project will be handled by the special project management unit (Unidade de Gestão de Projetos Especiais, UGPE) in the Ministry of Finance. This includes all FM aspects and procurement processes. The UGPE will hire one extra staff for the project, co-financed by other World Bank projects. UGPE will be responsible for preparing the operations manual, annual work plans, bi-annual updates on the results framework, progress reports, audits, procurement plans, interim financial reports, etc. in close coordination with INE and DNP.

113. Côte d’Ivoire: INS will be the implementation agency of the project in Côte d’Ivoire. INS is led by a DG. The DG of INS will be responsible for the fiduciary aspects of the project. A PIU will be established and will operate under the supervision of the DG of INS. The following PIU staff members will be recruited: a project coordinator, a monitoring and evaluation specialist, a FM and administration specialist, a procurement specialist, an administrative assistant and a driver. The PIU will be responsible for: (i) the day-to-day management and execution of activities supported under these project subcomponents; (ii) the preparation of annual activity and procurement plans; (iii) the drafting of contract documents; and (iv) the preparation of a consolidated report on the implementation of the project components. The project may also recruit specialized technical staff as needed, and some activities may be outsourced to third parties through contract agreements acceptable to the World Bank. The oversight of the project will be under the responsibility of a steering committee. The steering committee will include the DG of the INS and a member designated by each beneficiary agencies and the PIU Coordinator. The steering committee will have to review annual work plan, budget, annual progress reports and provide guidance for an effective implementation of the project. Its detailed composition will be outlined in the project manual of procedures.

114. Ghana: GSS will be the implementing agency and the Coordination and Program Management Directorate (CPMD) within GSS will coordinate all project activities with all beneficiary agencies, including financial and procurement management. The implementation arrangement in Ghana will be similar to that of previous World Bank supported statistics project. The project Oversight Committee (OC) will be responsible for oversight and governance of the project, and the project TC will be tasked with reviewing progress; addressing any critical problems; and,

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

preparing and reviewing project work programs, budgets, procurement plans, and financial, and monitoring and evaluation reports. TC members will be technical representatives from GSS and participating MDAs.

115. Liberia: The official provider of statistics in Liberia, LISGIS will be the main beneficiary of the project and the implementing agency. LISGIS management headed by the DG will oversee the PIU which is composed of a project coordinator, assistant project coordinator, monitoring and evaluation specialist, procurement officer or specialist, and finance officer or specialist. The Project Implementation Team will periodically provide written updates to LISGIS management of ongoing and planned project activities based on the annual work plan and results framework. After the fiduciary assessments particularly on procurement, LISGIS’s capacity to implement the project and reporting will benefit from intensive implementation support to guide the project implementation team. Mitigating measures include separation of responsibility for management of the fiduciary services by the Project Financial Management Unit (PFMU) in the Ministry of Finance and audit of the project. Therefore, the same arrangement as used in the previous MDTF project will be used, whereby PFMU will conduct the FM, and the Procurement Director of LISGIS will conduct procurement. PIT in consultation with the PFMU will prepare the annual budget which will be approved by the PFMRSC (or Project Steering Committee (PSC). PSC is composed of the Directors of statistics units at the MACs representing the NSS and will meet semi-annually to approve projects annual workplan and budgets. PTC is composed of the Directors and Heads of Departments within LISGIS and a representative from the Aid Management Unit (AMU) and will be responsible for ensuring the quality of the project activities. The project under Component 3 will support improvement in the capacity of the Aid Management Unit at the Ministry of Finance and Development Planning (MFDP) in order to enhance its effectiveness in providing project support on evaluation and monitoring.

116. Sierra Leone: Statistics Sierra Leone will be the implementing agency for the project in Sierra Leone and will coordinate with other government agencies and line ministries on implementation. The Ministry of Finance will provide fiduciary management under the PFMU, which will coordinate day-to-day activities and reporting and auditing responsibilities. It will also be responsible for compliance with World Bank procurement, disbursement, and FM policies and procedures. A good working relationship between PFMU and Statistics Sierra Leone has been established with the Integrated Household Survey project.

117. Togo: INSEED will be the implementation agency of the project in Togo. The institute is in charge of the coordination of the NSS and the secretariat of the National Board of Statistics in conformity with decree No. 2015- 020/PR signed on February 24, 2015. INSEED is led by a DG. In order to ensure efficiency and transparency, a Steering committee composed of representatives of the beneficiary agencies of the project will have oversight of the implementation of the project. This Committee will be tasked with review and approval of annual work plans and budget, monitoring progress, providing guidance for an effective implementation of the project and addressing any critical issues. INSEED will be responsible for coordinating all project activities, including financial and procurement management. INSEED is already managing the implementation of a PPA. It has established a PIU composed of the DG as coordinator, a focal point, a financial assistant and an accountant. This will be reinforced by an experienced statistician specialist in Monitoring and Evaluation (M&E), a FM specialist, a procurement specialist. As for the other countries, the PIU will be responsible for: (i) the day-to-day management and execution of activities; (ii) the preparation of annual activity and procurement plans; (iii) the drafting of contract documents; and (iv) the preparation of a consolidated report on the implementation of the project components. The project may also recruit specialized technical staff as needed, and some activities may be outsourced to third parties through contract agreements acceptable to the World Bank.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

B. Results Monitoring and Evaluation Arrangements

118. Results will be monitored and evaluated based on the results framework described in Section VII. A core set of PDO-level indicators and intermediate indicators with baselines and targets has been agreed on. The project coordinators at the implementation units will be responsible for monitoring and evaluating results at the national level for each of the seven participating countries, and the coordinator at ECOWAS will aggregate results at the regional level. There is an overall Results Framework to measure regional progress and country-specific Results Frameworks with customized annual targets. Results will be reported biannually in the Implementation Status Reports (ISRs).

119. A detailed annual work plan and progress report will be used to monitor the status of project implementation on a day-to-day basis and will benchmark results achieved against the results framework. Additional updates on status and project activities and indicators will be provided as requested and necessary.

C. Sustainability

120. The proposed regional focus of the statistics project will create economies of scale that facilitate introduction and expansion of innovations, peer-to-peer reviewing and learning and provide substantial opportunities for NSOs of participating countries to strengthen their statistical systems in the production, dissemination, and use of core economic and social statistics.

121. In many cases, statistical capacity-building projects have not been sustainable because of lack of financing. There are many explanations for the lack of involvement of governments in financing statistical activities, but three major ones have been identified: absence of institutional financing mechanisms, low capacities of human resources, and lack of demand for statistics from government.

122. In some countries (Burkina Faso, Cabo Verde, Côte d’Ivoire), the project will support reform planned to create a statistics fund and agreeing with NSOs on the provision of adequate public resources for official statistics. 123. When NSS lacks competent human resources, it relies on technical assistance, but technical assistance can never be a perfect substitute for local competent staff. The goal of the project is to support capacity building in academic training in Burkina Faso, Liberia, and Togo; on-the-job training in all countries; and institutional reforms in Burkina Faso, Côte d’Ivoire, Liberia, and Togo. These activities will benefit NSSs and other agencies that use data, including analytical work, such as departments of economic affairs. Strong human resources will ensure that, if funds are available, countries can deliver statistical products that meet international standards. Increasing demand for statistics for monitoring and evaluation will reinforce the need to increase budget allocations for statistics, increasing long- term sustainability.

124. Weak demand for statistics from the governments is a consequence of limited use of statistics for decision making, which is a result of lack of access to data (particularly microdata) and weak analytical ability. One subcomponent of the project is dedicated to data access, including supporting the institutional reforms needed for NSOs to anonymized microdata and make them publicly available. It is felt that making data available, in addition to training activities mentioned above, will increase demand for statistics for monitoring and evaluation and reinforce the need to increase the budget for statistics, thereby increasing long-term sustainability.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

IV. PROJECT APPRAISAL SUMMARY A. Technical, Economic, and Financial Analysis

125. Investment in statistics is not amenable to a detailed cost-benefit analysis. NSOs have limited opportunities for significant cost recovery (apart from erratic and insignificant revenues generated from data dissemination), so the financial returns from this project will not be representative of the economic returns, although improvements in statistical operations will produce higher-quality data, which could have significant benefits. First, high-quality data will reduce the information cost of all economic activities. Second, better data will enhance evidence-based decision making at policy, program, and project levels. Third, the project will increase the ability of producers and users to interpret and act on statistical information and will elicit cooperation among them.

126. Paying for production of statistics also yields a good return on investment. Availability of good-quality, transparent, timely disseminated macroeconomic and financial data reduces sovereign borrowing costs on international capital markets. Adherence to the Special Data Dissemination Standards, for instance, has been found to lower borrowing costs by 50 basis points by reassuring international investors on the reliability and serviceability of a country’s economic and financial data.

127. Production of official statistics is a sovereign mission of the state. Although quantification of the benefits of the project and recovery of funds invested is hard to estimate, the public good nature of the availability of timely, reliable statistics is critical for accountability and transparency and provides a strong rationale for public involvement. The capacity of NSSs would remain limited without this project, and major data gaps would take considerably longer to fill. Beneficiaries of the project include the public and private sectors, civil society, development partners, and the public at large.

128. Economic analysis of this project considers the counterfactual without a World Bank–funded regional statistical project. As stated earlier, donor organizations provide most funding for large data-collection activities. Government funding for statistics is highly volatile because of other priorities, including in social sectors and security. If the project does not go forward, there will be serious negative effects on the ability of the governments and the World Bank to use evidence for informed policy making and to monitor the progress and effect of public policies on the World Bank twin goals.

129. The technical design of the project is based on national priorities and international best practices. The technical design and components of the project are based on the needs that NSOs expressed in the NSDS and in consultations with the staff and management of NSOs and a wider group of policy makers. The design and components of the project also reflect the demand for statistics from governments in all seven countries (including specific indicators developed for the SDGs), the World Bank, and other development partners. The design of the project is in line with international best practices on core social and economic statistics such as, poverty and household surveys, farm (agriculture) and non-farm (enterprise) surveys of the economy, and price and national account data improvement.

B. Fiduciary

(i) Financial Management

130. The FM functions for the project will be performed by INSD for Burkina Faso; INS for Côte d’Ivoire; the Finance Directorate of GSS for Ghana; PFMU of the Ministry of Finance and Development Planning for Liberia; PFMU of the

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

Ministry of Finance for Sierra Leone; the External Fund Management Unit in the Finance Department for the ECOWAS Commission; the External Resources Management Division in the Directorate of Planning, Budgeting, Finance, and Accounting for AUC; INSEED for Togo; and UGPE of the Ministry of Finance for Cabo Verde.

131. The FM of these entities that will perform FM functions for the project was assessed. The objectives of the assessments were to determine whether the proposed FM arrangements can correctly and completely record all transactions and balances relating to the project; will facilitate preparation of regular, accurate, reliable, timely financial statements; will safeguard the project’s assets; and will be subject to acceptable auditing arrangements.21

132. The Financial management risk rating is assessed as substantial. To strengthen the FM system in the assessed implementing entities, some action plans must be implemented. Further to the recommended action plans being implemented within the agreed-upon timeframe, the FM arrangements will satisfy the World Bank’s minimum FM requirements in accordance with bank policy and directives on investment project financing. Taking into account the risk mitigation measures, the FM residual risk for this financing is assessed as substantial. IDA will disburse the credit and grant through a dedicated designated account. The specific banking arrangement will comprise one designated account and one project account opened in a financial institution acceptable to IDA and managed by the implementing entity. Accountants designated for the project will produce agreed-upon financial reports on a timely basis and of acceptable quality. In each of the participating countries and regional entities, the implementing entity will appoint an independent external auditor on the basis of ToRs acceptable to IDA to audit the project and submit a copy of the audit report together with the management letter to IDA within an agreed-upon time.

(ii) Procurement

133. For all Implementing agencies in the various countries, procurement under the proposed project will occur in accordance with the World Bank Procurement Regulations for Investment Project Financing Borrowers, dated July 2016 and revised in November 2017 and August 2018, and the Guidelines on Preventing and Combating Fraud and Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants, dated October 15, 2006, and revised in January 2011 and July 1, 2016, and other provisions stipulated in the financial agreements using the standard procurement documents accompanying the regulation. STEP will be the platform for preparing, reviewing, and clearing procurement plans and reviewing prior review of procurement activities (for post reviews government systems will be used).

134. Procurement capacity assessments. Consistent with the above procurement arrangements, different procurement assessments have been carried out for the 9 implementing agencies in the various countries by the World Bank respective Procurement Specialists during project preparation in accordance with PRAMS. The implementing agencies are GSS in Ghana, INSD in Burkina Faso, UGPE in Cabo Verde, the National Statistical Institute in Côte d’Ivoire, LISGIS in Liberia, Statistics Sierra Leone in Sierra Leone, INSEED in Togo, ECOWAS in Nigeria, and the African Union in Ethiopia. Procurement ability was assessed as required for any implementing agency for investment project financing. The full summary of the completed procurement assessments and suggested measures to address identified inadequacies and risks are provided in Annex 1. A brief synopsis of the summary is given below.

135. Each implementing agency will be responsible to ensure timely implementation of procurement activities. Some

21 FM assessments were conducted in compliance with Bank Policy and Bank Directive: Investment Project Financing and related directives and guidance notes, including Bank Directive: Financial Management Manual for World Bank Investment Project Financing Operations issued February 4, 2015, and effective March 1, 2010; and Bank Guidance: Financial Management in World Bank Investment Project Financing Operations, issued and effective February 24, 2015.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

statistics agencies have implemented procurement activities under past World Bank-funded projects on statistics though often with delays. These delays can be attributed to insufficient proficiency and experience from procurement officers with the new World Bank procurement framework, delays in executing procurement activities, poor record keeping and filing, inefficient organization and management of procurement, and possible governance problems are critical risks. These risks will be mitigated through hiring proficient procurement specialists; continuous World Bank supervision, support, and monitoring...

136. Overall, the project procurement risk rating is substantial.

C. Safeguards

(i) Environmental Safeguards

137. Only one part of the Sierra Leone country-specific component (building repairs and renovations of the Statistics Sierra Leone office in Freetown) triggers safeguard policies. The other components of the project are related to data collection, training, and harmonization of methodologies and do not trigger any safeguard policies.

138. The main adverse environmental effects are site specific and transient and are related to the proposed construction of additional floors and rehabilitation of the Statistics Sierra Leone office building. Rehabilitation of the building will include replacing the windows and doors, improving the internal supply of water and electricity, and replacing old wiring and plumbing. The expansion work includes construction of three floors on top of the existing structure, adding reinforced concrete columns and adjustable steel columns, fixing doors and windows, painting and tiling the floor, and fixing air conditioners. The main challenges include disposing of construction material, including asbestos, and spillage of such things as machine oil and lubricants; creation of nuisance in the form of dust and noise due to the construction activities; and disposal of excess material. The project has been assigned Environmental Category B—Partial Assessment, because it encompasses construction of additional floors and rehabilitation of the building. All work is within the footprint of the current facility. The prevention and mitigation measures are known and easily implementable. Statistics Sierra Leone developed an environmental and social management plan (ESMP) to ensure compliance with the World Bank’s environmental assessment policy (OP/BP 4.01). The project triggers physical and cultural resources protection (OP/BP 4.11) given Sierra Leone’s rich archaeological and cultural resources and the likelihood that the project will support projects requiring excavation, especially the addition of reinforced columns. The ESMP includes chance find procedures and measures to screen for and manage potential effects on cultural heritage or property that neighborhood development plans could affect. The location of the project interventions is not expected to harm natural habitats, including critical or sensitive areas. The ESMP specifies mitigation measures for various potential harms in the preconstruction, construction, and operation phases of the project. Funds for implementing the ESMP are included in project cost estimates. The ESMP has been prepared and publicly disclosed on December 5th, 2019.

(ii) Social Safeguards

139. Safeguards. The project design and activities do not pose major social risks. Rehabilitation of Statistics Sierra Leone’s office is within its premises and will not result in physical relocation, so no social safeguards policies are triggered for this project. Nevertheless, the rehabilitation will have some health and safety implications that will be addressed under the project’s Environmental and Social Impact Assessment and Environmental and Social Management Plan.

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

140. Social Risks and Benefits. The project will have significant social benefits because it will improve the availability of critical social and poverty statistical data, leading to better policy decisions, project-level planning, and targeting of social and economic development interventions. The project will incorporate the Washington Group set of short questions into the household surveys and population censuses to enhance the collection and use of data about people with disabilities. The project also presents an opportunity to support the gender tag commitment by designing actions to address gender gaps in data collection and analysis and to support capacity and training of staff responsible for data administration. Special consideration will be made for training women in the learning programs and as enumerators for data collection. A desktop gender analysis will be undertaken to explore gender gaps in statistics and data collection and explore entry points within the project scope to help respond to these gaps. Project activities will include steps to disseminate statistical information to a wide variety of users. This should include measures to reach local councils to meet local needs. Among the various platforms for data dissemination is web-site maintenance and an online data access portal. This online interface will be user friendly and should allow for collection of comments, questions, and queries and ensure feedback. Wherever feasible, efforts will be made to ensure that persons with disabilities can access data and reports, particularly those with hearing and visual impairment, by exploring available technologies. There is the potential for sexual exploitation and requests for sexual favors stemming from individuals responsible for selecting staff for training and recruitment of enumerators, as well as enumerators themselves engaged in administering questionnaires to respondents. The project will ensure transparency and communication on eligibility for staff training, provide training on harassment and gender-based violence, have enumerators and program staff sign a code of conduct, and implement a communication and grievance redress process adapted to risk of gender-based violence.

(iii) Citizen Engagement

141. A user satisfaction survey will be conducted as part of Citizen Engagement approach in the first year of implementation to measure the level of satisfaction of the various stakeholders with data quality, timeliness and accessibility. Two other user satisfaction surveys will be undertaken in later years of project implementation and the feedback will be used to improve implementation and course-correct of interventions as needed. Additionally, a grievance redress mechanism (GRM) will be developed in the first eighteen months at the local and national levels to allow affected stakeholders to raise grievances or seek information. The GRM will be designed in consultation with relevant stakeholders including the private sector. It will establish accessible and transparent procedures and will include the provision for appeal if aggrieved parties are dissatisfied with the outcome.

(IV) Grievance Redress Mechanisms

142. The project will analyze existing GRMs in other projects in participating countries and regional bodies and propose a comprehensive two-pronged mechanism which will enable stakeholders to submit grievances, concerns, questions and feedback to the PIE. The GRM will be accessible at the local and national levels and will be designed to channel grievances from project stakeholders; address issues related to project implementation. The GRM will have clear and transparent procedures from uptake to resolution and feedback. Specific GRM procedures will be designed and provided by contractors for workers to raise workplace concerns.

143. Communities and individuals who believe that a World Bank–supported project harms them may submit complaints to existing project-level grievance redress mechanisms or the World Bank’s Grievance Redress Service, which ensures that complaints received are promptly reviewed to address project-related concerns. Project-affected communities and individuals may submit complaints to the World Bank’s independent Inspection Panel, which determines whether harm occurred, or could occur, as a result of World Bank noncompliance with its policies and

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

procedures. Complaints may be submitted at any time after concerns have been brought directly to the World Bank's attention and Bank management has been given an opportunity to respond. For information on how to submit complaints to the World Bank’s corporate Grievance Redress Service, visit http://www.worldbank.org/en/projects- operations/products-and-services/grievance-redress-service. For information on how to submit complaints to the World Bank Inspection Panel, visit www.inspectionpanel.org

V. KEY RISKS .

144. The overall risk rating for this project is assessed as substantial. The primary risks that could jeopardize achievement of project outcomes are sector strategy and policy, sustainability and fiduciary.

145. Technical risks are rated as high. The technical design of the project does pose major risks to the achievement of the development objectives. The project includes resources for capacity building and technical assistance where existing capacity may not be sufficient. An important technical risk factor is related to supporting the implementation of population censuses which the project supports in several beneficiary countries. Risks associated with supporting population censuses include: (i) procurement of equipment and vehicles and associated governance risks; (ii) reputational risks involved in being associated with a population census and associated policy outcomes; iii) technical risks related to weak-technical preparation of the operation which can lead to the extension of the period of data collection and costs increase; and iv) risks related to insecurity in some countries. The risk associated with population censuses on this operation is however not at the same level in all countries. It can be classified as high in Côte d’Ivoire and Ghana because data collection is planned very soon (between March and May 2020 in both countries), there might not be enough time for procurement of necessary goods and services in both countries and in the case of Ghana, the funds involved are substantial. The risk is substantial in Sierra Leone and Liberia because of low capacity. The risk is moderate in Togo and is assessed as low in Burkina Faso as only analytical work is anticipated. To mitigate the risks arising from support to population censuses, procurement review has been done for the procurement of certain categories of goods. The project team will also undertake frequent supervision missions on this activity. As for issues related to insecurity, the project will support the NSOs to design a clear mapping of the level of insecurity in the country and adapt the data collection approach. This has been done recently in Burkina Faso.

146. Some of the technical challenges may lie in the transition to CAPI for administration of the Household Income and Expenditure Survey 2022 in Liberia and the Integrated Household Survey 2022 in Sierra Leone. Significant resources are dedicated in Subcomponent 1.5 to ensure the transition is successful. The World Bank has expertise in supporting this transition from its experience in many other countries, including FCV countries. Another dimension of technical risk stems from limited capacity in some NSOs involved in the project, particularly weak data processing ability. Solid, well-designed technical assistance will be necessary. This risk will be high in Burkina Faso, Liberia and Sierra Leone. In Burkina Faso, the technical design of the project includes activities in which NSS has expertise, but there are also activities in which NSS is weak, namely enterprise and labor statistics. The project will ensure that capacity-building activities, including short-term training and technical assistance, will be available to mitigate this risk. For Liberia and Sierra Leone the team will rely on resident statistical advisors and consultants to develop local capacities.

147. Institutional capacity and sustainability risks are substantial. One of the main weaknesses of statistical systems in sub-Saharan Africa is their inability to create demand for statistics from their governments. If this demand exists, governments will make greater effort to secure financial resources for NSOs. The project will work in three areas to achieve this goal: Burkina Faso and Côte d’Ivoire will set up a national fund for statistics (similar to what has been

The World Bank Harmonizing and Improving Statistics in West Africa (P169265)

done in Mali), supporting production of high-quality statistics by introducing modernization when necessary (e.g., use of CAPI in data collection), and supporting use of data by easing data access and supporting data analysis and dissemination of analytical product. Availability of future financial resources is also a concern and a potential threat to sustainability of project outcomes. Project activities designed to strengthen the human and technical abilities of NSOs and align deliverables with the priorities contained in their respective NSSs in an effort to restore their positive image will mitigate this risk. In addition, the World Bank will signal to donors the long-term engagement of statistical institutions in these countries and beyond through this regional initiative to reduce the risk of continued reliance on ad hoc donor financing.

148. The overall fiduciary risk for the project is rated substantial. The project will involve many statistical agencies, and some are better endowed in human resources than others. In Burkina Faso, experiences with the WAEMU regional project have shown that the ability of INSD to comply with FM procedures on projects that the World Bank finances is limited. The mitigating measures include hiring or appointing enough qualified staff to handle procurement and FM tasks and provide them with adequate training when the project is implemented. In Sierra Leone a PFM assessment in the past led to the proposed Project Fiduciary Management Unit (PFMU). Project management would be provided by the MoF, under the PFMU. In Liberia, PFMU, in the Ministry of Finance and Planning, which has experience working with World Bank projects, will handle the FM aspect of the project, and LISGIS will fulfill the procurement roles. In Ghana, GSS will handle procurement and FM, given that it has in-house capacity. In Togo, the risk rating on institutional capacity for implementation and sustainability is substantial because of limited managerial capacity and lack of clarity about high-level support for deep institutional reform. Approximately 20 percent of INSEED staff members are directly and actively involved in data production. Although these individuals tend to be self-motivated and overextended, many of the middle cadre are underemployed. Staff need to be rewarded according to productivity and capacity and in ways that avoid lay-offs. For Côte d’Ivoire the fiduciary risk involved is substantial given the low experience of the implementing agency to implemented World Bank funded projects. The project will hire fiduciary team to support the NSO on project procurement and financial management. In Cabo Verde, the risk is substantial given the workload as the team is working on the implementation of three other projects.

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

VI. RESULTS FRAMEWORK AND MONITORING

Results Framework COUNTRY: Western Africa Harmonizing and Improving Statistics in West Africa

Project Development Objectives(s) Strengthen the statistical systems of participating countries and regional bodies in Africa to harmonize, produce, disseminate and enhance the use of core economic and social statistics.

Project Development Objective Indicators

RESULT_FRAME_T BL_ PD O Indicator Name DLI Baseline End Target

Strengthening statistical systems.

Modified Statistical capacity index (SCI 2.0) (disaggregated by 30.00 50.00 participating countries) (Percentage)

Ghana (Percentage) 65.00 75.00

Liberia (Percentage) 50.00 65.00

Sierra Leone (Percentage) 50.00 65.00

Togo (Percentage) 60.00 75.00

Cabo Verde (Percentage) 55.00 70.00

Burkina Faso (Percentage) 70.00 75.00

Cote D’Ivoire (Percentage) 65.00 75.00

Share of beneficiary countries (National Statistical Office) that 0.00 70.00

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RESULT_FRAME_T BL_ PD O Indicator Name DLI Baseline End Target score at least 30 out of 50 for the ICI. (Percentage)

Ghana (Percentage) 20.00 30.00

Liberia (Percentage) 10.00 30.00

Sierra Leone (Percentage) 10.00 30.00

Burkina Faso (Percentage) 20.00 30.00

Togo (Percentage) 20.00 40.00

Cote d'Ivoire (Percentage) 23.60 35.00

Production and dissemination of harmonized statistics

Share of comparable core economic and social statistics 0.00 50.00 indicators produced and available for open access (Percentage)

Ghana (Percentage) 0.00 60.00

Liberia (Percentage) 0.00 40.00

Sierra Leone (Percentage) 0.00 40.00

Togo (Percentage) 0.00 60.00

Cabo Verde (Percentage) 0.00 30.00

Burkina Faso (Percentage) 0.00 60.00

Cote D’Ivoire (Percentage) 0.00 60.00

Share of comparable core economic and social statistics datasets 0.00 50.00 produced and available for open access (Percentage)

Ghana (Percentage) 0.00 60.00

Liberia (Percentage) 0.00 40.00

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RESULT_FRAME_T BL_ PD O Indicator Name DLI Baseline End Target

Sierra Leone (Percentage) 0.00 40.00

Togo (Percentage) 0.00 60.00

Cabo Verde (Percentage) 0.00 30.00

Burkina Faso (Percentage) 0.00 60.00

Cote D’Ivoire (Percentage) 0.00 60.00

Share of statistical products produced and published by the NSO following international standards and a predetermined release 0.00 50.00 calendar (Percentage)

Ghana (Percentage) 28.00 70.00

Liberia (Percentage) 14.00 43.00

Sierra Leone (Percentage) 14.00 43.00

Togo (Percentage) 28.00 70.00

Cabo Verde (Percentage) 28.00 70.00

Burkina Faso (Percentage) 28.00 70.00

Cote D’Ivoire (Percentage) 28.00 70.00

Enhance the use of statistics

Share of countries that produce and disseminate at least two analytical reports using survey, macro or administrative data. 0.00 80.00 (Percentage)

Increase in user satisfaction index (Percentage) 0.00 10.00

Ghana (Percentage) 0.00 10.00

Liberia (Percentage) 0.00 10.00

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RESULT_FRAME_T BL_ PD O Indicator Name DLI Baseline End Target

Sierra Leone (Percentage) 0.00 10.00

Togo (Percentage) 0.00 10.00

Cabo Verde (Percentage) 0.00 10.00

Burkina Faso (Percentage) 0.00 10.00

Cote D’Ivoire (Percentage) 0.00 10.00

PDO Table SPACE

Intermediate Results Indicators by Components

RESULT_FRAME_T BL_ IO Indicator Name DLI Baseline End Target

Harmonization, Data Collection, Quality Improvement, Dissemination and Use of Core Statistics Manuals on reprocessing and adjustment methodologies adopted for producing and managing all core economic and No Yes social statistics (disaggregated by participating countries) (Yes/No) (Yes/No) Ghana (Yes/No) No Yes Liberia (Yes/No) No Yes Sierra Leone (Yes/No) No Yes Togo (Yes/No) No Yes Cabo Verde (Yes/No) No Yes Burkina Faso (Yes/No) No Yes Cote D’Ivoire (Yes/No) No Yes Regional platform built or updated that enables data access, No Yes

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RESULT_FRAME_T BL_ IO Indicator Name DLI Baseline End Target archiving and dissemination (Yes/No) (Yes/No) Number of UNSD Minimum List gender indicators available using data collected within the past 5 years (Number) 78.00 132.00 Togo (Number) 7.00 12.00 Ghana (Number) 18.00 24.00 Sierra Leone (Number) 10.00 17.00 Liberia (Number) 3.00 18.00 Cote d'Ivoire (Number) 5.00 16.00 Cabo Verde (Number) 18.00 22.00 Burkina Faso (Number) 17.00 23.00 Component 2: Country-Specific Component Number of analytical reports produced and disseminated using 0 for all countries 3 reports per country survey, macro or administrative data per country (Text) NSS staff trained to produce welfare and macroeconomic statistics (disaggregated by participating countries) (number) 0.00 60.00 (Number) Ghana (Number) 0.00 12.00 Liberia (Number) 0.00 9.00 Sierra Leone (Number) 0.00 9.00 Togo (Number) 0.00 12.00 Burkina Faso (Number) 0.00 12.00 Cote d'Ivoire (Number) 0.00 15.00 Months between end of data collection and dissemination of main report (disaggregated by participating countries) (number) 12.00 8.00 (Number) Ghana (Number) 10.00 6.00

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RESULT_FRAME_T BL_ IO Indicator Name DLI Baseline End Target

Liberia (Number) 12.00 8.00 Sierra Leone (Number) 12.00 8.00 Togo (Number) 10.00 6.00 Cabo Verde (Number) 12.00 8.00 Burkina Faso (Number) 10.00 6.00 Cote D’Ivoire (Number) 10.00 6.00 Internationally accepted statistical concepts, definitions and standards are used for data compilation and validation No Yes (disaggregated by participating countries) (Yes/No) (Yes/No) Ghana (Yes/No) No Yes Liberia (Yes/No) No Yes Sierra Leone (Yes/No) No Yes Togo (Yes/No) No Yes Cabo Verde (Yes/No) No Yes Burkina Faso (Yes/No) No Yes Cote D’Ivoire (Yes/No) No Yes Data Quality Assessment Framework developed (Yes/No) No Yes (Yes/No) Ghana (Yes/No) No Yes Liberia (Yes/No) No Yes Sierra Leone (Yes/No) No Yes Togo (Yes/No) No Yes Cabo Verde (Yes/No) No Yes Burkina Faso (Yes/No) No Yes

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RESULT_FRAME_T BL_ IO Indicator Name DLI Baseline End Target

Cote d'Ivoire (Yes/No) No Yes Data release calendar updated regularly (Yes/No) (Yes/No) No Yes Ghana (Yes/No) No Yes Liberia (Yes/No) No Yes Sierra Leone (Yes/No) No Yes Togo (Yes/No) No Yes Cabo Verde (Yes/No) No Yes Burkina Faso (Yes/No) No Yes Cote d'Ivoire (Yes/No) No Yes

IO Table SPACE

UL Table SPACE

Monitoring & Evaluation Plan: PDO Indicators Methodology for Data Responsibility for Data Indicator Name Definition/Description Frequency Datasource Collection Collection A composite score assessing the capacity of a country's Modified Statistical capacity index (SCI statistical system, based on NSO to update SCI data Annual NSO NSO 2.0) (disaggregated by participating a diagnostic framework sheet countries) assessing the methodology; data sources; and periodicity and timeliness. Ghana

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Liberia Sierra Leone Togo Cabo Verde Burkina Faso

Cote D’Ivoire The ICI is designed to conduct systematic functional reviews to identify and analyze an Institution’s capacity across three areas: (i) staffing and human resources policies; (ii) management, incentive, and institutional arrangements; and (iii) Share of beneficiary countries (National NSO to update ICI data knowledge and learning Annual NSO NSO Statistical Office) that score at least 30 sheet (competencies, learning out of 50 for the ICI. plans, knowledge systems). Each area is composed of technical indicators that are measured systematically. The maximum score of each area is 50 and the overall ICI is the average the scores of the three areas. The ICI indicator does not apply for all beneficiary countries and

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

not all three areas are covered by the activities of the project. The project support only NSO to update ICI data Annual NSO NSO Ghana one area of the ICI: sheet

Knowledge and learning The project support only NSO to update ICI data Annual NSO NSO Liberia one area of the ICI: sheet

Knowledge and learning The project support only NSO to update ICI data Annual NSO NSO Sierra Leone one area of the ICI: sheet

Knowledge and learning The project support all three areas: (i) staffing and human resources policies; (ii) NSO to update ICI data Annual NSO NSO Burkina Faso management, incentive, and sheet

institutional arrangements; and (iii) knowledge and learning The project support all three areas: (i) staffing and human resources policies; (ii) NSO to update ICI data Annual NSO NSO Togo management, incentive, and sheet

institutional arrangements; and (iii) knowledge and learning The project support all three areas: (i) staffing and human NSO to update ICI data resources policies; (ii) Annual NSO NSO Cote d'Ivoire sheet management, incentive, and

institutional arrangements; and (iii) knowledge and

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

learning The indicators to be considered are the following: (i) Population size by region and areas of residence, (ii) Poverty indices, (iii) Inflation rates, (iv) Production volume of Share of comparable core economic and main staple crops, (v) Value Annual NSO Direct ECOWAS social statistics indicators produced and added of SMEs and MSMEs, available for open access (vi) Gross domestic product growth and (vii) underemployment rate. Open access means available to the users on a website. Statistics are comparable when produced using similar methodologies. Ghana

Liberia Sierra Leone

Togo

Cabo Verde Burkina Faso Cote D’Ivoire Share of comparable core economic and The list datasets include: (1) Annual NSO Direct NSO social statistics datasets produced and Anonymized cartography

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

available for open access dataset; (2) Anonymized household poverty survey, (3) CPI dataset, (4) Anonymized agricultural census or annual survey dataset, (5) Anonymized updated business registry, (6) Input-output tables, and (7) Anonymized labor force surveys dataset. Open access means available to the users on a website or upon request. Statistics are comparable when produced using similar methodologies. Ghana

Liberia Sierra Leone

Togo

Cabo Verde Burkina Faso

Cote D’Ivoire Core economic and social Share of statistical products produced and statistics include household published by the NSO following Annual NSO Direct NSO poverty survey (Poverty international standards and a indices), CPI (Inflation rate), predetermined release calendar agricultural census and

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

annual survey data (agricultural production), economic census and annual survey data, national accounts (GDP growth rate), and labor force surveys ( underemployment rate). For each statistical output of a subset of the core economic and social statistics, a methodological manual or guideline is produced or applied based on international standards, and a release calendar is set and adopted by all countries.

Ghana Liberia

Sierra Leone Togo

Cabo Verde

Burkina Faso Cote D’Ivoire Share of countries that produce and The analytical reports are NSO and Annual Direct NSO disseminate at least two analytical reports those produced using others using survey, macro or administrative population data, households Government

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

data. surveys data, labor force Agencies, surveys, enterprise or Universities agricultural surveys data, and local macroeconomic data research including national account, centers or price data. the reports think tanks. include but not limited to economic updates, economic projections and shocks policy impact analysis. The user satisfaction index will be computed from user Three times surveys. A baseline survey (I) first will be conducted the first year, (ii) third year of the project and Direct NSO Increase in user satisfaction index year and (iii) follow-up surveys in years fifth year of three and five. This indicator the project will measure the change in

percentage points from baseline. Ghana Liberia

Sierra Leone Togo

Cabo Verde Burkina Faso

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Cote D’Ivoire

ME PDO Table SPACE

Monitoring & Evaluation Plan: Intermediate Results Indicators Methodology for Data Responsibility for Data Indicator Name Definition/Description Frequency Datasource Collection Collection A manual is adopted if it is Manuals on reprocessing and adjustment used in a specific statistical methodologies adopted for producing and survey or to construct a Annually NSO Direct ECOWAS managing all core economic and social specific index (GDP, CPI) statistics (disaggregated by participating Idem as above at the countries) (Yes/No) regional level

Ghana

Liberia Sierra Leone Togo

Cabo Verde Burkina Faso

Cote D’Ivoire Regional platform built or updated that Idem as above at the Annually ECOWAS Direct ECOWAS enables data access, archiving and regional level dissemination (Yes/No) Number of UNSD Minimum List gender indicators available using data collected within the past 5 years

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Togo Ghana Sierra Leone Liberia Cote d'Ivoire

Cabo Verde Burkina Faso Number of analytical reports produced and disseminated using survey, macro or administrative data per country Number of staff trained to use CAPI in censuses (population, enterprises, agriculture) and surveys NSS staff trained to produce welfare and (household, LFS, Annually NSO Direct NSO macroeconomic statistics (disaggregated enterprises, agriculture) and by participating countries) (number) in CPI data collection. Staff might be from NSO or any line ministry supported by the project. Ghana Liberia

Sierra Leone Togo

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Burkina Faso Cote d'Ivoire Average number of months between the end of data collection of major surveys Months between end of data collection and the release of the main and dissemination of main report Annually NSO Direct NSO results. The surveys to be (disaggregated by participating countries) consider are household (number) surveys, LFS, agriculture surveys and enterprises surveys Ghana

Liberia Sierra Leone Togo Cabo Verde

Burkina Faso Cote D’Ivoire The concepts and standards are the one adopted with Internationally accepted statistical ECOWAS (NSNA 2008, concepts, definitions and standards are harmonized methodology Annually NSO Direct NSO and ECOWAS used for data compilation and validation for the CPI, harmonized (disaggregated by participating countries) methodology for enterprises (Yes/No) surveys) and FAO (AGRI surveys)

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Ghana Liberia Sierra Leone Togo Cabo Verde

Burkina Faso Cote D’Ivoire An assessment of data quality is developed and applied in the country A calendar of dissemination Data Quality Assessment Framework of the main statistical Annually NSO Direct NSO and ECOWAS developed (Yes/No) products (CPI, national accounts, labor statistics, agricultural production, etc.) is developed and adopted

Ghana

Liberia Sierra Leone

Togo

Cabo Verde Burkina Faso

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Cote d'Ivoire A calendar of dissemination of the main statistical Data release calendar updated regularly products (CPI, national Annually NSO Direct Poverty Economists (Yes/No) accounts, labor statistics, agricultural production, etc.) is developed and adopted Ghana

Liberia Sierra Leone Togo Cabo Verde Burkina Faso Cote d'Ivoire

ME IO Table SPACE

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 1: Implementation Arrangements and Support Plan

Financial Management and Disbursement Arrangements

148. Financial management assessments of the implementing entities were conducted in October 2019, in line with the Financial Management Manual (March 1, 2010) and the AFTFM Financial Management Assessment and Risk Rating Principles (October 2010). The assessments focused on the Finance Directorate of GSSs Department; Project Financial Management Unit of Ministry of Finance and Development Planning, Liberia; Project Fiduciary Management Unit of Ministry of Finance, Sierra Leone; External Fund Management Unit in the Finance Department, ECOWAS; External Resources Management Division in the Directorate of Planning, Budgeting, Finance and Accounting, AUC; the National Institute of Statistics and Demography (INSD); The National Institute of Statistics (Directorate of Accounting) of Côte d’Ivoire; INSEED of Togo; and the Unidade de Gestão de Projetos Especiais (UGPE) in the Ministry of Finance of Cabo Verde. The objectives of the assessments were to determine whether the proposed FM arrangements: (i) are capable of correctly and completely recording all transactions and balances relating to the project; (ii) would facilitate the preparation of regular, accurate, reliable, and timely financial statements; (iii) would safeguard the project’s assets; and (iv) would be subject to acceptable auditing arrangements.

149. The FM arrangements in each of the participating country and action plan are summarized in the following sections. A conclusion of the assessments is presented in the Appraisal section.

Planning and Budgeting

150. The annual budget for the project will be derived from the approved Annual Work Plans (AWP) and procurement plans. Budget preparation will follow country procedures as applicable, and budget execution will be monitored using periodic IFRs, which will include variance analyses comparing planned with actual expenditures. Detailed procedures for planning and budgeting will be documented in the FM procedures manual.

(a) Ghana. The Director of the Coordination and Programme Management Directorate CPMD on behalf of the government statistician working in collaboration with the Director of Finance will be responsible for initiating the budgeting process for the project and will obtain inputs (activities, schedules, timelines, cost) from beneficiary agencies. GSS, as with all implementing agencies and government departments or agencies, follows the budget preparation guidelines outlined in the Public Financial Management Act, 2016 (Act 921) and the annual budget guidelines that the Ministry of Finance issues. Members of the OC will approve the budget for submission to the World Bank for review and clearance. (b) The African Union. The Internal Program and Budget Committee coordinates the planning and budgeting processes within the AUC, but the project coordinating team at the African Union Statistics division of the Commission for Economic Affairs will prepare work plans and budgets. (c) Liberia. The Project Implementation Team, in consultation with the Project Financial Management Unit (PFMU) will prepare the annual budget, which the Project Financial Management Reforms Committee (PFMRSC) will approve. (d) Sierra Leone. The PFMU will prepare the annual budget in consultation with the implementing entity, taking into account the provisions of the Government Budgeting and Accountability Act 2005. (e) ECOWAS. The accountant designated for the project in the External Funds Management Unit, Finance Department of the ECOWAS Commission will prepare the annual budget. Budget preparation will be done in line with the ECOWAS Commission Financial Regulations & Manual of Accounting

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Procedures. The annual budget once approved is uploaded into Systems Applications and Products (SAP), wherein budget execution is tracked to prevent over commitment. (f) Burkina Faso. The project accountant in consultation with key members of the implementing entity will prepare the Annual Work Plan and Budget (AWP&B) with detailed description of planned Project activities for the following Fiscal Year. On or about November 30 of each Fiscal Year, the Review Committee will approve the budget and submit it to the World Bank. The AWP&B will be adopted not later than December 31 of the Fiscal Year. (g) Côte d’Ivoire. INS will prepare a detailed consolidated annual work plan and budget. The annual work plan and budget will be submitted to the INS Board of Directors for approval and transmission to the World Bank for no-objection not later than November 30 of the year preceding the year of implementation of the budget. (h) Togo. INSEED’s FM Unit in close collaboration with the other technical units will prepare the annual work plan and budget. Annual work plan and budget will be submitted to the World Bank for no- objection not later than November 30 of the year preceding the year of implementation of the budget. Based on lessons learned, budget discussions should begin at least six months before the fiscal year of implementation. (i) Cabo Verde. UGPE will prepare the budget in consultation with INE and DNP. A detailed annual work plan and the budget will be reviewed by the project coordinator and submitted for approval to the INE board of directors and DNP management before the beginning of its execution. The annual budget will be submitted for the World Bank’s non-objection no later than November 30th of the year preceding the year of implementation of the budget.

Accounting Systems, Policies and Procedures

151. IDA funds will be accounted for using a computerized accounting system and annual financial statements prepared in accordance with the International Public Sector Accounting Standards (IPSAS). Throughout project implementation, the implementing entities shall maintain a sound accounting system that enables controls, records project transactions correctly, and can produce timely and reliable financial information. (a) Ghana. The Government of Ghana is transitioning from a manual system and introducing the automated Government Integrated Financial Management Information System (GIFMIS) using Oracle Financials. It is expected that the project will be one of the selected World Bank-financed projects piloting GIFMIS to account for and record the use of donor partners funds. Project transactions - (expenditures and receipts), will be accounted for on a cash basis of accounting. Until GIFMIS is operational, project financial records will be managed using a combination of manual accounting ledgers and spreadsheets for processing transactions and preparing periodic financial reports. (b) African Union. AUC uses SAP to process and record financial transactions. Accounts are prepared on the IPSAS accrual basis of accounting. The SAP system will be used to account for and report on project financial transactions. The chart of accounts allows reporting on World Bank-financed transactions. (c) Liberia. Project accounts will be maintained on a cash basis, using a computerized accounting system. (d) Sierra Leone. A computerized accounting system, TOM2PRO, will be used to account for the IDA funds on a cash basis of accounting. (e) ECOWAS. The accounting system in the Commission is computerized using SAP Enterprise Resource Planning system. The Grant management module of the software is being used to account for and report on Donor funds. International Public Sector Accounting Standards (IPSAS), accrual basis of accounting will be used in preparing the project financial statements.

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

(f) Burkina Faso. The prevailing accounting policies and procedures in the West African Francophone countries accounting standards – SYSCOHADA, in use in Burkina Faso for on-going World Bank- financed projects will apply. (g) Côte d’Ivoire. The prevailing accounting policies and procedures in line with the West African Francophone countries accounting standards – SYSCOHADA- in use in Côte d’Ivoire and Burkina Faso for on-going World Bank-financed projects will apply. INS will customize the accounting software to meet the program requirements. (h) Togo. INSEED will use SYSCOHADA accounting standards which is commonly used amongst West African Francophone countries. Accounting will be done using a computerized system. (i) Cabo Verde. The UGPE will use the cash basis to maintain the project’s accounts. Annual financial statements will be prepared by the UGPE using the National Accounting Standards and Financial Reporting (SNCRF). The existing accounting software TOMPRO in UGPE, which has multi-project and multi-donor features will be used in preparing the financial reports. The software will be customized to accommodate the new project. All accounting procedures will be documented in the Project Implementation Manual.

Internal Controls and Internal Audit

152. Internal control comprises the whole system of control, financial or otherwise, established by management to: (a) carry out project activities in an orderly and efficient manner; (b) ensure adherence to policies and procedures; (c) ensure maintenance of complete and accurate accounting records; and (d) safeguard the project’s assets. The finance and administrative procedures to be employed by the implementing agencies will be documented in the project FM Manual to be finalized and adopted before the Effective Date.

(a) Ghana. The project’s internal controls will rely on the Government established accounting and internal control guidelines as documented in the Public Financial Management Act, 2016 (Act 921); and; the Public Financial Management Regulations 2019 (L.I.2378) and informed by the Internal Audit Agency Act, (Act 2003). The GSS has a functioning internal audit unit under the leadership of a qualified, experienced head. At a minimum, the internal audit unit will prepare half-yearly reports that will be shared with the World Bank. (b) African Union. The Internal Audit Directorate of the AUC conducts audits of program activities. The internal audit team reviews project activities annually. In recent years, there has been a delay in internal audit reviews. The Audit Directorate is constrained in staffing. (c) Liberia. The existing Internal Audit Unit in PFMU will ensure orderly, efficient conduct of operations of the project. The internal auditor will submit reports to the World Bank twice a year. (d) Sierra Leone. The Internal Audit Unit of the Ministry of Finance will conduct periodic internal audit reviews of project activities. Reports will be prepared and shared with the World Bank twice a year. (e) ECOWAS. The Office of the Auditor General in the Commission is responsible for internal audit function and will include audit of the project in their annual audit plan. The internal controls system of the ECOWAS Commission elaborated in the Financial Regulations & Manual of Accounting Procedures will apply to the project. Half yearly internal audit reports are prepared by the Office which will be shared with the World Bank. (f) Burkina Faso. The INSD internal auditor will perform periodic reviews of project activities and the country national institutions in charge of internal audit and administrative controls (Court of Auditors, Supreme Control and Anticorruption Authority of the State, Inspection General des Finances) will continue to fulfill their legal mandates. Reports of the periodic reviews will be shared with the World Bank. The Ministry of Economy, Finance and Development will assign an internal controller to the project to perform ex-ante controls.

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

(g) Côte d’ Ivoire. The organogram of INS includes the internal audit function as well as the audit committee and risk management. In line with the new Decree No. 475 governing the modalities of donors-financed project implementation in Côte d’Ivoire, the Inspection General des Finances (IGF) will have the responsibility of the internal audit function of the program managed by the INS. A Memorandum of Understanding will be signed between IGF and INS to allow the Government institution to conduct from time to time, some internal audit missions in collaboration with the Internal audit Unit of INS. (h) Togo. An internal auditor will be hired who will perform periodic reviews of project activities using a risk-based approach. The auditor will prepare semi-annual internal audit reports which shall be submitted to the World Bank within 45 days after the end of the relevant calendar semester. (i) Cabo Verde. An internal auditor will be hired by UGPE to perform periodic reviews of all the bank financed projects. The internal auditor will include the project in its work program and submit on a calendar semester basis its report to the bank.

Financial Reporting

153. Each implementing entity will prepare and submit periodic unaudited IFRs and annual project audited financial statements in form and content satisfactory to the World Bank. The financial reports will be prepared using computerized accounting system for quality and timely information to the project management, implementing agencies, and various stakeholders to monitor the project’s financial performance. The formats of the IFRs has been developed at appraisal and agreed at negotiation. At a minimum, the IFR will include a statement of sources and uses of funds by project components and categories; and uses of funds by project components and activities (including comparison of budget and actual expenditures).

154. The financial statements will comprise of: • A Statement of funds received, and expenditures incurred, • The Accounting Policies adopted and Explanatory Notes. The explanatory notes should be presented in a systematic manner with items on the Statement of Cash Receipts and Payments being cross referenced to any related information in the notes; and • A Management Assertion that World Bank funds have been expended in accordance with the intended purposes as specified in the relevant World Bank legal agreement. • A list of material assets acquired or procured to date with project funds.

Details of the periodicity and due date of the IFRs and audited financial statements are specified below. (a) Ghana. The GSS will be required to prepare and submit quarterly IFRs to account for activities financed from the credit, which will be submitted to the World Bank within 45 days after the end of the relevant quarter. The project annual financial statements must be audited and submitted to the World Bank within six months from the end of the government fiscal year. (b) Africa Union. AUC will prepare unaudited interim IFRs twice a year, ensuring that advances received, and expenditures made are properly accounted for. The IFRs will be submitted to the World Bank within 45 days of the end of the reporting period. To prepare IFRs, financial information relating to the project is exported from SAP to an Excel spreadsheet. The annual financial statements will be prepared using IPSAS, audited and submitted to the World Bank within six months after the end of the accounting year. (c) Liberia. The use of project funds will be reported in quarterly IFRs satisfactory to the World Bank and submitted to the World Bank within 45 days of the end of the relevant calendar quarter. The project accountant will prepare the project annual financial statements, and internal audit unit at PFMU will audit them. The audit report will be furnished to the World Bank within six months after the end of

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

the government fiscal year. (d) Sierra Leone. PFMU will be responsible for preparation and submission of quarterly unaudited IFRs for the project that will be submitted within 45 days after the end of the relevant calendar quarter. The accountant will be responsible for preparation of annual financial statements and have them audited and submitted to the World Bank within six months after the end of the government fiscal year. (e) ECOWAS. ECOWAS Commission will submit calendar semester unaudited interim financial reports within 45 days of the end of the relevant calendar semester. In addition, the Commission will prepare annual financial statements in accordance with IPSAS accrual which shall be audited and submitted to the World Bank within six months after the end of the financial year. (f) Burkina Faso. The INSD will submit quarterly unaudited IFRs to the World Bank by not later than one month after the end of each calendar semester. In compliance with the World Bank’s requirements, the project will produce annual financial statements and submit audited financial statements satisfactory to the World Bank every year within six months after the end of the fiscal year. (g) Côte d’Ivoire. Unaudited interim financial reports will be prepared every quarter and submitted to World Bank within 45 days of the end of the relevant calendar quarter. INS will submit audited program financial statements to the World Bank every year within six months of the end of the fiscal year. (h) Togo. INSEED will prepare quarterly unaudited IFRs which will be submitted to the World Bank within 45 days after the end of the reporting quarter. In addition, INSEED, will on an annual basis submit to the World Bank audited project financial statements within six months after the end of the fiscal year. (i) Cabo Verde. UGPE will produce on a calendar semester basis unaudited IFRs during project implementation encompassing activities of all the components, which shall be submitted to the World Bank within 45 days after the end of the calendar semester period. UGPE will also produce the projects Annual Financial Statements and these statements will comply with the Cabo Verde generally accepted accounting principles.

External Audit

155. In line with World Bank policy, implementing entities are required to submit annual project financial statements audited in accordance with international standards on auditing, by an independent external auditor appointed based on ToRs acceptable to IDA. Specific country arrangements are detailed in Table 2 below: Table 2: Auditing Arrangements

S/N COUNTRY IMPLEMENTING AUDIT AUDIT FIRM DUE DATE ENTITY TYPE 1 Ghana GSS Project Audit service Six months financial after end of statements government fiscal year 2 African Union African Union Project Private audit firm Six months Commission financial after end of statements government fiscal year 3 Liberia Liberia Institute of Project Private Audit Six months Statistics and Geo- financial Firm after end of Information statements government Services (LISGIS) fiscal year

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

4 Sierra Leone Statistics Sierra Project Audit Service Six months Leone Financial Sierra Leone after end of Statements government fiscal year 5 ECOWAS ECOWAS Project Private Audit Six months Commission Financial Firm after end of Statements government fiscal year 6 Burkina Faso Institut National de Project Private audit firm Six months la Statistique et de financial after end of la Démographie statements government fiscal year 7 Côte d’Ivoire INS Project Private Audit Six months Financial Firm after end of Statements government fiscal year 8 Togo INSEED Project Private Audit Six months Financial Firm after end of Statements government fiscal year 9 Cabo Verde INE and DNP Project Private Audit Six months Financial Firm after end of Statements government fiscal year

156. In each of the participating countries and regional entities, the external auditor will express an opinion on the project financial statements in compliance with ISA. In addition to the audit report, the external auditor will prepare a Management Letter (ML) containing the auditor’s assessment of the internal controls, accounting system and compliance with financial covenants in the financing agreement, suggestions for improvement, and management’s response to the auditor’s management letter. The ML along with the audited financial statements will be submitted to the World Bank not later than six months after the end of each financial year.

157. In line with the World Bank access to information policy, the implementing agencies will be required to make the annual audited financial statements publicly available on its official website. Accordingly, the World Bank will also publish the reports upon receipt.

Funds Flow and Disbursement Arrangements

158. Project funding consists of IDA credit and grant. IDA will disburse the credit and grant through segregated Designated Accounts opened with financial institutions acceptable to IDA which will be managed by the respective implementing agencies. Disbursement arrangements will follow World Bank’s disbursement guidelines and general practice and procedures applicable in each country. All project funds will be used in line with the Financing Agreement and World Bank FM procedures. Advances made to the DA would be documented either through the use of SOEs or summary reports (IFRs), and supporting documents as defined in the DL. Specific country arrangements are summarized in the table below:

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Table 3: Disbursement Arrangements

Country Implementing Designated Other Project Bank Accounts Supporting documents Entity Account (US$) (to be further detailed in DL) Ghana GSS DA - central bank Project Account denominated in local Report-based (Bank of Ghana) currency at same central bank AU AU DA - Commercial Project Account denominated in local SOE Commission bank currency at same commercial bank Liberia LISGIS DA – Commercial Project Account denominated in local Report-based bank currency at same commercial bank Sierra Statistics DA – Commercial Project Account denominated in local Report-based Leone Sierra Leone bank currency at same commercial bank ECOWAS ECOWAS Project Account denominated in local Report-based Commission currency at same commercial bank Burkina Institut Central bank Project account denominated in local SOE Faso National de la currency at a commercial bank Statistique et de la Démographie Côte INS DA – Central Project Account denominated in local SOE d’Ivoire bank currency at a commercial bank Togo INSEED DA – Commercial Project Account denominated in local SOE bank currency at the same commercial bank Cabo INE DA – BCV NA IFR Verde

159. The Figure 4 below shows the funds flow mechanism for the project activities to be financed.

Figure 2: Funds flow mechanism

World Bank (IDA)

Designated Account in Project Account in Local US$ Currency

Project transactions paid in either US$ or Local Currency

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Financial Management Action Plan Table 4: FM Action Plan

Action Responsibility Completion date

Agree format of unaudited Interim Financial GSS, AUC, LISGIS, Completed Report and external audit ToRs with the Stats SL, ECOWAS World Bank Comm, INSD, INS, INSEED, INE

Appoint external auditor for the project or GSS, AUC, LISGIS, No later than three (3) months recommend audit firm ECOWAS Comm, after the Effective Date, or at any INSD, INS, later date agreed upon in writing

GENERAL INSEED, INE, with the Association Statistics Sierra Leone Prepare the FM section of the Operations GSS, AUC, LISGIS, Before Effectiveness Manual/PIM Stats SL, ECOWAS Comm, INSD, INS, INSEED, INE Hire or assign a financial management Statistics Sierra No later than three (3) months specialist within the PFMU Leone after the Effective Date, or at any later date agreed upon in writing LEONE SIERRA with the Association

Hire or appoint FM officer and project INSD No later than one month after the accountant and train them on World Bank Effective Date, or at any later date FM and disbursement guidelines agreed upon in writing with the Association

BURKINA FASO BURKINA Designate FM specialist for the project. AUC No later than three (3) months Improve staffing level in the Internal Audit after the Effective Date, or at any AU Directorate later date agreed upon in writing with the Association Hire a FM specialist and an Accountant to INS No later than three (3) months support the INS team after the Effective Date, or at any

later date agreed upon in writing with the Association VOIRE I Complete restructuring of internal audit INS No later than three (3) months D’ function and hire/appoint Head of the after the Effective Date, or at any Internal Audit Unit later date agreed upon in writing CÔTE with the Association Procure and install an accounting software INS No later than five (5) months after SAP for the project and train staff the Effective Date, or at any later

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Action Responsibility Completion date

date agreed upon in writing with the Association

Hire FM specialist to support the INSEED FM INSEED No later than three (3) months team. Recruit an internal Auditor for the after the Effective Date, or at any

project later date agreed upon in writing

INSEED with the Association

TOGO Procure and install an accounting software INSEED No later than three (3) months for the project after the Effective Date, or at any later date agreed upon in writing

Customize the existing accounting software UGPE No later than three (3) months to include records/ledgers of the project after the Effective Date, or at any

later date agreed upon in writing

Recruit an internal auditor in UGPE UGPE No later than three (3) months CABO VERDE after the Effective Date, or at any later date agreed upon in writing

Appoint FM officer and project accountant GSS No later than three (3) months and train them on World Bank FM and after the Effective Date, or at any

disbursement guidelines later date agreed upon in writing

Recruit or engage an external auditor for the Project, with qualifications, experience and GSS No later than three (3) months GHANA terms of reference acceptable to the from the Effective Date, or at any Association. later date agreed upon in writing with the Association,

Project Financial Management Unit within LISGIS Before Effectiveness the Ministry of Finance, having responsibility for fiduciary aspects of the Project, with

composition, mandate and resources satisfactory to the Association. 3 months after the Effective Date, LIBERIA Recruit an external auditor, in accordance or at any later date agreed upon in LISGIS with terms of reference acceptable to the writing with the Association: Association

Implementation Support and Supervision Plan

160. World Bank’s FM implementation support will be consistent with a risk-based approach, and will involve collaboration with the World Bank’s task team, LOA and procurement. The supervision intensity

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

will be based initially on the PAD FM risk rating and subsequently on the updated FM risk rating during implementation. Given the substantial residual risk rating, on-site supervision will be carried out twice a year. On-site review will cover all aspects of FM, including internal control systems, the overall fiduciary control environment, and tracing transactions from the bidding process to disbursements as well as SOE review. Additional supervision activities will include desk review of periodic IFRs, quarterly internal audit reports, audited annual financial statements and management letters as well as timely follow up of issues that arise, and updating the FM rating in the Implementation Status Report (ISR) and the Portfolio and Risk Management (PRIMA) system. The World Bank’s task team will support in monitoring the timely implementation of the action plan.

Table 5: Implementation Support Plan

FM activity Frequency

Desk reviews

IFR review Quarterly/Semi-annual.

Audit report review of the program Annually.

Review of other relevant information such as interim internal Continuous as they become available. control systems reports

On-site visits

Review of overall operation of the FM system Semi-annually (implementation support mission)

Monitoring of actions taken on issues highlighted in audit As needed, but at least during each reports, auditors’ management letters, internal audit, and other implementation support mission. reports

Transaction reviews (if needed). As needed.

Capacity-building support

FM training sessions by World Bank FM team. Following the project transition and thereafter as needed.

Procurement Arrangements

161. Procurement will be carried out in accordance with: (i) the World Bank PR for IPF Borrowers Procurement dated July 2016, revised in November 2017 and August 2018; (ii) the ‘Guidelines on Preventing and Combating Fraud and Corruption in Projects financed by IBRD Loans and IDA Credits and Grants’, dated October 15, 2006, revised in January 2011 and July 2016; and (iii) the provisions stipulated in the Financing Agreement. The STEP will be the platform for preparing, submitting, reviewing and clearing procurement plans and prior review procurement activities. The PIM will elaborate on the procurement procedures, Standard Procurement Documents (SPDs) and model contracts associated with the market approaches and selection methods, for various procurement categories. The details of the procurement plans are in STEP.

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Procurement Capacity Assessments Summary:

162. Ghana - GSS: The GSS is an organization set up under the laws of Ghana (an Act of Parliament – Statistical Service Act, 2019 (Act 1003). GSS undertakes procurement in accordance with the Ghana Public Procurement Act, 2003 (Act 663), as amended by the Public Procurement (Amendment) Act, 2016 (Act 914). As a result, it has the stipulated procurement structures and uses the public procurement standard documents under the law. The entity has implemented IDA-funded project in the recent past- P118858 & P164827 - GSDP which ended December 31, 2018. – and therefore, the procurement Unit staff have proficiency in World Bank procurement using the Guidelines. The Procurement Unit is headed by a Procurement Head with much experience and led procurement delivery under the GSDP from preparation to completion. He has support from 5 procurement officers who have been with him and on the GSDP as well. They have attended a series of NPF training at the World Bank and have used STEP for a while. The main identifiable risk is the insufficient proficiency and experience of the Procurement officers in executing procurement using the World Bank procurement Regulation under the new Procurement Framework. To mitigate this risk, the World Bank will: (i) offer training in PR for the procurement team after project effectiveness, provide hands-on support throughout the lifetime of the project; and (ii) recommend periodic World Bank procurement training for the procurement officers, provided in World Bank procurement training institutions in the sub-region and beyond. The risk rating is substantial.

163. Burkina Faso - This project will be implemented by INSD, which has limited experience with the new procurement regulations under World Bank financed projects. The procurement service of INSD has three staff members, including the Senior Procurement Specialist (personne responsable des marchés) appointed in May 2019. The Department for the Regulation of Public Procurement and Finance (Direction du Contrôle des Marchés et des Engagements Financiers (DCMEF)), which is in charge of INSD, is also responsible of the Ministry of Water. The main risks identified for INSD are lack of experience in applying World Bank procurement regulation or the STEP system; lack of staff solely dedicated to this project procurement activities; lack of experience of the Department of Administration and Finance of INSD, the Senior Procurement Specialist and DCMEF on the World Bank’s new procurement framework; delays in the procurement process mainly due to delays in review of files and publication of procurement notices by DCMEF which is in charge of prior control; difficulties mobilizing the technical sub-commissions; numerous unforeseen interactions between contracting authorities and control structures due largely to the absence of a manual of procedures; and lack of space for records archiving. The proposed mitigation measures for these risks are train the Senior Procurement Specialist and staff of the Department of Administration and Finance, DCMEF, and the Tender Committee on the World Bank’s New Procurement Framework; revise the Project operational manual including the section on procurement and submit for IDA approval; nominate or hire a procurement specialist devoted to this project and having ToR, experience and knowledge acceptable to IDA; improve the recording system that includes as part of the project funding to improve safe keeping of records and clearly describes what records should be kept in the contract file, preferably in the Project operational manual/Project; and put in place a proper procurement planning system (working with focal point and beneficiaries) based on production of technical documents. The risk rating is substantial.

164. Cabo Verde - The UGPE has implemented several projects since its establishment in 1999 and has strong experience with World Bank procurement procedures and other donators. In addition, the UGPE is implementing five projects under the new Procurement Regulations, for which two procurements specialists are responsible. A recent assessment of the UGPE’s capacity to implement World Bank procurement was conducted and determined that UGPE has the experience and qualifications to carry out procurement under this project. However, this new project and three others in preparation, will increase the team’s workload. In addition, the UGPE has no technical expertise to prepare technical

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

documents and evaluate technical proposals. Therefore, the UGPE will need to work closely with technical stakeholders to ensure that they fully play their technical role in the relevant procurement activities. There are risks of possible delays in project implementation, and ineffective procurement would deliver poor results. The following mitigation measures are implemented: (i) Hire a new Procurement specialist; (ii) update the existing POMs to detail the roadmap for each procedure with the various stakeholders, the role of each, the time it has given to act and the procedures for the contracts management); (iii) establishment and maintenance of an acceptable procurement filing system throughout the life of the project; and (iv) organization of the UGPE procurement team for repartition of the workload. The risk rating is substantial.

165. Côte d’Ivoire - National Statistical Institute (INS): INS has been created in 1946 and became a public agency in December 1996 in accordance with the decree n°96-975 of December 18, 1996 related to the transformation of the National Statistical Institute in public organization. That means that since then the NSI undertakes procurement in accordance with the Public Procurement Act, n°2009-259, as amended by the Public Procurement (Amendment) Act, n°2014-306 as amended by the Public Procurement (Amendment) Act, n°2015-525. The capacity assessment of the INS focused on: (i) person in charge of the procurement process; the procedure manual and the expertise of the INS in terms of the procurement process. So, the INS do not have the necessary Procurement Unit and structure. So, the risks identified are the following ones: the lack of capacity and experience in the implementation of procurement in IDA- funded projects under new procurement regulations; the procedure manual that does not meet World Bank requirements; the lack of qualified procurement staff to be dedicated to this project. Thus, Procurement procedures will be a new experience for the entity which has to acquire knowledge and capacity in procurement. To mitigate all these risks, it will be important to hire a procurement specialist with a strong experience as well on the IDA-funded project as on the Procurement Regulation under the new procurement framework. The World Bank will also: (i) offer training in PR for the procurement newly hired procurement specialist after project effectiveness, provide hands-on support throughout the lifetime of the project; and (ii) recommend periodic World Bank procurement training for the staff involved in procurement. The procedure manual should also be updated to meet the World Bank requirements. This manual should also be submitted to the World Bank No-Objection. The risk rating is substantial.

166. Liberia -The LISGIS became an autonomous agency of Government by an Act of the National Transitional Legislative Assembly (NTLA) on July 22, 2004 and was subsequently signed into Law by the former Chairman Charles Gyude Bryant. The act is now known and cited as the National Statistics and Geo-Information Act. LISGIS as a government agency uses the Public Procurement and Concessions Act (PPCA) and Regulations, which are also available on the PPCC website. The PPCA and its Regulations are designed to meet core Procurement Principles of value for money, economy, efficiency, effectiveness, integrity, transparency, fairness, and accountability and LISGIS applies these consistently. LISGIS adheres to and upholds the procurement structures required by the PPCA and has in place a Procurement Committee whose role and responsibilities are clearly defined in the PPCA. A Director who has a Bsc. (Econ), Advanced Diploma (Proc.) and (CIPS Level 3) heads the Agency’s Procurement Unit. Three Procurement Officers two of whom are IPTP Graduates assist him. The staff’s procurement experience and record of accomplishment has however been limited to RFQ contracting. The identified risks are: (a) the unit has not carried out any open competitive bidding or selection of consultants, b) the procurement staff are less familiar with the Procurement Regulations. To mitigate this shortcoming in implementing this project, it is recommended that: i) the Agency retain the National Procurement Specialist hired to support the previous World Bank project and the preparation of this project, ii) World Bank will provide

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

training on the Procurement Regulations to the procurement staff and others, and iii) staff will benefit from the country office procurement clinics and any training in Goods, Works Consulting and Non- consulting Services within the sub-region. The risk rating is substantial.

167. Sierra Leone - The Government of Sierra Leone has established a single project fiduciary management unit (PFMU under the Ministry of Finance to manage all new World Bank finance projects. PFMU will perform procurement under this project, and Statistics Sierra Leone will manage the technical aspects. Given the country’s post-conflict and fragility context, the procurement management risk assessment found that, even though current PFMU staff are performing procurement in World Bank-funded projects, lack of capacity of the existing pool of staff despite the World Bank conducting several training and capacity-building workshops; substantial delays in internal approvals of procurement decisions because the technical teams are in different project-implementing ministries and agencies, and the procurement team is in PFMU; limited knowledge of the World Bank’s procurement regulations and use of the STEP system; need for establishment of a record-keeping system; inefficiencies and delays in the procurement process; insufficient competition in procurement; and a weak complaint redress system. The mitigation measures to address the risks and weaknesses identified is summarized as follows: capacity building by the World Bank (training in World Bank procurement procedures and systems), regular World Bank supervision and support (hand holding, monitoring), World Bank policy of disclosure of procurement activities and documentation, and a robust internal audit mechanism. The risk rating is high.

168. Togo - The statistical system is defined in the Law No. 01 / 008 of 16 July 2001 while decree no 16.0127 of 9 March 2016 establishes the National Institute for Statistics, Economic and Demographic Studies (INSEED) as a public entity with autonomous management. As a result, INSEED procurement is governed by Togo Public Procurement Law No. 2009-013 of June 30, 2009, on public Procurement and Public Service Delegations and by Decree No. 2009-277 of November 11, 2009, containing the code of public contracts and delegations of public service. This public procurement law requires INSEED to establish a Public Procurement Control Commission (Commission de contrôle des marchés publics, CCMP) and a Public Procurement Commission (Commission de la passation des marchés publics, CPMP), each consisting of five members. These two entities were set up during appraisal mission. The CPMP is chaired by the chief public procurement officer (Personne responsable des marchés publics, PRMP). A procurement unit is created and attached to the PRMP. It will house a qualified Procurement Specialist to be recruited because INSEED does not have enough experience in the management of World Bank-financed projects. Furthermore, the level of complexity of the procurement activities managed so far are not like the one for this current project. The main identifiable risks are: (i) lack of acceptable Operational Manual; (ii) no qualified procurement specialist; (iii) lack of experience of the procurement commissions (CCMP and CPMP); (iv) weak capacity of the CCPM, CPMP, and the central procurement control body (DNCMP) in the New Procurement Framework procedures. To mitigate the risks INSEED has to: (i) elaborate and submit to the World Bank for agreement, a satisfactory version of the Operations Manual comprising a section on procurement for use by the project; (ii) recruit a qualified procurement specialist; (iii) reinforce the capacity of the Procurement Commissions (CCMP and CPMP) in the New Procurement Framework procedures. The risk rating is substantial.

169. ECOWAS. The Statistics Unit of the Directorate of Macroeconomic Policy and Economic Research of ECOWAS will be responsible for procurement for the regional activities. The Directorate has no experience in the implementation of World Bank funded project. However, other directorate in ECWOWAS are currently implementing some World Bank funded and are supported by the Procurement department of ECOWAS that handles ECOWAS procurement. The main risk identified is that ECOWAS procurement officers will not be able add the RCU procurement work to their current workload. Therefore, a procurement consultant will have to be hired support the RCU procurement implementation. The risk

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

rating is substantial.

170. African Union (AU). The implementing agency of the proposed project is the African Union Institute of Statistics (STATAFRIC), which shall be housed in Tunis, Tunisia. The proposed AU component of the project shall be implemented under the umbrella of STATAFRIC since it is the official African Union Institute that is responsible to lead the coordination and the promotion of harmonized and quality data at continental, regional and national level. AUC corporate procurement function is carried out at its Procurement, Travel and Stores Division (PTSD) under the Directorate of Administration and Human Resources Management of the AUC. Thus, procurement under the proposed project is planned to be carried out under the PTSD. In view of this a procurement risk assessment was carried out at PTSD of the AUC. Some of the findings include the following: (a) PTSD is well staffed with the necessary support personnel and handles a portfolio of around US$ 100 million. There are also two qualified procurement staff at PTSD, employed under a World Bank financed project, who are familiar with the procurement procedures of the World Bank. The major challenge regarding organization and staffing is that the staff are overwhelmed with procurement planning, processing and contract administration. There is no structure within PTSD to support contract management and there is no qualified staff to handle contract administration at the PTSD. Hence procurement staff are also engaged in contract administration activities without the requisite qualification and training. There is a need for one Contract Management Officer to support the day to day contract administrations issues of the Commission. Moreover, the procurement staff need to be trained on the Procurement Regulations of the World Bank. (b) Procurement processes are carried out with the principle of value for money, economy, integrity and open competition and this is the preferred procurement method at AUC. However, direct contracting/single source selection are also utilized in some cases. This is an area which needs improvement. Procurement activities are planned and carried out in accordance with the authorized annual budget. However, procurement activities are not carried out in accordance with the timeline of the Procurement Plan (PP) particularly in the World Bank financed project. This is another area, which needs significant improvement. The AUC is updating its standard bidding documents. However, for high value contracts it is using World Bank’s standard BDs/RFPs. Business opportunities are openly advertised in AUC’s website and United Nations Development Business (UNDB) Online. The contents of the RFB/REOIs are considered adequate and the bid floating periods are also considered adequate. The evaluation reports contain the required information necessary for approval. Following the approval of evaluation reports, PTSD sends notification of contract award. However, publication of contract awards is not being done on the same media of publication. (c) The AUC has issued revised Procurement Manual, which is applicable to the wider African Union Organs. Procurement decision making and delegation of authority for contract signature is clearly stipulated in the AU Procurement Manual. Depending on thresholds decisions are made by the AU Tender Board, internal procurement committee, director of administration and human resources, and the Head of PTSD.

171. The AU procurement manual provides for lodging complaints during any stage of the bidding process. Complaints handling office is required to report on its findings to the Controller’s Office. Procurement process of the Commission is subject to annual audits by internal and independent external auditors.

172. Based on the findings of the risk assessment the overall procurement risk rating for AUC procurement is moderate.

173. Some of the identified risks and risk mitigation measures are provided in the following matrix:

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Table 6: AUC Matrix of Risk and Risk Mitigation Measures

Identified Risk Risk Mitigation Measures Responsible Body

Staff overloaded with Hire one additional qualified AUC procurement and contract procurement staff and one administration activities contract management staff

Procurement staff are not familiar Arrange for a training of the staff AUC/World Bank with the Procurement Regulations on the Procurement Regulations of the World Bank of the World Bank

Delays in procurement processing Establish performance indicators AUC in accordance with the timeline for processing of procurement established in the procurement activities and monitor the plan implementation of such standards

174. The procurement risk rating and respective thresholds for the Implementing Agencies in the various countries are shown below:

Ghana Prior Review Threshold in (US$ '000) Procurement Method s Thresholds (in US$'000) Goods, IT and non-consulting Shortlist of National Works Consultants services Consultants Single Engineering Goods, IT Source & Request for Request for Open Open Open Open & Systems+ Direct Quotation/ Quotation/ Consulting RISK RATING Works Firms Individuals Internationa National or Internationa National or constructio Non Con. Contract National National services l or ICB NCB l or ICB NCB n Serv Shopping Shopping supervision

SUBSTANTIAL ≥$10,000 ≥$2,000 ≥$1,000 ≥$300 ≥$50 ≥15000 <15000 ≤200 ≥3000 <3000 ≤100 <300 ≤500

Burkina Faso Prior Review Threshold in (US$ '000) Procurement Method s Thresholds (in US$'000) Goods, IT and non-consulting Shortlist of National Works Consultants services Consultants

Request Request Goods, IT Engineering Open Open for Open Open for Systems+ Consulting & RISK RATING Works Firms Individuals Internatio National Quotation/ Internatio National Quotation/ Non Con. services construction nal or ICB or NCB National nal or ICB or NCB National Serv supervision Shopping Shopping

SUBSTANTIAL ≥$10,000 ≥$2,000 ≥$1,000 ≥$300 ≥5000 <5000 ≤200 ≥500 <500 ≤100 <200 ≤400

Cabo Verde Prior Review Threshold in (US$ '000) Procurement Method s Thresholds (in US$'000) Goods, IT and non-consulting Shortlist of National Works Consultants services Consultants

SUBSTANTIAL ≥$10,000 ≥$2,000 ≥$1,000 ≥$300 ≥5000 <5000 ≤200 ≥500 <500 ≤100 <300 ≤300

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Côte d’Ivoire Prior Review Threshold in (US$ '000) Procurement Method s Thresholds (in US$'000) Goods, IT and non-consulting Shortlist of National Works Consultants services Consultants

SUBSTANTIAL ≥$10,000 ≥$2,000 ≥$1,000 ≥$300 ≥10000 <10000 ≤200 ≥1000 <1000 ≤100 <300 ≤500

Liberia

Sierra Leone Prior Review Threshold in (US$ '000) Procurement Method s Thresholds (in US$'000) Goods, IT and non-consulting Shortlist of National Works Consultants services Consultants Request Request Goods, IT Engineering Open Open for Open Open for RISK Systems+ Consulting & Works Firms Individuals Internatio National Quotation/ Internatio National Quotation/ RATING Non Con. services construction nal or ICB or NCB National nal or ICB or NCB National Serv supervision Shopping Shopping

HIGH ≥$5,000 ≥$1,500 ≥$500 ≥$200 ≥5,000 <5,000 ≤200 ≥500 <500 ≤100 <100 ≤200

Togo Prior Review Threshold in (US$ '000) Procurement Method s Thresholds (in US$'000) Goods, IT and non-consulting Shortlist of National Works Consultants services Consultants Request Request Goods, IT Engineering Open Open for Open Open for RISK Systems+ Consulting & Works Firms Individuals Internatio National Quotation/ Internatio National Quotation/ RATING Non Con. services construction nal or ICB or NCB National nal or ICB or NCB National Serv supervision Shopping Shopping

HIGH ≥$5,000 ≥$1,500 ≥$500 ≥$200 ≥5,000 <5,000 ≤200 ≥500 <500 ≤100 <100 ≤200

African Union Prior Review Threshold (in US$ ’000) Procurement Methods Thresholds (in US$ ‘000)

Consultants Works Goods, IT and Non- Shortlis consulting Services t of Nationa l Consult ants

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

RISK Works Goods, Firms Individuals Open Open RFQ Open Open RFQ Consult Engine RATING IT Internati Nation Interna Nation ing ering System + onal or al or t al or Service & Non-Con. ICB NCB or ICB NCB s Constr Serv. uction Super vision MODERATE ≥$15,000 ≥ $4,000 ≥$2,000 ≥ $400 ≥ 7,000 <7,000 ≤200 ≥1,000 <1,000 ≤200 ≤200 ≤300

175. Frequency of Procurement Supervision: In addition to the prior review supervision which will be carried out by the World Bank per each country’s World Bank Procurement Specialist, semi-annual supervision missions are recommended. Annual World Bank Procurement Post Review will be conducted in the respective countries by the World Banks’ Procurement Specialists. The sample size will be based on the procurement risk rating for the Implementing agencies in each country. The prior review procurements will be reviewed and cleared in STEP by the respective World Banks’ Procurement Specialists for the Implementing Agencies residing in the respect countries.

176. Summary of the Project Procurement Strategies for Development (PPSD). All PPSDs have been prepared. The PPSDs show that countries’ context in terms of bureaucracy, economic condition, currency stability, financial constraints, technology, and inadequate national market for high value and complex procurements, coupled with identified minor safeguards issues, the countries’ economic, procurement, and safeguards policies will impact the approach and response to the market and the execution of contracts. The capacities of the Implementing Agencies and the identified procurement risks will impact the procurement implementation. Thus, timely and adequate execution of the mitigations will help improve procurement implementation under the project. The studies and analysis will show that there are opportunities for both national and international firms under the project in each of the countries.

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 2: The Data for Policy Package

Type of data Objectives Example of data Population censuses and household surveys Population census Systematically collect information from Sociodemographic characteristics (gender, age, total population of country ethnicity) of entire population and dwelling Provide sampling frame for household characteristics surveys Household survey Measure demographic and socioeconomic Employment, health, income and expenditures, characteristics of population access to services Measure evolution of wellbeing Establishment censuses and enterprise surveys Census of firms Keep records of firms operating in country Firm identification number, name, legal status, and registrar of Provide sampling frame for business sector, size, address, contact information firms surveys Firm-level data for Measure production and evolution of Production, employment, costs national accounts economy and production statistics Enterprise survey Measure business environment Basic firm characteristics, productivity, costs, Measure firm performance innovation, trade, management practices, Benchmarking business environment (e.g., gender, corruption, crime, infrastructure) Agricultural censuses, surveys, and complementary tools to update census data Agricultural Keep records of farms and ranches in Land use and ownership, characteristics of holder, census country total area, crops, livestock Provide sampling frame for agricultural surveys Provide data for small administrative units Agricultural survey Measure agricultural production and Production practices, crop yields and productivity, performance of sector prices, costs Benchmarking Complementary Use new technology (weather stations, Soil conditions, forest and land use change, water tools to update satellite imagery, drones) to collect resources census or survey geospatial data data Price data Collect data on prices from businesses and Prices of basket of consumer goods and services services relating particular products to such as transportation, food, and medical care measuring cost of living and welfare Administrative Collect data for nonstatistical reasons to Social security registry, tax records, business data provide information for administrative or registry, trade data from customs, vital statistics, management purposes social policy beneficiary registry, education system Support evidence-based policy and statistics programs Provide transparent and accountable service delivery Big data Collect information using remote sensing Financial transactions, social media, satellite and telecommunication technologies images, Global Positioning System, cellphone

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 3A: Summary of Core Social and Economic Statistics in Sub-Saharan Africa

Country Overall System Household surveys since 2013 (number) World Census Statistical of agricultural (MR) Capacity National Poverty Demographic Multiple Labor surveys Index Accounts and Health Indicator force (MR) 2018 Survey Cluster survey Survey Angola 52.2 1993 1 1 0 0 2014 Benin 75.6 1993 1 1 1 1 2013 Botswana 50.0 1993 1 0 0 0 2015 2011 Burkina Faso 75.6 2008 1 2 0 2 2006-10 2006 Burundi 56.7 1993 1 1 0 0 2008 Cameroon 60.0 2008 1 1 1 0 2005 Cabo Verde 71.6 1993 1 0 1 0 2010 Central 35.6 1993 0 0 1 0 2003 African Republic Chad 50.0 1993 0 1 0 0 2009 Comoros 30.0 1993 1 0 0 0 2003 Congo, 52.2 1993 0 2 1 0 .. Democratic Republic Congo, 55.6 1968 0 0 1 0 2014/15 2007 Republic Côte d'Ivoire 70.0 1993 1 1 1 1 2014/15 2014 Equatorial 43.3 1993 0 0 0 0 2015 2015 Guinea Eritrea 31.1 N/A 0 0 0 0 .. Eswatini 58.9 2008 1 0 0 0 2012/13 2007 Ethiopia 70.0 1993 1 1 0 1 2007 Gabon 36.7 1993 1 1 0 0 2013 Gambia, The 68.9 2008 1 1 1 0 2011/12 2013 Ghana 71.1 2008 1 3 1 0 2010 Guinea 58.9 1993 0 2 2 0 2014 Guinea- 47.8 2008 0 0 1 1 2009 Bissau Kenya 55.6 2008 1 2 1 1 2009 Lesotho 72.2 1993 1 1 1 0 2009/10 2016 Liberia 56.7 1993 2 2 0 0 2008 Madagascar 56.7 1993 0 2 0 0 1993 Malawi 80.0 1993 1 4 1 0 2006/07 2008 Mali 61.1 1993 0 2 1 1 2009 Mauritania 65.6 2008 1 0 1 1 2013 Mauritius 75.6 2008 1 0 0 4 2014 2011 Mozambique 68.9 1993 1 2 0 0 2009/10 2007

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Namibia 64.4 1993 1 1 0 3 2013/14 2011 Niger 67.8 2008 0 1 0 1 2004-08 2012 Nigeria 68.9 2008 0 3 1 3 2006 Rwanda 78.9 1993 1 2 0 1 2008 2012 Sao Tome 70.0 1993 1 1 1 0 2011/12 2012 and Principe Senegal 85.6 2008 0 3 0 1 2013 2013 Seychelles 75.6 1993 0 0 0 0 2010 Sierra Leone 62.2 1993 0 2 1 1 2015 Somalia 30.0 1968 3 0 0 0 1987 South Africa 82.2 2008 1 0 0 4 2007 2011 South Sudan 37.8 2008 1 0 0 0 2008 Sudan 65.6 1968 1 0 1 0 2008 Tanzania 71.1 1993 1 3 0 1 2007/08 2012 Togo 72.2 1993 1 2 1 1 2011-14 2010 Uganda 74.4 2008 1 2 0 1 2008/09 2014 Zambia 62.2 2008 1 2 0 1 2010 Zimbabwe 66.7 1993 1 1 1 1 2012

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 3B. Summary of Core Social and Economic Statistics in Beneficiary Countries Burkina Sierra Cabo Verde Côte d'Ivoire Ghana Liberia Togo Observations Faso Leone 1.2. Household Based-Surveys 1.2.1. Household Surveys (HHS) Regular HHS Yes No Yes Yes No No No Existence of system of comparable HHS No No No Yes No No No with international standards Most recent HHS 2018 2015 2018 2017 2016 2018 2018 1.2.2. Labor Force Surveys (LFS) Regular LFS No Yes No No No No No Existence of system of comparable LFS No Yes No No No No No with international standards Most recent LFS 2018 2018 2018 2015 None 2016 2018 1.2.3. Population census Most recent Ongoing population census (2006 2010 2014 2010 2008 2015 2010 previous one) 1.3. Economic

Statistics 1.3.1. Enterprises Statistics Existence of Partial Partial Partial system of from Partial from from from comparable administr administrati No No No administrat administr enterprise surveys ative ve data ive data ative data data Most recent Establishm enterprise census 2016 2012 None 2013/14 ent census None 2017 - 2017 Most recent Establishm enterprise survey 2018 2017 2018 2015 ent survey 2019 2018 - 2018 1.3.2. Agriculture statistics Existence of a regular annual Yes No No No No No Yes survey Most recent AG No agr. census 2008 None 2015 2018 census in Liberia

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Most recent AG 2016 as survey componen t of Household 2019 None 2016 None None 2019 income and expenditur e survey 1.3.3. National Accounts (NA) SNA Used, 2008 or 2008 1993 1993 2008 1993 1993 1993 1993 Base year of NA 2014 2007 1996 2016 2016 1993 2015 1.4 consumer price index Coverage For SL, Price Three data for the islands Capital & CPI are covering 80 Urban Urban National Capital Main Urban collected in percent of Cities five markets the throughout population the country Base year 2008 2018 2008 2012 2005 2008 1.5 administrative data Existence of a comprehensive system of No No No No No No No administrative data in all key sectors 1.6 big data Use of big data No No No No No No No 1.7 data dissemination NSO has a website Yes Yes Yes Yes Yes Yes Yes NSS offers an integrated No No No No No No No platform to disseminate data NSO offers a smart system of No No No No No No No downloading data 1.8 institutional reforms and enhance human capital Existence of a Recently statistical Law in revised line with the UN Under and Under Under No No No principles of revision passed in revision revision Official statistics parliame nt

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 4: Statistical Capacity Index, Africa, 2018

0 10 20 30 40 50 60 70 80 90 Senegal South Africa Malawi Rwanda Benin Burkina Faso Mauritius Seychelles Mozambique Uganda Sao Tome and Principe Ethiopia Lesotho Togo Ghana Cabo Verde Tanzania Cote d'Ivoire Gambia, The Nigeria Niger Zimbabwe Mauritania Sudan Namibia Sub-Saharan Africa Sierra Leone Zambia Mali Cameroon Djibouti Eswatini Guinea Madagascar Burundi Liberia Congo, Rep. Kenya Botswana Angola Congo, Dem. Rep. Chad Guinea-Bissau Equatorial Guinea South Sudan

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 5: Planned Core Social and Economic Statistics in Project Countries, 2020-2029 Survey or Census 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029

Household survey Burkina Faso EHCVM II EHCVM III EHCVM IV Cabo Verde HIES HIES HIES Côte d’Ivoire EHCVMII EHCVMIII EHCVMIV Ghana GLSS8 GLSS9

Liberia HIES HIES HIES Sierra Leone SLIHS SLIHS Togo EHCVMII EHCVMIII EHCVMIV Economic survey Burkina Faso Census Survey Survey Survey Survey Cabo Verde Census Survey Survey Survey Survey Survey Survey Survey Survey Côte d’Ivoire Census Survey Survey Survey Survey IBES II IBES II IBES II (full Ghana IBES I (census) (economic (economic IBES II IBES I IBES II IBES II IBES II survey) survey) survey) Liberia Survey Census Survey Survey Census Sierra Leone Census Survey Survey Togo Census Survey Survey Survey Survey

Agricultural survey EPA (annual Agricultural Burkina Faso EPA EPA EPA EPA EPA EPA EPA EPA survey) census Agricultural Cabo Verde AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey Census Côte d’Ivoire AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey Agricultural Ghana AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey AGRISurvey Census Agricultural Liberia AGRISurvey AGRISurvey AGRISurvey Census

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Agricultural Sierra Leone AGRISurvey AGRISurvey AGRISurvey AGRISurvey Census Agricultural Agricultural Agricultural Agricultural Agricultural Agricultural Agricultural Agricultural Agricultural Togo Agricultural survey survey survey survey survey survey survey survey Census survey Population census Burkina Faso RGPH General Census of Cabo Verde Population and Housing Côte d’Ivoire RGPH5 Population and Ghana Housing Census National Population and Liberia HPC Housing Census Sierra Leone HPC HPC Togo RGPH5

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 6: Project Cost for Planned Core Social and Economic Statistics in Project Countries

Components, subcomponents and activities AU ECOWAS Burkina Cabo Côte Ghana Liberia Sierra Togo Grand Faso Verde d'Ivoire Leone Total 1 Regional Component: Harmonization, Data Collection, Quality Improvement, 2 6 51.5 11.5 50.8 135.91 25 24.5 27 334.21 Dissemination and Use of Core Social and Economic Statistics 1.1 Support implementation of the SHaSA2 initiative by the African Union, support production of 2 6 0 0 0 0 0 0 0 8 harmonized methodologies by the ECOWAS Commission, and improve data access at the regional level monitoring of SHaSA2 2 2 harmonization of methodologies 3.5 3.5 strengthen capacity of ECOWAS 2.5 2.5 1.2 Support household surveys at national level using harmonized 0 0 12.5 3.65 22.85 89.34 9.5 8.5 14 160.34 methodologies Poverty surveys (LSMS, Annual Household Exp Survey, Assets 2.5 1.6 7.85 12.1 2.5 3.5 4 34.05 Ownership Survey, Communal survey, etc.) baseline LFS + informal sector 2.5 0.9 2.5 1.4 0.7 2 10 call center 0.5 0.25 0.5 0.5 1.75 follow-up LFS 2 2 1.4 0.3 1.5 7.2 Census 2.5 10 72 6 5 5 100.5 DHS/MICS 2.5 0.9 2.44 1 6.84 1.3 Support core set of economic statistics at national level using 0 0 16 3.1 17.5 24.76 7.4 9 8 85.76 harmonized methodologies electronic DFS 1.5 1 1 3.5

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

enterprise censuses 4 0.1 4 7.82 1.4 1.5 3 21.82 enterprise surveys (including industry, commerce, service, 4 1.4 4 13.01 0.6 2 1 26.01 environment, tourism) ag census 4 3 7 ag surveys 0.9 5 2.19 1 4.5 13.59 ag survey improvement 1 1 fishery census 0.5 0.5 2008 SNA and rebase and satellite 1.5 0.2 1.5 1 1 2 7.2 accounts Informal trade for national accounts 1 0.82 0.4 2.22 Specific indices for NA 1 1 0.92 2.92 1.4 Support modernization of Consumer Price Index at national level using 0 0 0.8 0 0.5 1.44 0.5 1.5 0.5 5.24 harmonized methodologies CPI: improve coverage 0.8 0.5 1.04 0.5 0.5 3.34 CPI: update base year 0 1.5 1.5 CPI: upgrade software 0 0.4 0.4 Components, subcomponents and activities AU ECOWAS Burkina Cabo Côte Ghana Côte Sierra Togo Grand Faso Verde d'Ivoire d'Ivoire Leone Total 1.5 Support improvement of 0 0 11 2.3 2.85 9.44 2 5 0.5 33.09 administrative statistics admin data @ MDA / MACS 1 1.95 8.44 0.4 1 0.5 13.29 NSS data platforms 1.3 0.2 1 1.6 1 5.1 CHESS/Health statistics 2 0.3 3 5.3 livestock statistics 1.1 0.2 1.3 stats infra at MoAg 0.4 0.2 0.6 tech & stats infra at MoE 7.5 0 7.5 1.6 Increase use of big data 0 0 1 0.5 1 3.73 0 0 1 7.23 environmental data collection 0.5 0.25 0.3 2.53 0.5 4.08 poverty tracking with satellite/call 0.5 0.25 0.7 1.2 0.5 3.15 records 1.7 Improve data accessibility and 0 0 0.5 0.25 0.5 1.5 0.5 0.5 0.5 4.25

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

dissemination improve data dissemination 0.5 0.25 0.5 1.5 0.5 0.5 0.5 4.25 1.8 Institutional reforms and enhanced 0 0 9.7 1.7 5.6 5.7 5.1 0 2.5 30.3 human capital Institutional reforms 0.7 2 0.1 1 3.8 Formal academic training 5 0.6 3.4 1 10 On the job training and workshops in 2 0.5 4.7 1 8.2 data production On the job training and workshops in 2 1.7 2.5 1 0.6 0.5 8.3 the use of data and analytics 2 Country-Specific Component 0 0 6.5 2 1.2 11.09 3 3 1 27.79 Building rehabilitation, physical infrastructure and Statistical 2 2 infrastructure ICT, physical and statistical 6.5 2 1.2 9.09 3 1 0.75 23.54 infrastructure Strengthen statistical coordination 2 0.25 2.25 and quality assurance 3 Project Management and 0.5 1.5 2 1.5 2 3 2 2.5 2 17 Monitoring and Evaluation NSOs for program management 2 1.5 2 3 2 2.5 2 15 regional coordination 0.5 1.5 2 Grand Total 2.5 7.5 60 15 54 150 30 30 30 379

Project Components and Sub-Components Cost (US$ Millions) Component 1: Regional Component: Harmonization, Data Collection, Quality Improvement, Dissemination and Use of Core Social and 334.21 Economic Statistics Subcomponent 1.1. Support monitoring of SHaSA2 initiative by African Union; support production of harmonized methodologies and 8.00 improve management skills at ECOWAS Commission for all ECOWAS member states; improve access to data at regional level Subcomponent 1.2. Support household surveys at national level using harmonized methodologies 160.34 Subcomponent 1.3. Support core set of economic statistics at national level using harmonized methodologies 85.76 Subcomponent 1.4. Support modernization of Consumer Price Index at national level using harmonized methodologies 5.24

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

Subcomponent 1.5. Support improvement of administrative statistics 33.09 Subcomponent 1.6. Increase use of big data 7.23 Subcomponent 1.7. Improve data accessibility and dissemination 4.25 Subcomponent 1.8. Institutional reforms and enhanced human capital 30.30 Component 2: Country-Specific Component 27.79 Subcomponent 2.1. Burkina Faso: Modernize technological and statistical infrastructure 6.50 Subcomponent 2.2. Cabo Verde: Improve information and communications technology infrastructure 2.00 Subcomponent 2.3. Côte d’Ivoire : Modernize technological infrastructure 1.20 Subcomponent 2.4. Ghana: Modernize physical and statistical infrastructure 11.09 Subcomponent 2.5. Liberia: Improve physical and statistical infrastructure 3.00 Subcomponent 2.6. Sierra Leone : Rehabilitate Statistics Sierra Leone’s physical infrastructure 3.00 Subcomponent 2.7. Togo: Build capacity and modernize technological, statistical, and physical infrastructure 1.00 Component 3: Project Management and Monitoring and Evaluation 17.00 Grant Total 379 Note: SHaSA2, Strategy for Harmonization of Statistics in Africa; ECOWAS; LFS; labor force survey.

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

ANNEX 7: Modified Statistical Capacity Index Methodology

Modified statistical capacity index (SCI 2.0)

. = Score for statistical methodology+Score of data source+Score for periodicity and timeless 1. Statistical Methodology 𝐒𝐒𝐒𝐒𝐒𝐒 𝟐𝟐 𝟎𝟎 𝐬𝐬𝐬𝐬𝐬𝐬𝐬𝐬𝐬𝐬 3 Include Max. Indicators Score 1 Score 0 Weight in SCI score 2.0 1. National accounts base year Within last 10 years or annual chain linking Otherwise 1 10 Yes 2. Balance of payments manual in use Balance of Payments Manual, the fifth or sixth edition Otherwise 1 10 Yes 3. External debt reporting status Actual or preliminary Otherwise 1 0 No 4. Consumer Price Index base year Within last 10 years or annual chain linking Otherwise 1 10 Yes 5. Industrial production index Monthly or quarterly availability Otherwise 1 10 Yes 6. Import/export prices Monthly or quarterly availability Otherwise 1 10 Yes 7. Government finance accounting concept Consolidated central government accounts Otherwise 1 0 No 8. Enrolment reporting to UNESCO Annual or missed reporting only once in the last 4 years Otherwise 1 10 Yes 9. Vaccine reporting to WHO Nationally reported data on measles vaccine coverage consistent with WHO estimates for 4 years Otherwise 1 10 Yes 10. IMF’s Special Data Dissemination Standard Subscribed Otherwise 1 10 Yes Maximum total score is 80

2. Source Data

Include Score Max. Indicators Score 1 Score 0 Weight in SCI 1/2 score 2.0 1. Population census conducted within last 10 years 1 or more Otherwise 1 20 Yes 2. Agricultural census conducted within last 10 years 1 or more Otherwise 1 20 Yes 3. Number of poverty surveys conducted within last 10 years (IES, LSMS, etc.) 3 or more surveys 2 surveys Otherwise 1 20 Yes 4. Number of health surveys conducted within last 10 years (DHS, MICS, Priority survey, etc.) 3 or more surveys 2 surveys Otherwise 1 20 Yes 5. Completeness of vital registration system Complete Otherwise 1 0 No Maximum total score is 80

The World Bank Harmonizing and Improving Statistics in West Africa Project (P169265)

3. Periodicity and Timeliness Max. Include in Indicators Score 1 Score 2/3 Score 1/2 Score 1/3 Score 0 Weight score SCI 2.0 1. Periodicity of income Observed for at least 3 Observed for at least 2 Observed for at least 1 Not available/ 1 10 poverty indicator times within 10 years times within 10 years time within 10 years accessible Yes

2. Periodicity of child Observed for at least 3 Observed for at least 2 Observed for at least 1 Not available/ 1 malnutrition indicator times within 10 years times within 10 years time within 10 years accessible 10

Yes

National or international 3. Periodicity of child mortality Not available/ estimates available for 1 indicator accessible reference year 10

Yes 4. Periodicity of Immunization Annual within 5 year Not annual/ available/ 1 0 No indicator reference period accessible

National or international estimates available for Not available/ 5. HIV/AIDS indicator 1 0 No at least one year out of accessible the last 3 years

6. Periodicity of maternal Observed for at least 3 Observed for at least 2 Observed for at least 1 Not available/ 1 health indicator times within 10 years times within 10 years time within 10 years accessible 10

Yes

7. Periodicity of gender equal- Observed for at least 5 Observed for at least 3 Observed for 1 out of 5 Not available/ 1 ity in education indicator out of 5 latest years out of 5 latest years latest years accessible 10

Yes

Observed for at least 5 Observed for at least 3 Observed for 1 out of 5 Not available/ 8. Primary completion indicator 1 out of 5 latest years out of 5 latest years latest years accessible 10

Yes

Observed for 2 out of 6 Observed for 1 out of 6 Not available/ 9. Access to water indicator 1 latest years latest years accessible 10

Yes

10. Periodicity of GDP growth Observed for at least 6 Observed for at least 1 Not available/ Annual within 10 years 1 indicator times in 10 years time in 10 years accessible 10

Yes Maximum total score is 80