FOR OFFICIAL USE ONLY Report No: PAD3619 INTERNATIONAL BANK FOR RECONSTRUCTION AND DEVELOPMENT PROJECT APPRAISAL DOCUMENT ON A PROPOSED LOAN IN THE AMOUNT OF US$30 MILLION TO THE REPUBLIC OF INDIA FOR A NATIONAL PROGRAM FOR IMPROVING THE QUALITY OF STATISTICS IN INDIA February 19, 2020 Poverty and Equity Global Practice South Asia Region 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. The World Bank National Programme for Improving the Quality of Statistics in India (P169497) CURRENCY EQUIVALENTS (Exchange Rate Effective Feb 07, 2020) Currency Unit = Indian Rupee (INR) INR 71.40 = US$1 FISCAL YEAR April 1 – March 31 Regional Vice President: Hartwig Schafer Country Director: Junaid Kamal Ahmad Regional Director: Zoubida Kherous Allaoua Practice Manager: Benu Bidani Task Team Leader(s): Thomas Danielewitz, Rinku Murgai, Johannes Hoogeveen The World Bank National Programme for Improving the Quality of Statistics in India (P169497) ABBREVIATIONS AND ACRONYMS API Application Program Interface ARC Advance Release Calendar AS&FA Additional Secretary and Financial Advisor BCO Budget Controlling Officer BE Budget Estimate C&AG Comptroller & Auditor General CA Controller of Accounts CAP Coordination, Administration, and Policy CAPI Computer-Assisted Personal Interviewing CGA Controller General of Accounts COCSSO Conference of Central and State Statistical Organizations CPF Country Partnership Framework DDO Drawing and Disbursing Officer DIID Data Informatics and Innovation Division DLI Disbursement-linked Indicator DLR Disbursement-linked Result DPF Development Policy Financing DPR Detailed Project Report DQAD Data Quality Assurance Division EC Economic Census EDGE Evidence and Data for Gender Equality EEP Eligible Expenditure Program EIS Employee Information System ESCP Environmental and Social Commitment Plan ESD Economic Statistics Division FM Financial Management FOD Field Operations Division GDP Gross Domestic Product GeM Government e-Marketplace GFR General Financial Rules GHG Greenhouse Gas GIS Geographic Information System GoI Government of India GRM Grievance Redressal Mechanism GRS Grievance Redress Service GST Goods and Services Tax GSTN Goods and Services Tax Network HR Human Resource The World Bank National Programme for Improving the Quality of Statistics in India (P169497) IFD Integrated Finance Division IFMIS Integrated Financial Management Information System IFR Interim Financial Report IMF International Monetary Fund INE Spanish Statistical Office (Instituto Nacional de Estadistica) IPF Investment Project Financing IT Information Technology IVA Independent Verification Agent MCA Ministry of Corporate Affairs MDB Multilateral Development Bank MIS Management Information System MoF Ministry of Finance MOSPI Ministry of Statistics and Programme Implementation MoU Memorandum of Understanding NAD National Accounts Division NCA Natural Capital Account NIC National Informatics Centre NIIP National Integrated Information Platform NQAF National Quality Assurance Framework NSO National Statistical Office NSS National Sample Survey NSSTA National Statistical Systems Training Academy PAO Pay and Accounts Office PDO Project Development Objective PDPB Personal Data Protection Bill PFMS Public Financial Management System PIP Project Implementation Plan PMC Project Management Consultant PMU Project Management Unit PoC Proof of Concept PPP Purchasing Power Parity PPSD Project Procurement Strategy for Development PrAO Principal Accounts Office PSD Price Statistics Division QCBS Quality- and Cost-Based Selection RBI Reserve Bank of India RE Revised Estimate RFB Request for Bids RFP Request for Proposal RFQ Request for Quotation SBR Statistical Business Register The World Bank National Programme for Improving the Quality of Statistics in India (P169497) SDDS Special Data Dissemination Standards SDG Sustainable Development Goal SDRD Survey Design and Research Division SSD Social Statistics Division SSPU Statistical Strengthening Project Unit SSS Support for Statistical Strengthening STEP Systematic Tracking of Exchanges in Procurement ToR Terms of Reference TTL Task Team Leader UFS Urban Frame Survey UNSD United Nations Statistics Division The World Bank National Programme for Improving the Quality of Statistics in India (P169497) TABLE OF CONTENTS DATASHEET ........................................................................................................................... 1 I. STRATEGIC CONTEXT ...................................................................................................... 7 A. Country Context................................................................................................................................ 7 B. Sectoral and Institutional Context .................................................................................................... 8 C. Relevance to Higher Level Objectives............................................................................................. 11 II. PROJECT DESCRIPTION.................................................................................................. 12 A. Project Development Objective ..................................................................................................... 12 B. Project Components ....................................................................................................................... 13 C. Project Beneficiaries ....................................................................................................................... 19 D. Results Chain .................................................................................................................................. 21 E. Rationale for Bank Involvement and Role of Partners ................................................................... 22 F. Lessons Learned and Reflected in the Project Design .................................................................... 22 III. IMPLEMENTATION ARRANGEMENTS ............................................................................ 22 A. Institutional and Implementation Arrangements .......................................................................... 22 B. Results Monitoring and Evaluation Arrangements......................................................................... 23 C. Sustainability................................................................................................................................... 24 IV. PROJECT APPRAISAL SUMMARY ................................................................................... 24 A. Technical, Economic and Financial Analysis ................................................................................... 24 B. Fiduciary.......................................................................................................................................... 25 C. Legal Operational Policies ............................................................................................................... 28 D. Environmental and Social ............................................................................................................... 28 V. GRIEVANCE REDRESS SERVICES ..................................................................................... 29 VI. KEY RISKS ..................................................................................................................... 29 VII. RESULTS FRAMEWORK AND MONITORING ................................................................... 31 ANNEX 1: Implementation Arrangements and Support Plan .......................................... 58 ANNEX 2: Financial Management .................................................................................. 60 ANNEX 3: Procurement ................................................................................................. 68 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) DATASHEET BASIC INFORMATION BASIC_INFO_TABLE Country(ies) Project Name India National Program for Improving the Quality of Statistics in India Project ID Financing Instrument Environmental and Social Risk Classification Investment Project P169497 Low 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 19-Mar-2020 31-Mar-2025 Bank/IFC Collaboration No Proposed Development Objective(s) To improve the quality, efficiency, and user relevance of statistics produced by the India Ministry of Statistics and Programme Implementation. Components Component Name Cost (US$, millions) Page 1 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Improving Survey Data Quality 8.00 Making Most of Existing Data 21.00 Enhancing User Relevance of Published Statistics 0.80 Project Management Support 0.20 Organizations Borrower: Republic of India Implementing Agency: Ministry of Statistics and Programme Implementation PROJECT FINANCING DATA (US$, Millions) SUMMARY -NewFin1 Total Project Cost 60.00 Total Financing 60.00 of which IBRD/IDA 30.00 Financing Gap 0.00 DETAILS -NewFinEnh1 World Bank Group Financing International Bank for Reconstruction and Development (IBRD) 30.00 Non-World Bank Group Financing Counterpart Funding 30.00 Borrower/Recipient 30.00 Expected Disbursements (in US$, Millions) WB Fiscal Year 2021 2022 2023 2024 2025 Annual 4.00 6.00 7.00 6.50 6.50 Cumulative 4.00 10.00 17.00 23.50 30.00 Page 2 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 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 ⚫ Substantial 2. Macroeconomic ⚫ Low 3. Sector Strategies and Policies ⚫ Moderate 4. Technical Design of Project or Program ⚫ Substantial 5. Institutional Capacity for Implementation and Sustainability ⚫ Substantial 6. Fiduciary ⚫ Moderate 7. Environment and Social ⚫ Low 8. Stakeholders ⚫ Low 9. Other ⚫ Low 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 Page 3 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Environmental and Social Standards Relevance Given its Context at the Time of Appraisal E & S Standards Relevance Assessment and Management of Environmental and Social Risks and Impacts Relevant Stakeholder Engagement and Information Disclosure Relevant Labor and Working Conditions Relevant Resource Efficiency and Pollution Prevention and Management Relevant Community Health and Safety Not Currently Relevant Land Acquisition, Restrictions on Land Use and Involuntary Resettlement Not Currently Relevant Biodiversity Conservation and Sustainable Management of Living Natural Not Currently Relevant Resources Indigenous Peoples/Sub-Saharan African Historically Underserved Traditional Not Currently Relevant Local Communities Cultural Heritage Not Currently Relevant Financial Intermediaries Not Currently Relevant NOTE: For further information regarding the World Bank’s due diligence assessment of the project’s potential environmental and social risks and impacts, please refer to the Project’s Appraisal Environmental and Social Review Summary. Legal Covenants Name Recurrent Due Date Frequency Condition of Effectiveness No Before n.a. Effectiveness Description of Covenant Condition of Effectiveness: The Borrower has adopted the Project Implementation Plan (PIP), in form and substance satisfactory to the World Bank. Name Recurrent Due Date Frequency Page 4 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Project Implementation Arrangements Yes n.a. Throughout implementation Description of Covenant The Borrower shall (a) Maintain throughout the period of project implementation the National Statistical Office (NSO), led by the Chief Statistician of India; (b) Maintain throughout the period of project Implementation, a Project Management Unit (PMU), headed by a project director; (iii) Hire with its own resources and maintain throughout the period of implementation of the project, a Project Management Consultant (PMC), with staff and resources satisfactory to the World Bank, including a deputy project manager to provide support to the PMU; and (d) Ensure that the project is carried out in accordance with the arrangements and procedures set out in the PIP. Name Recurrent Due Date Frequency Safeguards Yes Various Throughout implementation Description of Covenant The Borrower shall (a) ensure that the project is carried out in accordance with the Environmental and Social Standards, (b) ensure that the project is carried out in accordance with the Environmental and Social Commitment Plan (ESCP), and (c) maintain and publicize the availability of a grievance mechanism, all in form and substance satisfactory to the World Bank. Name Recurrent Due Date Frequency Independent verification agent Yes Various Throughout implementation Description of Covenant The Borrower shall (a) appoint and thereafter maintain, at all times during the implementation of the project, an independent verification agent under terms of reference acceptable to the World Bank (independent verification agent) to verify the data and other evidence supporting the achievement of one or more selected DLIs and (b) ensure that the independent verification agent carries out verification and process(es) in accordance with the verification protocol described in the PIP and submits to the World Bank the corresponding verification reports in a timely manner and in form and substance satisfactory to the World Bank. Name Recurrent Due Date Frequency Page 5 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Other Undertakings Yes Various Throughout implementation Description of Covenant The Borrower shall (a) provide the necessary funds from its own resources for the hiring of the PMC to support the implementation of activities by the PMU during the entire duration of the project; (b) ensure that the project’s activities involving collection, storage, usage, and/or processing of personal data are carried out with due regard to the Borrower’s existing legal framework and appropriate international data protection and privacy standards and practices; and (c) in the event that, during the implementation of the project, the approval of any new legislation regarding personal data protection may have an impact on the activities financed by the project, ensure that a technical analysis of said impact is conducted and that the necessary recommendations and adjustments are implemented, as appropriate. Page 6 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) I. STRATEGIC CONTEXT A. Country Context 1. While Gross Domestic Product (GDP) growth has slowed in the past three years, India remains one of the fastest growing major emerging market economies. The current slowdown is primarily due to unresolved balance sheet issues in the banking and corporate sectors, compounded by stress in the non- banking segment of the financial sector. These issues have prevented a sustainable revival in private investment, and private consumption growth has also slowed in FY19/20. As a result, growth is expected to reach 5 percent in FY19/20. To address the slowdown, the Government has introduced various economy-wide and sectoral reforms (including a cut in corporate taxes, as well as steps to support the automobile and real estate sectors, non-banking financial companies, and medium and small enterprises). As a result, growth should pick up gradually from FY20/21 onward and revert toward potential. On the fiscal side, the general government deficit is estimated to have widened to above 6 percent of GDP in FY18/19, and it is expected to rise further in FY19/20, owing to recently adopted tax cuts and the impact of slower economic growth on tax proceeds. The current account balance is expected to improve in FY19/20, reflecting mostly a sizeable contraction in imports. Given this and robust capital inflows, India’s foreign exchange reserves rose to US$457.5 billion at end-December 2019 (equivalent to more than 11 months of imports). 2. Since the 2000s, India has made remarkable progress in reducing absolute poverty. Between FY11/12 and 2015, poverty declined from 21.6 percent to an estimated 13.4 percent at the international poverty line (US$1.90 per person per day in 2011 Purchasing Power Parity (PPP), continuing the earlier trend of rapid poverty reduction. Owing to robust economic growth, more than 90 million people escaped extreme poverty and improved their living standards during this period. Despite this success, poverty remains widespread. In 20151, 176 million Indians were living in extreme poverty, while 659 million—half the population—were below the higher poverty line commonly used for lower middle-income countries (US$3.20 per person per day in 2011 PPP). With the recent growth slowdown, the pace of poverty reduction may have moderated. 3. India is digitizing rapidly, and data are becoming ubiquitous. India’s digital push has led to 1.2 billion unique biometrics ID enrolments in the Aadhaar, more than a billion mobile connections, nearly half a billion internet users, and four-fifths of the adult population with bank accounts. India has become the world’s largest consumer of mobile data. Digital transactions are increasing at a rapid pace. The Ministry of Corporate Affairs (MCA) handles the registration of firms under the Companies Act through the MCA portal. More than 10 million businesses have been enrolled in the Goods and Services Tax Network (GSTN) enabling the tracking of sales tax and trade between registered firms under one platform. Initiatives under Digital India have transformed the e-government. Several state governments have started initiatives to enhance the analysis and use of data collected through administrative processes for policy action. 1World Bank. (2019). Poverty and Equity Brief: South Asia – India. October 2019. Accessed from: https://databank.worldbank.org/data/download/poverty/33EF03BB-9722-4AE2-ABC7-AA2972D68AFE/Global_POVEQ_IND.pdf Page 7 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 4. This rich digital footprint, rapidly advancing technology, and changes to the economic landscape have had profound impacts on expectations, opportunities, and risks for the statistical system. Policy makers and citizens expect more information, in real time, at a level of detail that is not always feasible through traditional surveys, in easily accessible formats, and all the while protecting privacy and confidentiality. Opportunities have grown as statistical products can potentially leverage government- wide and private sector data assets, deploy new tools to improve efficiency and quality assurance, and use advanced analytics to convert data to insights. These opportunities are not without risks—data may be nearly ubiquitous, but it is not uniformly of high quality, responsive to user needs, or trustworthy. B. Sectoral and Institutional Context 5. India’s statistical system used to be among the most advanced and innovative in the world. Professor Mahalanobis (1893–1972) founded the Indian Statistical Institute in 1931 and made myriad contributions to the field of statistics, particularly the design of large-scale sample surveys. He oversaw India’s first National Sample Survey (NSS) in 1950, establishing a practice that continues to the present— the fieldwork for the 78th round of the NSS has started in January 2020. India has an elaborate system of household and establishment surveys producing statistics that are comparable across time and space. On the World Bank’s composite Statistical Capacity Indicator which covers dimensions of methodology, source data, and periodicity, India’s system scores 91.1 (out of 100), ranking it high among developing countries. India subscribes to the Special Data Dissemination Standards of the International Monetary Fund (IMF), regularly updates its national accounts base year, has adopted the 2008 System of National Accounts, and has moved its system over time to meet international data standards in other areas. But the system is coming under pressure in several ways. 6. Demand is growing for real-time data to support policy decisions and track outcomes. NITI Aayog, the policy think tank of the Government of India (GoI), requires frequent and spatially disaggregated data to coordinate and monitor the Government’s development agenda; the Reserve Bank of India (RBI), in its role as regulatory agency and bank supervisor, requires increasingly specialized information for financial intermediation, which is seeing rapidly growing and increasingly complex transactions. Nationwide large-sample surveys that are conducted once every five years are important but insufficient to meet such demands. Sample sizes are not adequate for generating reliable data for administrative units below the state level, and traditional survey methodologies struggle to keep up with dynamism in the economy. Respondents—especially businesses or high-income households—are less willing to be interviewed or spend time completing survey questionnaires. Surveys will remain an important method of data collection in an economy with a large informal sector and with large variations in state administrative capacities. However, there are opportunities to both improve survey operations to make them more efficient and of higher quality, and for statistical outputs to rely on mixed-mode statistical production combining survey and non-survey data sources including administrative databases. 7. Statistical data are required at the state, district, and local levels to support effective policy and decision making. India is promoting cooperative and competitive federalism driven by a significant devolution of revenues and responsibilities to the states. The implementation capability of the public sector, particularly at the state and local level, has large and determinative effects on India’s development trajectory. There is now widespread recognition that if the public sector is to deliver better services, then citizens need agency and platforms to exert demand. For that, reliable, relevant, and regular information is needed. There are a variety of promising initiatives to make information available from the bottom up— Page 8 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) such as stronger Management Information Systems (MISs) of schemes that collect transaction-level data, compilation of available data on Aspirational Districts by the NITI Aayog,2 and efforts by nongovernmental organizations such as Pratham to make information on learning performance available in villages and districts. However, systematic data collection and reporting of key outcomes at the district level has not yet been realized; insufficient data availability is only more acute at the level of rural and urban local governments. 8. There are clearly recognized needs for improving data quality and expanding the range of statistical products. More gender-disaggregated statistics and gender-relevant statistics are needed to help policy makers and stakeholders design policies to close pressing gender gaps. Gender statistics must reflect the many areas where women and men may not enjoy the same opportunities (for example, the labor market) or where women’s and men’s lives may be affected in different ways. India still faces significant gender data gaps. Data are unavailable for 13 indicators in the minimum set of gender indicators as defined by the Evidence and Data for Gender Equality (EDGE) project, a joint initiative of the United Nations Statistics Division (UNSD) and UN Women. Key macroeconomic indicators, such as GDP, the Index of Industrial Production, and consumer price indexes are produced with a fixed release calendar. Questions have arisen recently after a new GDP series (with the revised base year 2011–12) and associated back series were released, as revised estimates did not seem consistent with other related macro-aggregates. The new series relies on improved data and methods, but there is insufficient clarity on the respective roles of the new base, new data, and improved methodology. Deciphering patterns of employment growth has proven difficult, with data from multiple (government and nongovernment) sources; for different periods, coverage, and sample sizes; with varying methodologies. Credible nationwide data on nonmonetary indicators of well-being are not frequently available. The most recent consumption survey for which data are available was conducted in 2011–12. New consumption data for welfare monitoring and update of poverty numbers will only be available in 2021 or 2022. 9. Statistical sources and methods must adapt to a fast-changing socioeconomic landscape. It is becoming increasingly difficult to incorporate the complexities of a globalized and digitized economy in headline economic indicators. Equally, there is lack of clarity on the accuracy of measuring the sharing economy in national accounts and employment statistics. Digitization also offers new possibilities. Information collected through administrative procedures can be used to produce statistics but requires new skills and different ways of working. Several national digital databases are hosted and overseen by the federal government (for example, GSTN and MCA213) enabling the production of subnational statistics without relying on state contributions. To address potential shortcomings and benefits from these opportunities, India must adjust its production processes to maximize the gains from administrative and other data sources, change the skill mix of its data producers, and adapt its institutional setup. The statistical system must evolve from collecting data through surveys mainly for government use to integrating data holdings across government, and sometimes the private sector; transforming that data into key indicators and analytics; and disseminating them to a broader and more diverse group of users 2 Launched in 2018, the ‘Transformation of Aspirational Districts’ program aims to quickly and effectively transform these districts. The broad contours of the program are convergence (of central and state schemes), collaboration (of central- and state-level ‘Prabhari’ officers and district collectors), and competition among districts driven by a mass movement. NITI Aayog, in partnership with the Government of Andhra Pradesh, has created a dashboard for monitoring the real-time progress of the districts. 3 Ministry of Corporate Affairs: the MCA21 database comprises all information companies are obliged to report under the Companies Act. Page 9 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) such as news media, academic researchers, businesses, fund managers, and civil society organizations, to name a few. 10. Strengthening India’s national statistical system requires stronger statistical offices at federal and state levels and an increased emphasis on quality control, coordination, and political commitment to the independence of the statistical authorities. A strong national statistics coordinator is of primary importance to make the decentralized system work. The national coordinator must be equipped with a mandate to set and enforce statistical standards such as definitions, classifications, and data transmission protocols as well as sufficient capacity to train and advise other statistics producers and to promote compliance. The national coordinator must also build and maintain adequate information and communication technology infrastructure to compile and process survey and non-survey data from different sources and to integrate this data to produce new statistical outputs in addition to making the statistical production process more efficient. Credible statistics also require that the agency in charge of the production of statistics is seen as impartial, professional, and free of political interference. Achieving an effective, impartial, and coherent system that serves both national and local data needs takes leadership, political will, and a plurality of investments at the national and subnational levels. 11. The Ministry of Statistics and Programme Implementation (MOSPI) is the main producer of official statistics in India. It has three major wings: The National Statistical Office (NSO), Program Implementation Wing, and Finance Wing. This project is limited to the NSO as it is the nodal agency for planning and facilitating the integrated development of the national statistical system in India. All statistical operations take place under the NSO, which comprises three main verticals, each headed by a director general reporting to the secretary, MOSPI, who is also the Chief Statistician of India. The three verticals are statistics; NSS; and Coordination, Administration, and Policy (CAP). The Statistics vertical plays a crucial role in responding to the emerging and evolving data needs across a wide range of socioeconomic-demographic issues and is primarily responsible for compilation of frameworks such as the India system of national accounts, monitoring and reporting on progress toward the Sustainable Development Goals (SDGs), Economic Censuses (ECs), and the indexes of industrial production and consumer prices, as well as maintaining and updating national classification frameworks for industries and products. It comprises five divisions: National Accounts Division (NAD), Economic Statistics Division (ESD), Price Statistics Division (PSD), Social Statistics Division (SSD), and the Data Informatics and Innovation Division (DIID). DIID is responsible for the information and communication technology related aspects of statistical production, including MOSPI’s website; data archiving and dissemination; cloud, server, and software management; and the design and rollout of the National Integrated Information Platform (NIIP), an integrated platform for data acquisition, processing, and dissemination. The second vertical, the NSS, is responsible for implementing the various NSS rounds such as consumption, employment, social expenditures, household debt and investment surveys, and Annual Survey of Industries. The NSS is also responsible for maintaining and updating sampling frames, questionnaire design, fieldwork organization, and survey data collection. It comprises four divisions: the Survey Design and Research Division (SDRD), Data Quality Assurance Division (DQAD), Field Operations Division (FOD), and Survey Coordination Division. The third vertical, CAP, is primarily responsible for all cross-cutting activities which requires coordination among and within various internal and external stakeholders including human resource (HR) management, administration, training, management of the statistical service cadre, and capacity building. It is also the nodal agency for managing the capacity development scheme of the ministry including the Support for Statistical Strengthening (SSS) scheme for states. Furthermore, while the project activities are spread across the three verticals of NSO, the Project Monitoring Unit for this project is housed under CAP. Page 10 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 12. MOSPI is mandated to provide leadership and coordination of the national statistical system. A National Statistical Commission (NSC) has been established as the main advisory body. In 2000, the GoI launched a commission, chaired by Dr. C. Rangarajan, to conduct a comprehensive review of the statistical system. Following the review, the GoI initiated several reforms to improve the operational efficiency of the statistical production hubs at the national and state levels and to improve coordination between the center and states. The NSC was established in 2005 with the goal of being the apex advisory body on statistical matters, and the Collection of Statistics Act was passed in 2008. MOSPI was tasked with establishing standards, norms, and benchmarks for key statistical activities and transferring technical and financial resources from the center to states. A National Statistical Systems Training Academy (NSSTA) was set up as part of MOSPI to provide trainings to statistical personnel. The Conference of Central and State Statistical Organizations (COCSSO) was revived to strengthen institutional coordination of statistical activities between MOSPI, other central ministries, and state statistical organizations. At the national level, the system benefits from a cadre of highly educated and well-trained statistical professionals collectively known as the Indian Statistical Service. C. Relevance to Higher Level Objectives 13. To respond to growing demand for more timely, relevant, and high-quality statistics, official statistical producers led by MOSPI need to modernize and reform. In June 2018, MOSPI hosted a two- day conference— ‘Data for a new India’—that provided a forum for exchange between Indian policy makers and current and former leaders of statistical offices in Australia, Canada, Singapore, and the United Kingdom. Shortly afterward, the GoI submitted a formal request for World Bank support to assist MOSPI in its modernization efforts. Subsequently, MOSPI prepared a five-year vision document (2019– 2024), aiming to enhance the efficiency, user responsiveness, and robustness of national statistical system and create capacities for real-time monitoring of critical parameters of the economy. The GoI has requested World Bank financial support of US$250 million to support the modernization agenda, of which this project is the first step. 14. The proposed project is a first step to set India, particularly MOSPI, on a path toward a modernized statistical system. In addition to this US$30 million Investment Project Financing (IPF) with disbursement-linked indicators (DLIs), a series of Development Policy Financing (DPF) operations (US$220 million) to support to policy reforms to strengthen the enabling environment is being discussed. Support from the proposed project focuses on promoting ongoing technological modernizations including use of Computer-Assisted Personal Interviewing (CAPI) for survey data collection and establishment of an integrated data platform, which in turn catalyze data integration and metadata-driven statistical production approaches and enhance quality control and dissemination. This project will also finance data innovation, training, and capacity building. A complementary series of DPF(s) to facilitate institutional and governance reforms and to strengthen state-level statistics through a revamped SSS scheme is also being discussed. 15. The proposed project is aligned with the World Bank Group’s Country Partnership Framework (CPF) for India for FY18–22 discussed by the Board on September 20, 2018 (Report No. 126667-IN, July 25, 2018). The objectives of the CPF are to be achieved through four approaches one of which is ‘strengthening public sector institutions. The quality of statistical systems is highlighted as a key indicator of CPF impact in this area. The success of this project will yield benefits through a strengthening of evidence for decision making inside and outside of the Government in addition to contributing to the Page 11 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) outcome of the CPF. This operation complements other projects in the India portfolio that focus on strengthening data systems in their respective domains by improving a shared national data infrastructure and enabling stronger coordination across the system. Complementary engagements are ongoing in the context of state partnerships, including statistical components in the development policy operations at the state level. 16. The project will leverage the ‘Lighthouse India’ initiative, which aims to create, curate, and disseminate knowledge and know-how generated within the World Bank Group program and India more broadly. This includes identifying states, including some low-income states, and using these states as learning centers—or lighthouse states—for others. Good practices among states in areas supported by the project will be shared through existing coordination mechanisms, and down the line, through the SSS scheme that is planned to be revamped to facilitate state innovation and greater vertical integration. This approach recognizes that statistics is on the concurrent list of the Indian constitution, and the heterogeneity in capacities, approaches, and outcomes provide an opportunity for sharing experiences and lessons across states. 17. The project contributes to closing the gender gap in statistics and to improved monitoring of climate change. The World Bank Group Gender Strategy document for FY16–23 calls for improved country-level diagnostics on gender gaps in Systematic Country Diagnostics and CPFs 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 country-level and regional-level data is deemed essential, and this project responds to this need by supporting the production of gender statistics which were previously unavailable. The same holds for data relevant to informing environmental and climate policies as this project will ensure the production of ecosystem and natural capital accounts. II. PROJECT DESCRIPTION A. Project Development Objective PDO Statement 18. To improve the quality, efficiency, and user relevance of statistics produced by the India Ministry of Statistics and Program Implementation. PDO Level Indicators 19. Progress toward the Project Development Objective (PDO) will be measured by the following indicators: • PDO indicator 1: NSO core surveys released according to the adopted Advance Release Calendar • PDO indicator 2: Share of core surveys using real-time supervision • PDO indicator 3: Indicators released quarterly from the National Factsheet • PDO indicator 4: Legacy surveys available for use in the online tabulation tool Page 12 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) B. Project Components 20. In line with the objectives defined in the PDO, the project comprises four components: (1) Improving Survey Data Quality, (2) Making Most of Existing Data, (3) Enhancing User Relevance of Published Statistics, and (4) Project Management Support. Integrated in these components are three major initiatives initiated by MOSPI which each have the potential to catalyze statistical modernization. The first initiative is the development of a multimodal data capture platform, which transforms survey data collection from paper-based to computer-assisted. The second is the establishment of the NIIP as an integrated data warehouse with data ingestion, processing, quality control, and dissemination capabilities. The third is the development of a statistical business register based on the 7th EC for which data collection is ongoing. A detailed description of activities supported by this project is as follows: 21. Component 1: Improving Survey Data Quality (estimated component cost US$8 million, DLIs valued at US$12.925 million). Activities financed under this component include the following: a) improving survey data quality, through inter-alia: reducing non-sampling error; shortening delays between field data collection and the presentation of results; and establishing pre-agreed timetable for release of data and reports; b) assessing and improving survey methodologies; carrying out studies and engaging expert advice to ensure survey data quality and best international practices; c) performing analyses on impact of the transition from paper-based schedules to CAPI questionnaires; implementing effective ways to use paradata for quality control and ways to improve collection of specific data such as consumption information; d) providing appropriate equipment including hardware (laptops, tablets and software) needed to make the transition to CAPI; and e) facilitating organizational restructuring and developing an advance release calendar, workshops, training, and consultations; and developing an e- learning course for investigators. 22. Improving survey data quality requires efforts in several dimensions. Non-sampling error must be reduced, and methodologies reviewed to ensure that the data collected are reliable. The delay between field data collection and the release of results should be shortened to ensure that statistics are timely. In addition, data and reports should be released in accordance with a pre-agreed timetable, to ensure that the production of statistics is predictable. The NSS in MOSPI has a long history in survey data collection. A well-defined program of household surveys exists comprising regulars such as the five-yearly consumption survey, the annual survey of industries, and the quarterly labor force survey, among others, as well as ad hoc surveys such as the time use survey and informal sector survey. Besides these surveys, the NSS collects data on rural and urban prices and plays a significant role in the improvement of crop statistics through supervision of the area enumeration and crop estimation surveys of the state agencies. It also maintains a frame of urban area units for use in sample surveys in urban areas. 23. The NSS has four divisions: SDRD is responsible for technical planning of surveys, formulation of concepts and definitions, sampling design, designing of inquiry schedules, drawing up of tabulation plan, and analysis and presentation of survey results; the FOD, with headquarters in Delhi and a network of six zonal offices, 52 regional offices, and 117 subregional offices spread throughout the country, is responsible for the collection of primary data for the surveys undertaken by the NSS. The DQAD has its headquarters at Kolkata and has five Regional Centers; the DQAD is responsible for sample selection, software development, processing, validation, and tabulation of the data collected through surveys. The Survey Coordination Division, finally, coordinates all the activities of different divisions of the NSS. It also Page 13 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) brings out the biannual journal of the NSS, titled ‘Sarvekshana’, and organizes national seminars on the results of various socioeconomic surveys undertaken by the NSS. 24. The NSS introduced CAPI in selected surveys using off-the-shelf software that is not always capable of meeting specific needs of the NSS. Informed by this, MOSPI decided to develop a customized CAPI platform which would gradually be rolled out to all core surveys implemented by the NSS, including the state samples. This shift will have profound implications for survey design and enumerator training. The changes are primarily related to a shift from schedules to questionnaires and implementation through tablets instead of paper forms. Supervision activities will also be positively affected as supervisors will be able to use para-data to monitor field activities. Data processing can now be done in parallel with data collection, which should cut down on the time lag between fieldwork and data release. A full transition to CAPI is expected to improve data quality because enumerators can be better supervised. Enumerators will be better trained due to the introduction of online certification courses and will have more information at their disposal such as training videos. Realizing these benefits requires organizational restructuring as workflows and tasks will change. MOSPI has already initiated commissioning the development of custom-built CAPI software, a multiyear, multimillion-dollar project. The project builds on this major initiative of the ministry by investing in activities that will help create an enabling environment for the technology to succeed and produce expected results. 25. Investments under this component are expected to achieve the DLIs listed in table 1. Table 1. DLIs under Component 1 IBRD Allocation DLI (US$, millions) DLI#1: Average time lag between end of fieldwork and public release of core survey data 6.000 DLI#2: Survey-related methodological studies completed and published on MOSPI website 2.000 DLI#3: NSO core surveys released according to the adopted Advance Release Calendar 4.925 Component 1 total 12.925 26. Component 2: Making Most of Existing Data (estimated component cost US$21 million, DLIs valued at US$13.5 million). Activities financed under this component include the following: a) strengthening the implementation of the NIIP to facilitate: (i) data acquisition, (ii) data processing, and (iii) archiving and dissemination, through, inter-alia: facilitating the onboarding of data into the NIIP and promoting attention to data quality through the development and application of a National Quality Assurance Framework (NQAF); creating a statistical business register; strengthening data quality and data innovation, carrying out business reengineering activities; and introducing an integrated software for the production of national accounts; b) carrying out training and capacity building activities to enable the implementation of the NIIP; and c) releasing periodic factsheets of the Indian economy (containing a list of 100 critical economic indicators); producing ecosystem and natural capital accounts and closing the data gaps with respect to SDG and EDGE (gender); and stimulating the use of new data. 27. Modern statistical offices rely increasingly on administratively collected information for the generation of statistics. The nature of these data is such that information is often incomplete and not fully up-to-date, while the definitions used reflect the primary use of the data and not necessarily statistical concepts. Administrative data can therefore rarely be used directly and need to be processed, Page 14 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) transformed, quality-checked, and triangulated with data from other sources, and missing values may need to be imputed. Modern statistical offices have invested a great deal of time and resources in reengineering their production processes, shifting away from an emphasis on primary data collection4 and moving toward automated production systems using administrative data sources. This requires enhanced standardization and documentation of concepts and definitions. This has resulted in two widely referenced models for statistical production: The Generic Statistical Business Production Model and Generic Statistical Information Model.5 28. To make MOSPI more relevant and to make the most of existing information, it has to • Reengineer statistical processes, especially data processing aspects; • Enhance the national data infrastructure and data sharing agreements to facilitate data integration across ministries and between the center and the states; • Create an adaptive organization with flexible structures and enhanced resources to meet new technological challenges and data demands; • Deepen the capabilities and resources of statisticians and allied professionals to meet new, higher standards expected for all statistical outputs; • Add value to existing statistical outputs with deeper analysis and broader dissemination; and • Develop new statistical products and services for specific issues that policy makers, researchers, businesses, and people care about. 29. With the development of the NIIP, MOSPI makes an important step toward the routine use of administrative data for statistical production and the reliance on metadata-driven statistical production approaches. The NIIP is an all-in-one platform intended to facilitate data (a) acquisition, (b) processing, and (c) archiving and dissemination. Data for acquisition can come from MOSPI’s own survey program or from administrative sources, preferably through Application Program Interface (APIs). Data processing includes all the steps from raw data to publishable statistics. Processing in statistical offices requires careful definitions of roles and responsibilities to assure that data transformations are fully recorded and accounted for. Doing so requires reliance on metadata systems which define the contents of each statistic and the various processing steps needed to go from raw material to final product, including who is permitted to make which changes. The transition from a vertically integrated ‘stove pipe’ production approach whereby each statistical production process is managed in parallel from end to end to horizontally integrated systems organized according to function involves elaborate, complex business process reengineering. The introduction of the NIIP data processing modules will give impetus to this transition. The NIIP will also act as data archive and dissemination platform, incorporating existing dissemination platforms such as the micro-data library run by the NSO but enhancing the user experience by offering customized mapping or tabulation facilities. 4In some countries which put less confidence in administrative data systems, like the United States, surveys remain important. 5The Modernization Maturity Model developed under the high-level group project on Implementing ModernStats is gaining in popularity too: https://statswiki.unece.org/pages/viewpage.action?pageId=129172266. Page 15 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 30. While the project does not directly finance the NIIP, which MOSPI commissioned in late 2019 using government resources directly, it catalyzes the implementation of NIIP. DLIs facilitate the onboarding of data into the NIIP and promote attention to data quality through the development and application of a National Quality Assurance Framework (NQAF) to be applied to data ingested into and disseminated by the NIIP6 such as SDG indicators and the quarterly produced indicators of the national indicator framework which monitor the economy. The project will provide support and capacity building at the state level to compile data for SDG indicators and State Indicator Frameworks. 31. DLIs formulated around the creation of a dynamic business register support the business reengineering case as they ensure that a dynamic business register is created out of the 7th EC by ingesting data from MCA21, Goods and Services Tax (GST), and state registers. The successful ingestion of such data is furthermore supported by DLIs on data quality. Important issues to resolve include investigating the completeness of MCA21 data, using GST transactional data with firm definitions that may be different from the statistical definitions used for the business register. The project will support strengthening of state business registers in a small number of states with the goal of developing scalable methods that can be applied throughout the country. 32. Business reengineering is also supported through DLIs on the introduction of an integrated software to produce national accounts. The introduction of such software ensures that what presently exists in 14 different silos (basically stand-alone Excel sheets) becomes one streamlined production process. Introducing this successfully will require not only training and capacity building—partnering with advanced statistical agencies will play an important role here—but also the re-definition of roles and responsibilities of staff working in the NAD. 33. Data innovation and ingestion of data from other agencies do not remain limited to the creation of a business register. DLIs formulated around the periodic release of the factsheet of the Indian economy, which is a compilation of 100 critical economic indicators; the production of ecosystem and natural capital accounts; and the closing data gaps with respect to SDGs and gender EDGE7 will stimulate the use of new data, often obtained from administrative data sources and at times collected through special surveys. 6 Much like the Generic National Quality Assurance Framework developed by the United Nations, the Indian NQAF will need to offer a template which is sufficiently flexible to permit sector-specific circumstances to be considered when applying the framework template to data produced by different entities. 7 The project will work toward full compliance with the minimum set of gender indicators as defined by the EDGE project, a joint initiative of the UNSD and UN Women that seeks to improve the integration of gender issues into the regular production of official statistics for better, evidence-based policies. Page 16 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Box 1: Statistics and Climate Change Climate change is an integral part of India’s development narrative. As noted in the India SCD, India’s efforts to reduce greenhouse gas emissions will have global implications: global damages from climate change will be much greater if India does not meet its greenhouse gas reduction targets. India is also highly vulnerable to the impacts of climate change. India is already vulnerable to climate risks – ranking 29 out of 191 countries in the 2019 Informed Risk Index 2019. The major climate risks are from flooding, drought, and cyclones and climate change is expected to exacerbate these risks. In its Nationally Determined Contributions (NDC), India has committed to ambitious goals to reduce greenhouse gases and to make its economy less vulnerable to climate impacts. India has plans to transform its economy and reduce emissions intensity of its GDP by 33 percent from 2005 levels by 2030. In addition, India is committed creating additional carbon sinks of 2.5-3 billion tons of CO2 equivalent through additional forest and tree cover. To reduce vulnerability, India plans to enhance investments in development programs to reduce vulnerability in sectors particularly agriculture, water resources, coastal economies, and health. The effectiveness of India’s climate mitigation and adaptation policies will depend in part on availability of data to inform these policies. The System of Environmental and Economic Accounts: Central Framework and Ecosystems Accounts can produce the needed data. The System of National Accounts (SNA2008), which India currently follows, does not provide sufficient information on natural assets such as forests and water to support policy making and to track progress of programs and initiatives. Many non-marketed services from forests are either omitted or wrongly attributed to other sectors of the economy. Similarly, SNA2008 does not track emissions – be it greenhouse gas emissions or pollutants that lead to air pollution – limiting effectiveness of policy decisions. With support in the form of technical assistance, training, and data collection from the project, MOSPI will develop a comprehensive set of environmental accounts to support data-informed natural resource policies and programs, including on climate change mitigation and adaptation. For example, the Energy Account will inform, and track progress of India’s renewable energy policies and residual accounts will produce information on greenhouse gas emissions. The residual accounts offer the power of the National Accounts analytical framework and will help elucidate the flows of GHG from both the producer and consumer perspectives. This will support carbon policies (such as carbon markets and prices) and help target emissions reduction. Forest Accounts will enable tracking of carbon storage and sequestration potential of forests in India; Urban Accounts would help understand what is done in cities to mitigate the effects of climate change, for example with measuring the impact of trees on the cooling of so-called urban heat islands; Coastal/Marine Ecosystems Accounts would deepen the understanding of the impact of ocean rise and increased water temperature in coastal environments, and inform policies to adapt to climate change A stated goal of the accounting project is to create the data required to report back to the many international conventions that India is signatory to, including the UNFCC. The Ministry of Environment, Forests and Climate Change is a close partner in the accounting project to ensure that information will be available to inform policies related to climate change adaptation and mitigation. Page 17 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 34. Investments under this component are expected to achieve the DLIs listed in table 2. Table 2. DLIs under Component 2 IBRD Allocation DLI (US$, millions) DLI#4: Statistical business register updated with information from states 9.00 DLI#5: National Factsheet indicators assessed using National Quality Assurance Framework 2.50 DLI#6: Indicators released quarterly from National Factsheet 1.25 DLI#7: Beta statistics released 0.75 Component 2 total 13.50 35. Component 3: Enhancing User Relevance of Published Statistics (estimated component cost US$0.8 million, DLIs valued at US$3.5 million). Activities financed under this component include the following: a) introducing innovative ways of disseminating data such as online mapping and tabulation tools and strengthening user-producer interactions during National Statistics Days; b) promoting data advocacy through capacity building, training, data visualization, social media presence; and c) providing necessary hardware and software (for maps and interactive tables) and software development. 36. Modern statistical offices produce core statistics relevant for monitoring key socioeconomic trends, such as GDP, inflation, or employment, and thematic material relevant to inform critical debates in society. As such, one observes less reporting on, for example, results from a recently completed survey and more reporting on thematic issues pulling together information from surveys and other data sources. DLIs will disburse against the introduction of online mapping and tabulation tools and the intensification of user-producer interactions. 37. Investments under this component are expected to achieve the DLIs listed in table 3. Table 3. DLIs under Component 3 IBRD Allocation DLI (US$, millions) DLI#8: Number of legacy surveys available for use in the online tabulation tool 1.5 DLI#9: Number of layers accessible through online mapping tool (incl. through APIs) 2.0 Component 3 total 3.5 38. Component 4: Project Management Support (estimated component cost US$0.2 million). Activities financed under this component will include, inter-alia: (i) strengthening the Project Management Unit (PMU), housed under NSO, MOSPI in the day to day management of implementation of Project activities; (ii) setting up a monitoring and evaluation (M&E) system; (iii) overseeing compliance with fiduciary obligations; (iv) coordination with all relevant divisions within MOSPI; and (v) carrying out capacity building activities for MOSPI staff (but excluding the hiring of PMC). 39. Project cost. The total project cost is US$60 million, out of which the World Bank is funding US$30 million and the remaining US$30 million is being borne by the GoI as counterpart funding. Figure 1 provides an overview of the project cost by activity, year, and divisions. The Eligible Expenditure Program (EEPs) consists of project-related investments (goods, non-consulting services, consulting services, Page 18 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) training, and operating costs) and part salaries. For more details on the DLI costing, EEPs, and so on, please see annex 2: Financial Management. 40. Project closing date. The loan closing date is March 31, 2025. C. Project Beneficiaries 41. The primary project beneficiary is MOSPI. This ministry is at the heart of the national statistical system, and by enhancing its capacity, the entire statistical system is put on a more solid footing. Indirect project beneficiaries are data users, decision makers, private sector, and citizens who will benefit from statistics that are more relevant and readily accessible. Page 19 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Figure 1. Distribution of Estimated Cost by Type of Expenditure, Year, and Division Estimated Cost by Type of Expenditure Year-wise Distribution of Estimated Cost by (In INR, crores) Type of Expenditure (In INR, crores) 1% 1% 3% 100 1% 6% 90 80 5% 70 5% 60 43% 50 9% 40 30 20 12% 10 14% 0 FY 20- FY 21- FY 22- FY 23- FY 24- 21 22 23 24 25 Division-wise Estimated Cost by Type of Expenditure (In INR, crores) SSD 28% FOD 19% DIID 18% Salaries* 14% PMU 7% ESD 6 SDRD 3% % DQAD 3% NAD 1% NSSTA 1% 0 20 40 60 80 100 120 140 Consultants Hardware & software Studies & Surveys PMC Capacity Building & E-Course Development Advocacy Workshops, Seminars & Conferences Innovation Funds % share of Operating Cost Travel estimated project Salaries* cost Note: *Please see annex 2 for more details regarding salaries. Page 20 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) D. Results Chain Page 21 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) E. Rationale for Bank Involvement and Role of Partners 42. Through its global engagement and multiple country engagements in statistical capacity building, the World Bank brings international expertise and experience to the challenge of modernizing national statistical systems. This expertise is critical to the design of the reform program at MOSPI, which is supported by this IPF. It is also important to support the coalition of high-level decision makers who champion statistical reform and to promote institutional reforms to strengthen statistical governance, supported through associated statistics DPF at the national level and statistical components in state partnership DPF engagements. 43. The project partners with the Department for International Development and the Office of National Statistics in the United Kingdom with the goal of setting up a durable mutual engagement aimed at knowledge exchange in the areas of statistical governance, use of administrative data in statistics production, user orientation, quality assurance for both survey and administrative data, data innovation, and environmental accounting. An initial visit to the Office of National Statistics is planned for April 2020. F. Lessons Learned and Reflected in the Project Design 44. Previous World Bank efforts to strengthen statistical capacity through a single-tranche, stand-alone Development Policy Finance operation in 2010–11 had limited success. The operation succeeded in setting up a structure for increased center-state cooperation and support, the SSS scheme, and in setting and documenting standards for certain statistical products. It also ushered in new regulations for data collection to operationalize the Data Collection Act of 2008. However, it failed in increasing the operational efficiency of the statistical system and in bringing about sustainable improvements in state capacity to produce statistics. An Independent Evaluation Group review of this operation rated project outcomes as moderately unsatisfactory; a more recent independent review commissioned by MOSPI suggests that “a lot of ground is to be covered in developing statistical capacity in the country especially at the state, district and local level.”8 This project design is informed by these reviews. Key lessons reflected in the design of this operation are that strengthening a complex statistical system like that in India requires a long-term engagement and multiple instruments to address issues related to capacity at the national and state levels. A combination of investment lending and development policy lending at the national and state levels will assure a longer term and more consistent engagement and will allow addressing statistical modernization from the capacity, state, and policy angles. III. IMPLEMENTATION ARRANGEMENTS A. Institutional and Implementation Arrangements 45. MOSPI is the implementing agency through its statistics wing, also referred to as the National Statistical Office (NSO). The NSO is led by the secretary, MOSPI, who also serves as the Chief Statistician of India. Within the NSO, a PMU has been created under the CAP vertical which is responsible for oversight over the day-to-day implementation of the project. The PMU for this project is supported by a PMC procured following national rules. In addition to providing dedicated consultants for the project, the PMC will support the implementation of the NIIP, which is critical to the success of the project and will help ensure better integration and synergy among 8National Institute of Financial Management (NIFM). 2017. Evaluation Report on Capacity Development Scheme of Ministry of Statistics & Programme Implementation. Page 22 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) complementary activities under this project such as quality control, data innovation, and introduction of Multi- Modal Data Capture (MMDC) platform. 46. The PMU will be headed by a project director and comprise MOSPI staff responsible for overseeing and facilitating project implementation. The PMC will provide support to the PMU to carry out project-related tasks. The PMU will be adequately staffed, including a deputy project manager (main responsibilities include project monitoring; strategic feedback on project implementation to the project director; and managing of the innovation activities such as call for proposals, selection, procurement, progress monitoring, support for grievance redress, preparation of progress reports, and the preparation of annual implementation plans and strategies for achieving the DLIs and results identified. A change management specialist and a strategy specialist will be included in the PMC to facilitate MOSPI’s business reengineering process, and associated communication, research, and capacity building, and various consultants and junior associates to facilitate project implementation within the various divisions. Other PMC staff, including those responsible for procurement and financial management (FM), will also have joint responsibilities for the NIIP and project activities. 47. As detailed under the description of project components, project activities will be implemented in each of the three verticals of MOSPI: the NSS, Statistics, and CAP. Divisions under each of the verticals will be responsible for implementing a set of activities and achieving associated results under the overall guidance and oversight of the PMU. B. Results Monitoring and Evaluation Arrangements 48. Realistic, specific, time-bound, actionable, and measurable targets have been set for the key performance indicators, the DLIs, and the intermediate outcome indicators, in discussion with stakeholders in MOSPI. To conform to the requirements for incorporating beneficiary feedback into the project, consultations with data users will be held regularly. User consultations are part and parcel of routine statistical activities, but specific opportunities for user-producer interaction will be facilitated through the annual celebration of Statistics Day and the COCSSO, among others. To ensure compliance with the gender tag, the project will work toward full compliance with the minimum set of gender indicators as defined by the EDGE project, a joint initiative of the UNSD and UN Women that seeks to improve the integration of gender issues into the regular production of official statistics for better, evidence-based policies.9 To contribute to the World Bank’s climate commitments, the project invests in the generation of NCAs for water, air, and land. 49. The PMU, supported by the PMC, will be responsible for carrying out project monitoring activities. These include (a) conducting periodic project progress reviews, (b) preparing and disseminating project progress reports (including reporting on the fiduciary and safeguards requirements of the project), (c) reporting on DLI achievements, and (d) preparing other studies, evaluations, and reports. 50. Verification of DLI achievements will be carried out on time, according to agreed protocols, and in alignment with the disbursement cycle. MOSPI will appoint an independent verification agent (IVA) to verify the data and other evidence supporting the achievement of one or more selected DLIs and recommend corresponding payments to be made. MOSPI will ensure that the IVA carries out verification and process(es) in accordance with 9Gender statistics must reflect the many areas where women and men may not enjoy the same opportunities (for example, the labor market) or where women’s and men’s lives may be affected in different ways. India still faces significant gender data gap. As many as 13 key gender statistics identified by EDGE are not reported. These data gaps will be filled by the project. Page 23 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) the verification protocol and submit to the World Bank the corresponding verification reports on time and in form and substance satisfactory to the World Bank. 51. Implementation arrangements, performance monitoring and evaluation, and reporting requirements including fiduciary requirements will be described in detail in a Project Implementation Plan (PIP). C. Sustainability 52. Sustainability of the project will depend on the Government’s commitment to statistics reforms as set out in the Five-year Vision 2019–2024, which identifies an urgent need to enhance the efficiency, responsiveness, and robustness of the national statistical system so that it becomes more responsive to efficient production of high- quality statistics which will be a critical part of the democratic process, providing policy makers and nongovernmental stakeholders, including public at large, on the state of socioeconomic progress of the nation. The vision document defines its objective as follows: “Strengthen India’s national statistical system to provide real-time inputs for policy and stronger dissemination practices for public.” The project will benefit from strengthening the data governance architecture that is expected to result from institutional and policy reforms supported by a series of statistics DPFs that are prepared in parallel to this project. 53. The project supports MOSPI’s vision and extends and strengthens already existing reform initiatives aimed at enhancing the quality of survey data (the introduction of multimodal data collection tools), strengthening the use of administrative statistics (integration of the NIIP), and enhancing the user orientation of MOSPI by supporting data innovations or by enhancing the user experience of data dissemination through use of mapping and interactive tabulation tools. Project activities have been rigorously appraised to ensure that they are viable and aligned with available capacities and will lead to the desired benefits. Innovation funding and investments in training (including through MoUs with advanced statistical agencies) will help the absorption of new approaches aimed at producing higher-quality, timely, and user-friendly statistics. The financial sustainability of the project investments is likely since the project will result in increased trust in publicly generated statistics. IV. PROJECT APPRAISAL SUMMARY A. Technical, Economic and Financial Analysis 54. Official statistics are a global public good. According to public choice theory, a public good is an item for which consumption is both non-excludable and non-rivalrous in that individuals cannot be excluded from use and where use by one individual does not reduce availability to others. This contrasts with private goods. Public goods include law enforcement, national defense, public parks, and official statistics. No market exists for such goods, and therefore, there is a strong case for public provision of these services, free of charge. 55. Data may be the fuel of the information society and calculating the return on investments in national statistics is not straightforward. When inadequate data lead to mistargeting of resources due to wrongly informed formulas for transfers to the states or to beneficiaries of social programs, the savings that quality data could help realize are evident.10 However, in the policy space, it is impossible to compare the results of policy 10For example, in the 2020 budget speech, the Government announced a new transfer scheme that offers approximately 120 million smallholder farmers a guaranteed income of US$84.5 per year. Any small efficiency gain in this US$10 billion program attributable to better statistics would pay for itself. Page 24 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) decisions informed by good data with the counterfactual of decisions made on the basis of outdated or low-quality information. Yet, clearly, without reliable data, decision makers are in the dark and some decisions are not made at all. Core statistics, such as the size and location of the population, are vital for a democratic society to function in the first place. Health and education statistics are required for planning and monitoring public service delivery. Studies have found that reliable data are necessary for accountability by linking investments in education data to stronger school performance and academic improvements.11 56. There have been attempts at measuring the economic benefits of statistical data, which suggest the return is positive. New Zealand’s population census has been estimated to deliver benefits well in excess of its direct costs with a net present value of close to US$1 billion. The Spanish Statistical Office (Instituto Nacional de Estadistica, INE) has been measuring the economic impact of statistical information in the media to have a more accurate perception of how the public values official statistics and to know about their interests. Based on this, the value of INE operations in the media is estimated at €372 million in 2014. A 2005 IMF study indicated that borrowing cost for emerging markets governments fell by 20 percent or 55 basis points on average following subscription to the Special Data Dissemination Standards (SDDS).12 India is already a subscriber to the SDDS, but it is likely that equally impressive gains are possible with continued development, especially within macroeconomic, business, and financial statistics that would improve the functioning of financial markets. 57. The rate of return to investing in statistics is higher in large countries because per capita production costs are lower. Economies of scale in data production emerge from the fact that a country only needs one national statistical commission, or only one set of national accounts but also arise for technical reasons: the accuracy of survey data barely depends on the size of the population for which data are collected. 58. There is mounting evidence that switching data collection platform from paper-based to computer- assisted reduces interview time and cost and increases quality. Introducing CAPI technology for survey interviews is an important component of this project. Studies have shown that this tends to lead to cost savings,13 especially for larger surveys since CAPI has higher fixed up-front cost; shorter interview time, especially for experienced interviewers; and reduced time for backend processing. Studies have also found an increase in quality due to fewer errors.14 B. Fiduciary (i) Financial Management 59. The project has acceptable FM arrangements to account for and report on project expenditures including (a) use of funds in an efficient and economical manner for the purposes intended, (b) preparation of accurate and reliable periodic financial reports, and (c) acceptable audit/assurance arrangements. FM arrangements for the project are fully reliant on ‘use of country systems’, that is, predicated on the GoI’s extant systems which are assessed as satisfactory. 11 Burgess, S., Wilson, D. and Worth, J., 2013. “A Natural Experiment in School Accountability: The Impact of School Performance Information on Pupil Progress.” Journal of Public Economics 106:57–67. 12 Cady, J. 2005. “Does SDDS Subscription Reduce Borrowing Costs for Emerging Market Economies?” IMF Staff Papers 52 (3); 503–517. 13 Leisher. 2014. “A Comparison of Tablet-based and Paper-based Survey Data Collection in Conservation Projects.” Social Sciences 3 (2): 264–271. 14 Asian Development Bank. 2019. “The CAPI Effect, Boosting Survey Data Through Mobile Technology.” Page 25 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 60. The project implementation arrangements rely upon the existing structures within the ministry. This project is being implemented by the NSO within MOSPI. A PMU with adequate staff has been created within the NSO. The secretary, MOSPI, is the executive and administrative head of the ministry and is also designated as the chief accounting authority for the same. The secretary performs this function with the assistance of the additional secretary and financial advisor (AS&FA) and controller of accounts (CA). The CA is the head of the Departmental Accounting Organization and exercises this control with the assistance of senior accounts officers within the Pay and Accounts Office (PAO) and Principal Accounts Office (PrAO). The structure of the finance function in MOSPI is provided in detail in annex 2. 61. The annual budgeting exercise at the GoI follows the provisions governing budget formulation exercise prescribed in General Financial Rules (GFR) 2017. FY 20-21 (Demand for Grants) has been created by the GoI. A separate budget line will facilitate easier tracking of the allocations, execution, and financial reporting under the project. 62. The World Bank funds will be provided to the GoI and will remain within the existing FM systems of the NSO. All guidelines followed for FM are according to the GFR 2017, and the Treasury operations are governed by the Central Treasury Rules of the GoI. There is no separate bank account maintained at the NSO, and all the transactions are routed through the PAO. 63. The project activities are centralized with the division headquarters at New Delhi and will be processed by the PAO based in New Delhi. No funds are being transferred to the states for this project. 64. All transactions pertaining to the project at the PAOs will be recorded in the Public Financial Management System (PFMS). The PFMS was developed by the office of the Controller General of Accounts (CGA), under the Ministry of Finance (MoF), GoI, as a fund-tracking and expenditure-filing system and is being expanded as the GoI’s Integrated Financial Management Information System (IFMIS) solution. The processing mechanism of transactions in PFMS and preparation of monthly accounts in e-Lekha are detailed in annex 2. 65. Financial reporting to the World Bank will be done on a six-monthly basis, reflecting the actual expenditures incurred under the EEP to support the DLIs achieved. The FM consultant based in the PMU will prepare interim financial reports (IFRs) from the expenditure records maintained in the PFMS by the PAO. These IFRs will be submitted to the World Bank half-yearly within 45 days from the end of every such period. 66. Internal controls for payroll and non-payroll transactions are robust in the GoI. The internal control framework at the GoI is embodied in the Budget Manual, GFR 2017, and Treasury Code read with the Store Purchase Manual and Works Manual and other related employee rules. 67. The applicable disbursement method will be ‘Reimbursement’. Disbursement will be made on the basis of satisfactory achievement and verification (according to the agreed verification protocol) of the nine DLIs, supported by adequate EEP reporting. The basic principles governing the DLI-based component are provided in annex 3. 68. The EEPs will consist of project-related investments (goods, non-consulting services, consulting services, training, and operating costs) and partly salaries. The project-related investments include (a) the cost of appointing consultants (through an HR agency); (b) procurement of hardware and software and its maintenance cost during the project lifetime; (c) studies to augment the quality of statistics; (d) training, capacity building, Page 26 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) communication, and change management; and (e) project management support, including consultants at the PMU, and rental office space. The contract for appointment of a PMC is being funded by the GoI and is part of the counterpart funding—thus not within the EEP scope. 69. The Comptroller & Auditor General (C&AG) will be the external auditor for the project. The scope of audit will be according to the terms of reference (ToRs) agreed with the office of the C&AG. The audit report for the project will be submitted by the PMU to the World Bank within nine months from the close of the financial year. 70. The FM risk for the project is being assessed as Moderate. The project has a single accounting center with no transfer of funds. As implementation progresses, it will involve review of financial and audit reports. In the initial years, the project staff may require support/training on project FM and disbursement processes/procedures and guidance on contract management. The World Bank will undertake at least semiannual implementation support missions to ensure that agreed FM arrangements are appropriately followed. (ii) Procurement 71. All goods and consulting and non-consulting services to be financed by the loan will be procured in accordance with the World Bank’s Procurement Regulations for IPF Borrowers (dated July 2016 , revised November 2017 and August 2018) and the provisions of the Loan Agreement. No works procurement is envisaged. If there is conflict between government decrees, rules, and regulations and the World Bank Procurement Regulations, then the World Bank’s Procurement Regulations shall prevail. The project will use the online tool Systematic Tracking of Exchanges in Procurement (STEP) to prepare, clear, and update its Procurement Plan and conduct all procurement transactions. Unless otherwise agreed with the World Bank, the World Bank’s Standard Procurement Documents, Requests for Proposals (RFPs), and Forms of Consultant Contract will be used. 72. Procurement under the project will be carried out by the PMU established for the project under the CAP vertical of the NSO under the auspices of MOSPI. Procurement activities under the project will cover procurement requirements of various divisions of MOSPI, such as the FOD, DQAD, SDRD, DIID, SSD, ESD, and NAD. Some of these divisions have their regional and zonal offices (for example, the FOD and DQAD). The PMU, MOSPI, will be headed by a designated project director and will have a procurement expert to provide guidance and oversight over all procurement activities envisaged under the project. While MOSPI has implemented World Bank- financed Development Policy Loan under the First Statistical Strengthening Project in 2010–2011, it has no experience of or exposure to World Bank’s applicable Procurement Regulations and their requirements. 73. The procurement profile under the project comprises goods and consulting and non-consulting services and is likely to exclude civil works. It includes, among others, selection of PMCs; procurement of HR firm (including payroll management); third-party verification agent for verification/IVA of achievement of Disbursement-linked Results (DLRs); information technology (IT) equipment and accessories (tablets, laptops, printers, and so on); software and hardware for digitizing Urban Frame Survey (UFS); and firms to develop e-training modules, information, education, and communication and outreach material, need-based assessments and studies, individual experts/specialist consultants, and so on. 74. According to the requirement of the Procurement Regulations, a Project Procurement Strategy for Development (PPSD) has been developed, based on which the Procurement Plan for the first 18 months has been prepared. It provides adequate supporting market analysis for the selection methods detailed in the Procurement Page 27 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Plan. The PMU, MOSPI, shall submit to the World Bank, for its review and approval, any updates of the Procurement Plan approved by the World Bank. The project will use STEP in procurement system for all its procurement activities. 75. The project will use technology to bring in efficiencies in its procurement process. It will make use of the GoI’s National Informatics Centre (NIC) platform assessed by the World Bank against Multilateral Development Bank (MDB) requirements to carry out bidding in the project for procurement of goods and consulting and non- consulting services. Depending on needs assessment, the project may use Government e-Marketplace (GeM)15 for procurement of goods and non-consulting services up to the threshold for Request for Quotations (RFQ), that is, up to the equivalent of US$100,000. 76. Fiduciary risks are rated as Moderate. The PMU, MOSPI, will be the key procuring entity under the project. According to its PPSD, total procurement spend is approximately 54 percent of the World Bank loan (US$30 million) and approximately 33 percent of the total project cost (US$60 million). However, the procurement profile does not envisage complex procurement, that is, specifications/ToRs can be easily defined, supply markets are established/developed and competitive, the value of various procurement packages is not very high, and complex contracting strategies are not envisaged. Further, procurement will be centralized at the PMU, MOSPI, with involvement of and technical inputs from various divisions of MOSPI to reduce transaction costs, bring in consistency regarding applicable procurement rules as well as process efficiencies, and provide contract management (other than for PMC, IVA and HR firm) decentralized to various divisions. While MOSPI has implemented World Bank-financed Development Policy Loan under the Statistical Strengthening Project in 2010– 11, it has no experience of or exposure to the World Bank’s applicable Procurement Regulations and their requirements. Capacity is limited and weak, especially on procurement of consultancy services including development of market-responsive ToRs and provision of oversight and monitoring of results. According to the current assessment procurement risk is assessed as Moderate. Appropriate mitigation measures are detailed in annex 3. 77. The World Bank will support procurement implementation on a regular basis with a formal supervision once every six months alongside other project team members and an annual post procurement review. Mission frequency may be increased or decreased based on the procurement performance of the project. C. Legal Operational Policies Triggered? Projects on International Waterways OP 7.50 No Projects in Disputed Areas OP 7.60 No D. Environmental and Social 78. The scope and activities of the project indicate a low-risk project from the environmental and social safeguards perspective. The emphasis on technical assistance for statistical production methods and processes, upgrading of human resource skills, and expanding of capacity is consistent with this assessment. The project does 15 https://gem.gov.in/. Page 28 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) not envisage any land acquisition or construction activities. The disposal of new IT equipment to be acquired for data capture and processing will have environmental management implications. While environmental risks are not expected at the time of IT procurement and adoption, appropriate procedures will need to be in place for disposal of equipment according to the best environmental practices in line with the E-Waste Management guidelines of the GoI and World Bank Group Environmental, Health, and Safety guidelines. Social risks are mostly related to labor management, stakeholder engagement, information disclosure, and grievance redressal. An Environmental and Social Commitment Plan (ESCP), a Stakeholder Engagement Plan, and a Grievance Redressal Mechanism (GRM) have been prepared (and disclosed on MOSPI’s website) to address these risks. Implementation of the material measures and actions set out in this ESCP will be monitored and reported to the World Bank by MOSPI as required by the ESCP and the conditions of the Legal Agreement, and the World Bank will monitor and assess progress and completion of the material measures and actions throughout implementation of the project. V. GRIEVANCE REDRESS SERVICES 79. MOSPI has a fairly robust and easily accessible GRM. Till date, MOSPI has been successful in addressing nearly all grievances received through its existing GRM within a period of 30 calendar days from the receipt of the grievances. The project GRM Plan prepared by MOSPI outlines how MOSPI will address project-related grievances through its existing GRM system. 80. Communities and individuals who believe that they are adversely affected by a World Bank (WB) supported project may submit complaints to existing project-level grievance redress mechanisms or the WB’s Grievance Redress Service (GRS). The GRS ensures that complaints received are promptly reviewed in order to address project-related concerns. Project affected communities and individuals may submit their complaint to the WB’s independent Inspection Panel which determines whether harm occurred, or could occur, as a result of WB non-compliance with its policies and 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 (GRS), please visit www.worldbank.org/grs. For information on how to submit complaints to the World Bank Inspection Panel, please visit www.inspectionpanel.org. VI. KEY RISKS 81. The overall risk to the outcome of the proposed project is Substantial. 82. Political and governance risks are rated Substantial. The credibility of official statistics has been under discussion recently with respect to the GDP back series methodology, delayed dissemination of labor market indicators; and the non-release of the data and report from the 2017/18 round of the NSS dealing with household consumption. Improving the credibility of statistics requires political will, professionalism, and investments in data quality. The latter two will be directly affected by this project; over the former, this project has limited control, though the risk will be mitigated by the World Bank’s engagement on institutional and governance aspects of statistics, in the context of the DPF series that is under consideration. 83. Risks associated with sector strategies and policies are rated Moderate. MOSPI’s strategy is outlined in the Five-year Vision 2019–24 document, which gives a strong signal of government ownership of the reform Page 29 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) strategy. The main risk to the project from ongoing policy initiatives relates to potential changes to Data Privacy and Protection. Activities directly or indirectly supported by this project collect personal data, that is, name, age, ID number, gender, and cell phone number, which could be used to identify an individual person. Currently, statistical data collection is governed by the Data Collection Act of 2008, which contains provisions to guarantee confidentiality to respondents. A Personal Data Protection Bill (PDPB) is currently under preparation. The PDPB has been sent to the Joint Select Committee of Parliament on December 11, 2019, for consultation and deliberation. The PDPB aims to protect the personal data of individuals and to regulate the collection, usage, transfer, and disclosure of the such data. The bill, as currently drafted, provides access to data by individuals and places accountability measures for organizations processing personal data and supplements it by providing remedies for unauthorized and harmful data processing. Additionally, a national-level Data Protection Authority is intended to be set up under the bill to supervise and regulate data fiduciaries. A final text is not expected to be adopted before the Board date of this operation but is likely to be adopted during its implementation period. This PDBP would be applicable to those organizations that are (a) processing the data that have been collected, disclosed, and/or shared within the territory of India and (b) processing personal data that have a connection with any business carried on in the territory of India or have a connection with any activity which involves the profiling of data principles within the territory of India; in addition, the bill is applicable to the processing of personal data if the same is undertaken by the state, any Indian company, or any Indian citizen or persons incorporated under the Indian law. The draft PDBP makes provisions for the use of data for statistics and contains provisions pursuant to which ‘government’ entities could request an exemption from application. Because the implications of the PDBP are not clear yet, the team has valued risks associated with sector strategies and policies as Moderate. A mitigating factor is that the draft bill already explicitly recognizes the use of data for statistical purposes and that MOSPI has a long history dating back to the first household survey over 70 years ago of dealing with data privacy. Should the PDPB be approved, MOSPI and the World Bank will conduct a technical analysis of the potential impact of the effectiveness of the bill on the design of the project and discuss any modifications that may be needed. 84. The risk associated with the technical design is substantial because of uncertainties associated with the design of software which underpins reforms in the administration of household surveys (customized CAPI software being developed by MOSPI) and in the use of existing data (NIIP). These software projects which have been commissioned by MOSPI (funded by GoI) are ambitious and complex and come with tight deadlines. The possibility of delay is real. Consequences of using the software for work flow and roles and responsibilities of units and individuals are unspecified as yet. Uncertainty is therefore high. The project aims to minimize the associated risks by focusing on the results that need to be achieved (for example, a reduction in the time between completing a survey and publishing results). 85. Risks associated with institutional capacity for implementation and sustainability are substantial because MOSPI is short on staff and this is the first time MOSPI implements an IPF. Staff shortages leave limited time for managing the reform program at the top of the organization. MOSPI staff have difficulty to redirect attention from routine activities to data innovations as existing work pressures are high. Moreover, statistical modernization requires a different way of working, with a greater focus on quality control, data integration, and collaboration with other organizations collecting data. Exposure to such approaches has been limited, making it necessary to create a common understanding on how the organization has to change, requiring leadership and vision. The project minimizes these risks through a PMC to ease the burden on management; access to consultants to support professional staff and to bring IPF expertise; and a program of capacity building, training, and staff exchanges with advanced statistical offices to increase awareness about the direction of change. . Page 30 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) VII. RESULTS FRAMEWORK AND MONITORING Results Framework COUNTRY: India National Program for Improving the Quality of Statistics in India Project Development Objectives(s) To improve the quality, efficiency, and user relevance of statistics produced by the India Ministry of Statistics and Programme Implementation. Project Development Objective Indicators RESULT_FRAME_TBL_PDO Indicator Name DLI Baseline Intermediate Targets End Target 1 2 3 4 Improving Survey Data Quality An ARC covering at minimum the fiscal year is approved and NSO core surveys released according to the released on MOSPI’s adopted Advance Release Calendar DLI 3 0.00 website comprising 100 100 100 100 (Percentage) all core statistics, including core surveys (and to be updated annually) Share of core surveys using real-time 0.00 0.00 25.00 50.00 75.00 100.00 supervision (Percentage) Making Most of Existing Data Page 31 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) RESULT_FRAME_TBL_PDO Indicator Name DLI Baseline Intermediate Targets End Target 1 2 3 4 Indicators released quarterly from National DLI 6 0.00 10 20 30 45 60 Factsheet (Number) Enhancing User Relevance of Published Statistics Legacy survey data available for use in the DLI 8 0.00 0.00 0.00 4.00 6.00 10.00 online tabulation tool (Number) PDO Table SPACE Intermediate Results Indicators by Components RESULT_FRAME_TBL_IO Indicator Name DLI Baseline Intermediate Targets End Target 1 2 3 4 Improving Survey Data Quality MOSPI has approved and made the ‘Innovation Funds’ operational: (i) it Survey-related methodological studies includes an DLI 2 0.00 2.00 4.00 6.00 8.00 released (Number) appropriate selection procedure, and (ii) it has already started funding selected studies Share of outsourced investigators with 0.00 0.00 25.00 50.00 75.00 90.00 certification (Percentage) Page 32 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) RESULT_FRAME_TBL_IO Indicator Name DLI Baseline Intermediate Targets End Target 1 2 3 4 Core surveys implemented using a multi- 0.00 20.00 20.00 50.00 75.00 75.00 modal data capture platform (Percentage) Average time lag between end of fieldwork and public release of core survey data DLI 1 12.00 12.00 10.00 8.00 7.00 5.00 (Months) Making Most of Existing Data Missing EDGE indicators reduced (Number) 13.00 13.00 10.00 7.00 5.00 3.00 Protocols for NQAF developed National Factsheet indicators assessed (acceptable to the using National Quality Assurance DLI 5 0.00 10 20 30 45 World Bank) and Framework (Number) have been adopted by MOSPI. Integrated data processing system used for No Yes national accounts (Yes/No) Natural capital accounts produced 4.00 6.00 6.00 9.00 9.00 12.00 (Number) Training needs assessment completed. Training gap reduced for MOSPI staff 100.00 MoU signed for 90.00 80.00 60.00 50.00 (Percentage) collaboration with leading international statistical agency Beta statistics released (Number) DLI 7 0.00 1.00 2.00 3.00 Page 33 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) RESULT_FRAME_TBL_IO Indicator Name DLI Baseline Intermediate Targets End Target 1 2 3 4 Data gaps in SDG indicators reduced 100.00 80.00 55.00 30.00 15.00 0.00 (Number) The Detailed Project Report (DPR) setting out The Proof of Concept the key issues for (PoC) for the preparing an SBR Statistical Business Statistical business register updated with and details on its DLI 4 0.00 Register (SBR) has 2.00 4.00 5.00 information from states (Number) implementation been approved by approach has MOSPI and agreed to been approved by World Bank. by MOSPI and agreed to by World Bank. Enhancing User Relevance of Published Statistics A Geo-spatial unit or team has been established in MOSPI Layers available for online mapping tool with adequate DLI 9 0.00 5.00 10.00 15.00 20.00 (Number) hardware and software and with access to geo-spatial data. IO Table SPACE UL Table SPACE Page 34 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Monitoring & Evaluation Plan: PDO Indicators Responsibility for Indicator Name Definition/Description Frequency Datasource Methodology for Data Collection Data Collection ARC means a document which provides a general NSO core surveys statement on the schedule of release of data, which MOSPI Visual inspection of MOSPI website. released according to is publicly disseminated to provide prior notice of Annual website/NS See verification protocol for DLI #3 PMU the adopted Advance the precise release dates. Such information may be S for details. Release Calendar provided for statistical releases in the coming week, month, quarter, or year. The transition to CAPI will enable the use of para- data to assess in real-time the quality of Year 1: Visual inspection of the enumeration by investigators. These platforms are approved (by MOSPI and World expected to be used for surveys implemented by Bank) Protocol for real-time the multi-modal data capture system and in all Share of core surveys DQAD/FOD supervision of surveys. relevant field offices of FOD. At baseline, none of annual PMU using real-time /MIS report Year 2–5: Inspect and calculate the the surveys use para-data for enumerator supervision share of core surveys out of the all supervision, because, though CAPI is used, none of core surveys which applied the the para-data collected is used to supervise approved real-time supervision enumeration quality. protocol. To be reported by the NSS. List of core surveys is included in the Project Implementation Plan (PIP). MOSPI Visual inspection of MOSPI website. Indicators released The Quarterly National Factsheet of the Indian Quaterly website/ES See verification protocol for DLI #6 PMU quarterly from Economy is a compilation of 100 indicators notified D for details. National Factsheet by MOSPI. Legacy surveys are surveys completed before the start of the project for which the micro-data are MOSPI Visual inspection of MOSPI website. Legacy survey data available in the online micro-data library: Annual website/DII See verification protocol for DLI #9 PMU available for use in the http://microdata.gov.in/nada43/index.php/catalog/ D for details. online tabulation tool central/about Page 35 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) An online interactive tabulation tool enables users to tabulate data in several legacy surveys according to their own specifications. ME PDO Table SPACE Monitoring & Evaluation Plan: Intermediate Results Indicators Responsibility for Indicator Name Definition/Description Frequency Datasource Methodology for Data Collection Data Collection Year 1: Inspect whether the Survey-related methodological studies refer to DIID, PMU, Innovation Funds are operational Survey-related studies that aim to improve the quality of surveys SDRD, and Annual Year 2: Visual inspection of MOSPI PMU methodological and have been financed from ‘Innovation Funds’ MOSPI website studies released following the agreed procedure described in the website See verification protocol for DLI #2 PIP to be eligible to be included under this DLI. for details. Certification refers to investigators having Inspect the share of outsourced completed the course for investigators and having Share of outsourced investigators out of all the successfully passed the relevant exam. Annual NSSTA/FOD PMU investigators with investigators hired, in any given year, Investigators may require to be re-certified when certification that are certified. To be reported by their performance (as established using para-data the NSS. driven quality control) is insufficient. Core surveys Multi-modal data capture platform refers to any The NSS to report which surveys use implemented using a Annual NSS PMU CAPI system. CAPI for data collection. multi-modal data (DQAD) List of core surveys is included in the PIP. capture platform Average time lag between end of Time lag between the end of fieldwork and the FOD and Annual See verification protocol for DLI #1 PMU fieldwork and public public release of the micro-data of core surveys to SDRD for details. release of core survey be reduced over the project period. data Page 36 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Missing EDGE indicators refers to the list of 13 indicators that MOSPI is not reporting on (at SSD and baseline) but which it intends to produce by Missing EDGE Annual MOSPI Visual inspection of the MOSPI PMU 2025. Reported EDGE indicators can be found at: indicators reduced website website www. Genderstats.un.org/#/data-availability. List of missing edge indicators is provided in the PIP. Quality framework applied means that the indicator has been assessed against the criteria identified in National Factsheet the National Quality Assurance Framework and that SSD and Visual inspection of the MOSPI indicators assessed the results of said assessment have been obtained Annual MOSPI PMU website. See verification protocol for using National Quality in a joint process with the producer of these data Website DLI #5 for details. Assurance Framework (and at very least been shared with said data producer). Data quality reports are made publicly available on the MOSPI website. Inspection may entail commissioning Integrated system to be designed/purchased in Integrated data of a subject expert to review the consultation with World Bank. This system will NAD/DIID processing system Annual successful (in terms of PMU replace the separate Excel sheets maintained at (NIIP) used for national efficiency; data quality; replicability; baseline. accounts archiving) implementation of the integrated system. NCA is a transparent way of quantifying the value of natural assets beyond what you would see in a typical financial account. They are a series of interconnected accounts that provide a structured set of information relating to the stocks of natural SSD/MOSPI Visual inspection of the MOSPI Natural capital Annual PMU capital and flows of services supplied by them in website website. accounts produced physical or monetary terms. Details about the nature and kind of NCAs being developed as part of the project are available in the PIP. The NCAs need to be disclosed publicly on the MOSPI website. Page 37 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) The training gap will be established during the training needs assessment, to be completed during Year 1: Visual inspection of the the first year of the project. The training gap training needs assessment and the identified post the needs assessment is scaled to MoU signed with a leading 100 as a baseline for monitoring purposes. The gap NSSTA/MIS international statistical agency. Training gap reduced is a reflection of at least two variables: skills needed Annual PMU report for MOSPI staff and number of staff needing these skills. Year 2–5: Inspect and calculate the training gap being met annually, over Successful completion of the Year 1 target will also the baseline, through various include signing of MoU(s) with leading international activities done by MOSPI (NSSTA). statistical agencies to address (some) of the gaps identified though the needs assessment. Beta statistics involve new statistics developed which use innovative data, data collection, and/or data processing methodologies. Beta statistics may DIID / MIS Visual inspection of the MOSPI Beta statistics Annual PMU initially come with a higher margin of error as report website. See verification protocol for released data/methodologies used are new. Beta statistics DLI #7 for details. are publicly released on the MOSPI website, which may reflect their beta nature. MOSPI has identified a list of 100 SDG indicators Visual inspection of the MOSPI Data gaps in SDG which it is not reporting on at baseline but intends Annual SSD /NIF PMU website/NIF indicators reduced to produce by 2025. The list of 100 SDG indicators is included in the PIP. Incorporation into the statistical business register refers to an updating of the business register Investigate the number of states for Statistical business (derived from the 7th EC) using administrative data. ESD (EC) / which the business register was register updated with Such data may be obtained from state registers, Annual PMU MIS report updated. See verification protocol for information from MCA, GST, or otherwise. The implementation DLI #4 for details. states strategy will be developed based on the PoC and DPR being prepared in Year 1 and 2 of the project, respectively. Page 38 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) A layer refers to a variable available in such a geo- Visual inspection of MOSPI spatial format that it can be combined with other DIID / MIS Layers available for Annual website/NIIP. See verification PMU layers. The data for these layers may be hosted by report online mapping tool protocol for DLI # 9 for details. MOSPI but could also simply be accessible through APIs from other agencies. Disbursement-linked Indicators, Disbursement-linked Results and Allocated Amounts and Formulas16 Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts Number of core Number of core Number of core Number of core surveys (from surveys (from surveys (from surveys (from Reduction in the total core the total core the total core the total core the average surveys in this surveys in this surveys in this surveys in this time lag year) that have year) that have year) that have year) that have between end 12 reduced the reduced the reduced the reduced the of fieldwork months time lag time lag time lag time lag and public between end of between end of between end of between end of release of fieldwork and fieldwork and fieldwork and fieldwork and 1 survey data public release public release public release public release of survey data of survey data of survey data of survey data to 10 months to 8 months to 7 months to 5 months Formula: Formula: Formula: Formula: Yes US$1,500,000 * US$1,500,000 * US$1,500,000 * US$1,500,000 * Total financial US$ Undisbursed (timely released (timely released (timely released (timely released allocated to 20% 6,000,000 amounts are surveys/total surveys/total surveys/total surveys/total DLI carried over core surveys) core surveys) core surveys) core surveys) to subsequent 16 Values for each element of the formulas are according to the Verification Protocol. Page 39 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts year (s) to the US$1,500,000 US$1,500,000 US$1,500,000 US$1,500,000 maximum allocation of the DLI. 2 survey-related 4 survey-related 6 survey-related 8 survey-related MOSPI has methodological methodological methodological methodological approved and studies selected studies selected studies selected studies selected made the (as per (as per (as per (as per “Innovation Innovation Innovation Innovation Innovation Survey-related Funds” Funds Funds Funds Funds methodologic operational (i) it Baseline: procedures) procedures) procedures) procedures) al studies includes an Zero (0 have been have been have been have been completed appropriate studies) completed and completed and completed and completed and and published selection published on published on published on published on on MOSPI procedure, and MOSPI’s MOSPI’s MOSPI’s MOSPI’s website (ii) it has already 2 website website website website started funding compared with compared with compared with compared with selected studies baseline. baseline. baseline. baseline. Yes. Undisbursed amounts are Formula: Formula: Formula: Formula: Total financial US$ carried over US$125,000 per US$125,000 per US$125,000 per US$125,000 per allocated to 2,000,000 6% to subsequent US$1,000,000 study study study study DLI: year (s) to the maximum US$250,000 US$250,000 US$250,000 US$250,000 allocation of the DLI. Page 40 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts An ARC covering at minimum the Increase in the fiscal year is Number of core Number of core Number of core Number of core number of approved and surveys (from surveys (from surveys (from surveys core surveys released on the total core the total core the total core released (from released No MOSPI’s website surveys in this surveys in this surveys in this the total core according to baseline comprising all year) released year) released year) released surveys in this the adopted available core statistics, as per the as per the as per the year) as per the Advance including core current year’s current year’s current year’s current year’s Release surveys (and to ARC ARC ARC ARC Calendar 3 be updated (ARC) annually) Formula: Formula: Formula: Formula: 1,000,000*(surv 1,000,000*(surv 1,000,000*(surv 1,000,000*(surv eys release in a eys release in a eys release in a eys release in a No. Release Total financial timely timely timely timely US$ or reports as allocated to 16.5% US$925,000 manner/numbe manner/numbe manner/numbe manner/numbe 4,925,000 per ARC is DLI: r of core r of core r of core r of core time-sensitive surveys) surveys) surveys) surveys) US$1,000,000 US$1,000,000 US$1,000,000 US$1,000,000 DPR setting out Number of The PoC for the the key issues 2 states have 4 states have 5 states have states SBR has been for preparing a been been been incorporated No approved by SBR and details incorporated incorporated incorporated 4 into the baseline MOSPI and on its into the SBR into the SBR into the SBR Statistical available agreed to by implementation compared with compared with compared with Business World Bank approach has baseline. baseline. baseline. Register (SBR) been approved Page 41 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts by MOSPI and agreed to by World Bank Yes. Undisbursed amounts are Formula: Formula: Formula: Total financial US$ carried over US$1,200,000 US$1,200,000 US$1,200,000 allocated to 9,000,000 30% to subsequent US$1,000,000 US$2,000,000 per state per state per state DLI: year(s) to the maximum US$2,400,000 US$2,400,000 US$1,200,000 allocation of the DLI National Protocols for The NQAF has The NQAF has The NQAF has The NQAF has Quality NQAF developed been applied to been applied to been applied to been applied to Assurance No (acceptable to 10 National 20 National 30 National 45 National Framework baseline the Bank) and Factsheet Factsheet Factsheet Factsheet (NQAF) is used available have been Indicators Indicators Indicators Indicators for National adopted by compared with compared with compared with compared with Factsheet MOSPI baseline. baseline. baseline. baseline. Indicators 5 Yes. Undisbursed amounts are Formula: Formula: Formula: Formula: Total financial carried over US$44,445 per US$44,445 per US$44,445 per US$44,445 per US$ allocated to 8% to subsequent US$500,000 indicator indicator indicator indicator 2,500,000 DLI: year(s) to the maximum US$444,445 US$444,445 US$444,445 US$666,665 allocation of the DLI. Page 42 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts At least 20 At least 30 At least 45 At least 60 National National National National National At least 10 Factsheet Factsheet Factsheet Factsheet Factsheet National Indicators on Indicators on Indicators on Indicators on Indicators on Factsheet Indian No Indian economy Indian economy Indian economy Indian economy Indicators on economy are baseline are released are released are released are released Indian economy released available quarterly on quarterly on quarterly on quarterly on are released quarterly on MOSPI’s MOSPI’s MOSPI’s MOSPI’s quarterly on MOSPI’s website website website website MOSPI’s website. 6 website. compared with compared with compared with compared with baseline. baseline. baseline. baseline. Formula: Formula: Formula: Formula: Formula: US$ US$ US$ US$ US$ 250,000*q/4 250,000*q/4 250,000*q/4 250,000*q/4 250,000*q/4 Total financial US$ (annual (annual (annual (annual (annual allocated to 4% No. 1,250,000 disbursements) disbursements) disbursements) disbursements) disbursement) DLI: up to up to up to up to up to US$250,000 US$250,000 US$250,000 US$250,000 US$250,000 1 Beta Statistics 2 Beta Statistics 3 Beta Statistics has been has been has been Beta statistics publicly publicly publicly are publicly No released in released in released in 7 released on baseline MOSPI’s MOSPI’s MOSPI’s MOSPI’s available website website website website. compared with compared with compared with baseline. baseline. baseline. Page 43 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts Yes. Undisbursed amounts are Formula: Formula: Formula: Total financial carried over US$250,000 per US$250,000 per US$250,000 per US$ allocated to 2.5% to subsequent beta statistics beta statistics beta statistics 750,000 DLI: year(s) to the maximum US$250,000 US$250,000 US$250,000 allocation of the DLI. 4 legacy surveys 6 legacy surveys 10 legacy Number of data are data are surveys data are legacy surveys accessible for accessible for accessibility for data available No use in the use in the use in the for use in the baseline online online online online available tabulation tool tabulation tool tabulation tool tabulation compared with compared with compared with tool baseline. baseline. baseline. 8 Yes. Undisbursed Formula: Formula: Formula: amounts are US$150,000 per US$150,000 per US$150,000 per Total financial carried over US$ legacy survey legacy survey legacy survey allocated to 5% to subsequent 1,500,000 data data data DLI: year (s) to the maximum US$600,000 US$300,000 US$600,000 allocation of the DLI. Number of No online A Geo-spatial 5 Layers are 10 Layers are 15 Layers are 20 Layers are 9 Layers mapping unit or team has accessible accessible accessible accessible accessible tool been established through an through an through an through an Page 44 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Disbursement As a % of Roll over of Expected Target for specific DLRs DLI # -linked total undisbursed Baseline FY 20/21 FY 21/22 FY 22/23 FY 23/24 FY 24/25 Indicator financing amounts through exists; in MOSPI with online mapping online mapping online mapping online mapping online nor is adequate tool (incl. tool (incl. tool (incl. tool (incl. mapping tool there a hardware and through APIs) through APIs) through APIs) through APIs) (incl. through dedicated software and compared with compared with compared with compared with APIs) geographi with access to baseline. baseline. baseline. baseline. c geo-spatial data. informati on system (GIS) unit Yes. Undisbursed Formula: Formula: Formula: Formula: amounts are US$82,500 per US$82,500 per US$82,500 per US$82,500 per Total financial carried over geo-spatial geo-spatial geo-spatial geo-spatial allocated to US$ 6% to subsequent US$350,000 layer layer layer layer DLI: 2,000,000 year(s) to the maximum US$412,500 US$412,500 US$412,500 US$412,500 allocation of the DLI. Page 45 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Verification Protocol Table: Disbursement-linked Indicators Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period Disbursements will be based verification of the The time lag standard refers to the share of core surveys out of all core surveys time in months between the end of conducted in a given fiscal year that meets the fieldwork and release of data. The time lag standard for the year. time lag standard becomes increasingly shorter over the US$1,500,000 is allocated to each fiscal year lifetime of the project, starting from year 2 through year 5 of the project. The Reduction in from a baseline of 12 months and amount disbursed each year is the allocated the average gradually decreasing to 5 months FOD (End of amount for that fiscal year multiplied by the time lag at the end of the project. Fieldwork), share of core surveys that meet the standard between end DIID (date of out of all core surveys conducted in the fiscal 1 Yes IVA of fieldwork End of fieldwork as indicated by release of data), year. If data from all core surveys in any given and public date entered on last completed and year are released as per the standard of that release of questionnaire. MOSPI website year, the full amount allocated to that year will survey data be disbursed in addition to any undisbursed Date of data release refers to the amount carried over from the previous fiscal date that data becomes accessible year. through the micro-data library. The number and title of core surveys to be Survey data refers to the conducted in a given fiscal year will be anonymized unit level data. established before the beginning of each fiscal year, agreed to by the World Bank and recorded in the PIP. Page 46 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period Undisbursed balance will be carried over to the subsequent fiscal year. Progression in this DLR is achieved by the fact that the time within which survey data should be released becomes shorter over the course of the project. An undisbursed amount that is carried over to the next year will only be disbursed when a more stringent survey release time is achieved in the next year. The Innovation Funds will be Disbursement in Year 1 will be made based on considered ‘operational’ when (1) the operationalization of the Innovation Funds. appropriate procedures for study Visual verification of the agreed procedure in selection, award, monitoring and the PIP and contract ward (or equivalent evaluation have been documented, documentary proof) of commissioning at least DIID (nodal Survey-related in agreement with the World Bank, two studies following the agreed procedure agency for methodologica and (2) at least 2 studies have been will be done. Innovation l studies selected to be funded following the Funds), 2 completed agreed procedure. The agreed Yes IVA US$1,000,000 is allocated to fiscal year 1 of the PMU (Procuring and published appropriate procedure will be project. The amount will disburse on Agency) on MOSPI documented and included in the achievement of the Year 1 target as explained and website PIP. above. MOSPI website Survey-related methodological Disbursements in Year 2–Year 5 will be made studies refer to studies that aim to based on the number of survey-related improve the quality of surveys and methodological studies completed. Document have been financed from based verification of the method of selection Page 47 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period ‘Innovation Funds’ following the and funding along with visual verification of the agreed procedure described in the completed study on the MOSPI website will be PIP to be eligible to be included done. under this DLI. US$125,000 is allocated to each study with a A study is considered complete maximum of 8 studies that can be funded when (1) it meets acceptable under this DLI during the project lifecycle. The academic standards, and (2) its amount disbursed each fiscal year is calculated results are accessible on the MOSPI by multiplying the allocated amount for each website. study with the number of eligible studies completed for any given fiscal year. The DLI The numbers indicated as targets amount will disburse fully when 8 eligible are cumulative. By Year 5, 8 survey- studies have been completed. related methodological studies should be published on the Undisbursed balance will be carried over to the website. subsequent fiscal year. Progression in this DLR is achieved by the increase in the number of studies conducted. An undisbursed amount that is carried over to the next year will only be disbursed when more studies are published. List of tentative areas of methodological studies has been indicated in the PIP. Increase in the ARC means a document which MOSPI Website Disbursement in Year 1 will be made based on number of provides a general statement on and visual verification of an approved ARC on the 3 No IVA core surveys the schedule of release of data, SDRD (date of MOSPI website. released which is publicly disseminated to release) Page 48 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period according to provide prior notice of the US$925,000 is allocated to fiscal year 1 of the the adopted precise release dates. Such project. The amount will disburse on Advance information may be provided for achievement of Year 1 target explained above. Release statistical releases in the coming Calendar (ARC) week, month, quarter or year. Disbursements in Year 2–Year 5 will be made based on verification of the share of surveys, Year 1: An approved (by MOSPI out of all the surveys included in the ARC, and concurred by World Bank) ARC released information as per the ARC in a given is developed for all core statistics fiscal year. including surveys and is published on the MOSPI website. The ARC US$1,000,000 is allocated to each fiscal year should have, at the very least, from Year 2 through Year 5 of the project. The precise release dates of key amount disbursed each year is the allocated statistical outputs—survey report amount for that fiscal year multiplied by the and anonymized unit level data— share of surveys that meet the timeline as set for core statistics including core forth in the ARC out of all surveys conducted in surveys to be completed in a given the fiscal year. Disbursements are subject to fiscal year. the ARC being updated annually, in consultation with the World Bank, approved by Year 2–5: Core surveys need to be MOSPI and released on the MOSPI website. If released on the MOSPI website in data from all surveys in any given year are accordance with the ARC. released as per the ARC, the full amount allocated to that year will be disbursed. The ARC needs to be updated annually to (1) accommodate the Undisbursed amounts are not carried forward timeliness of core survey data to the next fiscal year. release used in DLI#1, but may be Page 49 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period more ambitious, and (2) include all List of ‘core statistics’ including ‘core survey’ surveys being conducted in that has been indicated in the PIP. fiscal year. Disbursement in Year 1 will be made based on ‘SBR’ means a register built and visual verification of the PoC. maintained for statistical purposes of all enterprises and/or US$1,000,000 is allocated to fiscal year 1 of the establishments in the economy. project. The amount will disburse on The SBR is the main source of data achievement of Year 1 target explained above. for business demography, structural changes in the economy Disbursement in Year 2 will be made based on and acts as the central sampling visual verification of the DPR. Number of frame for censuses and surveys of states businesses. External US$2,000,000 is allocated to fiscal year 2 of the incorporated Yes Specialist project. The amount will disburse on 4 into the Year 1: The PoC will document (Year 3 ESD and PMU Consultant achievement of Year 2 target explained above. Statistical research and feasibility studies onward) and IVA Business based on sample datasets from Disbursements in Year 3–Year 5 will be made Register (SBR) Central/State government registers based on verification carried out by an external and the 7th EC. The final PoC is specialist consultant who will review whether approved by MOSPI and acceptable the SBR is being updating with business data to the World Bank. from states. Year 2: The DPR sets out the key US$2,400,000 is allocated to each state that is issues for preparing an SBR and incorporated into the SBR. The amount details the implementation disbursed each year (Year 3–5) will be calculated approach. Final DPR is approved by by multiplying the amount allocated to each Page 50 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period MOSPI and acceptable to the state with the number of states incorporated in World Bank. that given fiscal year. An undisbursed amount that is carried over to the next year will only be Year 3–5: The SBR developed based disbursed when another state is incorporated on the approved DPR will get into the SBR, up to a maximum of 5 states during updated by incorporating data the project lifecycle. Progression is achieved as from the states. [Note the counting SBR updating requires use of data from is done on the number of states increasingly more states. that have been updated, not the number of data sources used. MCA Undisbursed balance will be carried over to the or GSTN can be used for multiple subsequent fiscal year. Progression in this DLR states.] is achieved by the increase in the number of states incorporated in the SBR. An undisbursed The numbers indicated as targets amount that is carried over to the next year are cumulative. will only be disbursed when more states are incorporated into the SBR. The list of target states has been indicated in the PIP. National NQAF is a structure for Disbursement in Year 1 will be made based on Quality implementing quality assurance review of a specialist external consultant. Assurance activities in an organization. The External Yes PMU, periodic Framework NQAF for statistics in India is an Specialist US$500,000 is allocated to fiscal year 1 of the 5 (Year 2 implementation (NQAF) is used adaptation of the generic UN Consultant project. The amount will disburse if the review onward) progress reports for National NQAF. It sets out the core quality and IVA finds the NQAF to meet international standards Factsheet standards for statistical products and fitness-for-purpose in an Indian context Indicators and processes against which Page 51 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period activities carried out can be Disbursements in Year 2–Year 5 will be based assessed to provide confidence on the number of National Factsheet indicators that the processes fulfill the that have been assessed systematically using requirements for the statistical the approved NQAF. The satisfactory and output. systemic assessment needs to be endorsed by a specialist external consultant. Year 2 onward: It is applied to data published on the National US$44,445 is allocated to each fiscal year from Factsheet. The results of the Year 2 through Year 5 of the project. The assessment have to be obtained in amount disbursed each year will be calculated a joint process with the producer by multiplying the amount allocated to each of these data (and at very least indicator with the number of National Factsheet been shared with said data indicators assessed using the adapted NQAF. producer) and published on the Assessment of up to a maximum of 45 indicators MOSPI website after completion. can be funded during the project lifecycle The numbers indicated as targets An undisbursed amount is carried over to the are cumulative. next year. It will disburse only when more indicators are assessed. Progression is achieved as the number of National Factsheet indicators subject to the NQAF increases. The list of National Factsheet indicators is annexed in the PIP. Page 52 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period Disbursement will be made based on the number of National Factsheet indicators that are released quarterly out of the number of national factsheet indicators targeted in any given year. Visual inspection of the MOSPI website suffices to assure that the indicators are released. US$250,000 is allocated to each fiscal year National from Year 1 through Year 5 of the project. The Factsheet The Quarterly National Factsheet amount disbursed each year is calculated by indicators on of the Indian Economy is a multiplying the allocated amount for that fiscal Indian compilation of 100 indicators year with the number of quarters in which the 6 economy are notified by MOSPI. No MOSPI website IVA targeted numbers of National Factsheet released indicators were released on the MOSPI quarterly on The numbers indicated as targets website. If all the targeted National Factsheet MOSPI’s are cumulative. indicators in all quarters are released, the full website amount allocated to that year will be disbursed. Undisbursed amounts will not be carried forward to the next year. This DLI will disburse annually. List of National Factsheet indicators is annexed in the PIP. Page 53 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period Disbursements in Year 3–Year 5 will be made Beta statistics refers to a set of based on the number of beta statistics newly developed or innovative published on the MOSPI website. Production of statistics, produced using beta statistics to be verified by external innovative techniques and or data, specialist consultant(s) reviewing progress on that are undergoing evaluation and data innovations. further development, and which may become part of official US$250,000 is allocated to each year. Each statistics. beta statistics which is publicly released will result in a disbursement of US$250,000. The Beta statistics World Bank and MOSPI staff to amount disbursed each fiscal year is calculated are publicly jointly agree (at selection stage for by multiplying the allocated amount for each 7 released on Yes MOSPI website IVA funding; based on relevance) beta statistics with the number of beta MOSPI’s whether a newly developed statistics produced for any given fiscal year up website. statistic qualifies as beta statistics to a maximum of 3 beta statistics to be funded upon development. Only those under this DLI during the project lifecycle. The beta statistics which have been DLI allocation will be fully disbursed when all 3 funded by the innovation funds, beta statistics have been published. following the agreed procedures, will be eligible to be included under An undisbursed amount is carried over to the this DLI. next year. It will disburse only when more beta statistics are released. Progression is achieved The targets are cumulative. as the number of beta statistics published increases. Number of Legacy surveys are surveys Disbursements in Year 3–Year 5 will be made 8 legacy surveys completed before the start of the Yes MOSPI website IVA based on the number of legacy surveys for available for project for which the micro-data Page 54 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period use in the are available in the online micro- which online tabulation tools are accessible on online data library: the MOSPI website in any given year. tabulation tool http://microdata.gov.in/nada43/in dex.php/catalog/central/about US$150,000 is allocated to each legacy survey for which an online tabulation tool has been An online interactive tabulation developed up to a maximum of 10 legacy tool will be created which enables surveys during the project lifecycle. The users to tabulate data in several amount disbursed each fiscal year is calculated legacy surveys according to their by multiplying the amount allocated to each own specifications. Over time the legacy survey multiplied by the number of number of legacy surveys for which legacy surveys for which online tabulation tool the online tabulation tool can be is accessible on the MOSPI website in any given used will increase. fiscal year. The DLI amount will disburse fully when all 10 legacy surveys have been The targets are cumulative. published on MOSPI website. An undisbursed amount is carried over to the next year. It will disburse only when online tabulation tools are available for more legacy surveys. Progression is achieved as the number of legacy surveys for which online tabulation tools exist increases. List of tentative legacy surveys for which online tabulation tool will be accessible is indicated in the PIP. Page 55 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period Disbursement in Year 1 will be made based on MOSPI establishing a Geo-Spatial Unit with adequate hardware and software and access to geo-spatial data. Geo-spatial layers are different US$350,000 is allocated to fiscal year 1 of the geo-spatial attributes, which are project. The amount will disburse on combined on a map. For example, achievement of Year 1 target explained above. municipal boundaries, trunk roads, rural roads, and water bodies Disbursements in Year 2–Year 5 will be based Number of would be four different layers. DIID, on the number of geo-spatial layers available layers MOSPI website on the MOSPI website introduced in the said accessible These layers will be available in an and year. 9 through online Yes IVA online mapping tool. These layers PMU, periodic mapping tool may be owned and curated on implementation US$82,500 is allocated to each geo-spatial layer (incl. through MOSPI’s website or available progress reports that has been made accessible on the website in APIs) through APIs and maintained by each fiscal year from Year 2 through Year 5 of other agencies. the project. The amount disbursed each year will be calculated by multiplying the amount allocated to each geo-spatial layer made accessible with the number of layers made accessible in a given fiscal year. An undisbursed amount that is carried over to the next year will only be disbursed when another layer is accessible on the MOSPI Page 56 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Protocol to Evaluate Achievement of the DLI and Data/Result Verification Scalability of Data Disbursemen # DLI Definition/ Description Source/Agency Verification ts Procedure and Reporting Entity (Yes/No) Period website up to a maximum of 20 layers during the entire project lifecycle. Progression is achieved as the number of layers accessible online increase. The numbers layers as targets are cumulative. By year 5, 20 layers will be available on the MOSPI website. Note: a) for the purposes of verification, NIIP is also considered a part of the MOSPI website, that is, products publicly available on the NIIP portal may be considered as disclosed on the MOSPI website for the purposes of monitoring and fulfilling verification protocols, b) For more details on the verification protocol, please refer to the PIP document, c) PMU to coordinate and ensure the IVA has access to all the data/information required. Page 57 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) ANNEX 1: Implementation Arrangements and Support Plan COUNTRY: India National Programme for Improving the Quality of Statistics in India 1. The strategy for implementation support has been developed based on the nature of the project and its risk profile. It aims to make implementation support to the client flexible and efficient and focuses mainly on implementation of the risk mitigation measures defined in the Systematic Operations Risk- Rating Tool. 2. The World Bank’s approach to implementation support strongly emphasizes open and regular communication with all actors directly involved in the project, constant information exchange, and adequate flexibility to accommodate the specificities of the scheme. 3. The implementation support strategy is based on several mechanisms that will enable enhanced implementation support to the Government and timely and effective monitoring. The implementation support thus comprises (a) review missions, (b) regular technical meetings and visits by the World Bank between the formal review missions, (c) PMU reporting based on the performance agreements, and (d) internal audit and FM reporting. 4. The World Bank will provide timely implementation support to the project’s components as well as guidance regarding technical, fiduciary, social, and environmental issues. Regular interaction is facilitated by the presence of at least one co-task team leader (TTL) in the country office, along with fiduciary and safeguards specialist. Country office staff will be supported by a full-time short-term consultant/extended-term consultant. Formal implementation support and field visits will be carried out as required and will focus on the following: (a) Technical inputs. The World Bank will solicit inputs from international experts in statistical modernization, para-data analysis for household surveys, and business registries whose support will focus on relevant components of the project. The team will also draw on expertise within the World Bank, particularly environmental accounts and data visualization. (b) Fiduciary requirements and inputs. Training will be provided by the World Bank’s FM specialist and the procurement specialist before project effectiveness and during project implementation. This will allow building capacity among implementing agencies in matters of FM and procurement, particularly regarding the World Bank procedures. Supervision of FM arrangements will be carried out as required as part of the project supervision plan, and support will be provided on time to respond to project needs. Procurement supervision will be carried out on a semi-annual basis. Mission frequency may be increased or decreased based on procurement performance of the project. (c) Safeguards. The World Bank will monitor compliance with the Environmental and Social Framework during the implementation support missions, and technical guidance will be provided accordingly. Page 58 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 5. The main focus of the implementation support is summarized below: Table 1.1. Implementation Support Plan Time Focus Resource Estimate First 12 Technical inputs Statistical modernization 4 Ws months Para-data 3 Ws Business registries 2 Ws Environmental accounts 2 SWs Procurement training Procurement specialist 1 SW FM training FM specialist 1 SW Safeguards training Environment specialist 1 SW Social development specialist Project supervision Co-TTLs 26 SWs FM, disbursement, and reporting FM specialist 2 SWs Procurement management Procurement specialist 2 SWs Environment and social monitoring and Environment specialist 1 SW reporting Social development specialist 12–60 Technical inputs Statistical modernization 2 Ws months Para-data 2 Ws (annual) Business registries 3 Ws Environmental accounts 2 SWs Data visualization 1 SW Environment and social monitoring and Environment specialist 1 SW reporting Social development 1 SW specialist FM, disbursement, and reporting FM specialist 2 SWs Procurement management Procurement specialist 2 SWs Project supervision Co-TTLs 26 SWs Note: SW = Staff week; W = Week. Page 59 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) ANNEX 2: Financial Management COUNTRY: India National Programme for Improving the Quality of Statistics in India Institutional Arrangements 1. This project is being implemented by the NSO within MOSPI. A PMU with dedicated staff has been created under the Statistical Strengthening Project Unit (SSPU) within the NSO. The PMU will be further strengthened with consultants, as required during the project implementation. The secretary of MOSPI is the executive and administrative head of the ministry and is also designated as the Chief Accounting Authority for MOSPI. The secretary performs this function with the assistance of the AS&FA and CA. The structure of the finance function in MOSPI is provided in Figure 2.1: Figure 2.1. Organogram of Finance Function in MOSPI Secretary MOSPI (Chief Controller General of Accounts (CGA) Accounting Authority) under Ministry of Finance, GoI Additional Secretary and Financial Advisor (AS&FA) Controller of Accounts (CA) Integrated Pay & Principal Finance Accounts Accounts Division (IFD) Office (PAO) Office (PrAO) Drawing and Disbursing Officer (DDO) 2. The functions of each of the offices are provided as follows: • The IFD reports to the AS&FA and is responsible for reviewing and providing in-principle approvals for activities before their initiation, including commenting upon their financial status. • The CA is the head of the Departmental Accounting Organization and exercises this control with the assistance of senior accounts officers within the PAOs and PrAOs. Page 60 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) • The DDOs are responsible for presenting the claims/bills to the designated PAOs for processing payments. 3. There are four PAOs in the NSO, located across the country (New Delhi, Nagpur, Kolkata, and Bangalore), who are responsible for processing bills and making payments. The NSO consists of various divisions which are all headquartered in New Delhi, and financial transactions for them are processed through the PAO in New Delhi. A few divisions have regional and zonal offices across the country, and their financial transactions are processed by the respective PAOs. 4. The PrAO is responsible for preparation of monthly and annual accounts and their submission to the CGA office for consolidation. The PrAO is also entrusted with the responsibility to roll out the web- based application PFMS, including providing trainings and capacity building to the NSO staff. 5. MOSPI is implementing a World Bank-financed IPF project for the first time. An FM consultant will be appointed within the PMU to support the World Bank reporting requirements, primarily timely submission of IFRs for claim purposes, and will additionally support the day-to-day FM activities, as required. Adequate training on World Bank procedures will be provided to the consultant being onboarded. Planning and Budgeting 6. The process of annual budgeting at MOSPI starts through a budget circular issued by the MoF to each of the central government ministries/departments for budget proposal submission. MOSPI subsequently requests inputs from each of its divisions by September–October and consolidates the same as ‘Demand for Grants’ for submission to the MoF. The MoF presents the budget in the Parliament for discussion in January–February, which when finalized is the Budget Estimate (BE). The BE, as observed, is allotted to the Budget Controlling Officers (BCOs) in MOSPI in May–June, until which time the BCOs can spend one-sixth of their BE (for the months of April and May) for existing expenditures. In addition to the submission of BE, a Revised Estimate (RE) for the current financial year is also submitted. 7. Budget preparation and its approval in the Parliament, provisions for which are enshrined in the Constitution of India, go through legislative scrutiny. Funds can only be allocated after such approval, which is an effective instrument of financial control. The approved budgets/demand for grants are uploaded on the respective ministries’ website for public disclosure. The budget classification system as determined by the C&AG office is uniformly applied across the country. The budget and accounts present department-wise programs and activities which bring together all expenditures under appropriate functions (major), program (minor), and activities (subhead). 8. A separate account head for this project in the budget for FY 20-21 (demand for grants) has been created by the GoI. The details of the budget line are provided in the table below: 3454-02-02-204-26 National Programme for Improving Quality of Statistics in India (NPIQSI) – Census, Survey and Statistics major head 2552-188-06 National Programme for Improving Quality of Statistics in India (NPIQSI) – North Eastern Area (major head) Page 61 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) A separate budget line will facilitate easier tracking of the allocations, execution and financial reporting under the project. Flow of Funds 9. The World Bank funds will be provided to the GoI and will remain within the existing FM systems of the NSO. All guidelines followed for FM are according to the GFR 2017, and the Treasury operations are governed by the Central Treasury Rules of the GoI. There is no separate bank account maintained at the NSO, and all the transactions are routed through the PAO. Accounting 10. The project activities are centralized with the division headquarters at New Delhi and will be processed by the PAO based in New Delhi. No funds are being transferred to the states for this project. 11. All transactions pertaining to the project at the PAOs will be recorded in the PFMS. The PFMS was developed by the office of the CGA, under the MoF, GoI, as a fund-tracking and expenditure-filing system and is being expanded as the GoI’s IFMIS solution. The PFMS covers multiple financial activities such as budget distribution/allocation, funds management, treasury functions, electronic payments, and management of payroll system. It facilitates strengthening of the internal control framework through online distribution of budgets, online submission and approval of bills, electronic payments, and online generation of salary bills. Processing of Non-payroll Transactions in the PFMS 12. For each transaction, the invoices and supporting documents are received by the responsible officer who generates a sanction ID on the PFMS, which is received by the DDO. The DDO’s office generates and approves the bill with a unique number for each sanction. Once it is approved, the bill is submitted to the PAO online on the PFMS, along with a hard copy of the documents. The PAO reviews the bill and provides approval in the form of e-authorization, using a Digital Signature Certificate. Thereafter, the payment is initiated, and the details of the bill are passed on to the concerned bank through the PFMS. The bank reviews and makes payment to the concerned beneficiary. If the payment authorization fails at the bank, it goes back to the PAO through the PFMS and the PAO either reissues or cancels the payment. Processing of Payroll Transactions in the PFMS 13. The payroll of central government employees is processed in the Employee Information System (EIS) module of the PFMS. At the time of joining, a record of every central government employee is created in the EIS with a unique identification number. This EIS record is maintained in addition to the physical service book of the employees. At every month end, the DDO’s office generates and approves the pay bill in the EIS module and forwards the same to the PAO through the PFMS. Once the bill is approved by the PAO, the instructions are sent through the PFMS to the banks to transfer the payments electronically to the employees’ bank accounts. The GoI is in the process of integrating the existing e-Office application, containing leave records of employees, with the EIS to process deductions for leave automatically. Page 62 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Further, in the event of transfer of employees, the Last Pay Certificate is generated in the PFMS from the relieving office, and the salary in the newly assigned office is processed on the Last Pay Certificate. The PFMS also allows transfer of employee records from one office to the other in such cases. Processing of Payments for Procurements through GeM 14. The GeM portal will be used for procurement of small-value IT equipment. At the time of initiating procurement in GeM, the requisite amount will be blocked against an identified budget line. Upon satisfactory delivery of the goods, which will be recorded in GeM, the payment request will be passed automatically from GeM to the PFMS for the concerned PAO to process the same. The GeM and PAO systems are integrated and do not need manual intervention for data exchange. Beneficiary Verification in the PFMS 15. The PFMS portal has the functionality of processing a one-time beneficiary validation at the time of registration—the banking details provided by the beneficiary are uploaded in the PFMS, which interacts with the Core Banking System of approximately 100 banks and validates the same. Thus, the PFMS allows payments to be made to the beneficiary, minimizing the risk of ghost beneficiaries and double payments. Accounting in e-Lekha 16. The compilation of monthly transactions is passed from the PAO to the PrAO electronically—that is, from the PFMS to another web-based portal e-Lekha. At month end, the PrAO reviews the data in e- Lekha with the report received from the RBI and reconciles the balances. Based on this, the latter prepares the monthly accounts and submits to the CGA office for consolidation. Financial Reporting 17. There are currently no provisions for presenting a midyear budget execution report to the Parliament. The aggregated monthly accounts prepared by the CGA for the GoI, compiled from the departmental accounts, provide monthly accounts. These in-year budget execution reports are publicly disclosed on the CGA website. Reporting to the World Bank 18. The PMU will prepare IFRs from the expenditure records maintained in the PFMS by the PAO. IFRs will reflect the actual expenditures incurred under the EEP to support the DLIs achieved by the project. The IFRs will be submitted to the World Bank half-yearly within 45 days from the end of every such period. Internal Controls 19. The internal control framework at the GoI is embodied in the Budget Manual, General Financial Rules 2017, and Treasury Code read with the Store Purchase Manual and Works Manual, and other related employee rules. Key internal control arrangements in the project include (a) approval of activities by competent authorities, (b) processing of all payments on a web-based system by PAOs, (c) periodic reconciliation of accounts by the PrAO with RBI reports, and (d) deliverables approved by respective divisions within the NSO based on which payments will be initiated. Page 63 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 20. Procurement of IT equipment and accessories (tablets, laptops, printers, and so on) will be subject to annual verification and management systems at the NSO and its respective field offices. The controls include labelling of assets with a unique identifiable number and annual physical asset verification by the administration team at each of the offices. 21. A lean in-house Internal Audit team reporting to the CA within MOSPI conducts regular internal audits. During discussions, it was noted that the nature of audit is transaction based. Disbursement Arrangements 22. The applicable disbursement method will be ‘Reimbursement’. Disbursement will be made on the basis of satisfactory achievement of DLIs and verified according to the agreed verification protocol, supported by the adequate EEP. The basic principles governing the DLIs are as follows: • The project will submit reports showing the status of achievement of DLIs. This will be verified by the World Bank staff and, where appropriate, supported by an external expert/specialist consultant to be appointed by the project according to ToR agreed with the World Bank. • On validation of DLIs achieved, the project will seek reimbursement from the World Bank of an amount equivalent to the DLI value achieved. The World Bank, subject to the EEPs being adequate to cover the value of DLI(s) achieved, will disburse the full amount. Where the reported EEP is less than the aggregate DLI value achieved by the project, disbursement by the World Bank will be limited to the value of the reported EEP. The balance DLI value will be reimbursed when adequate EEP is reported subsequently. The reported EEP will be considered cumulatively. • In case the audited EEP is less than the reported EEP, the difference would be adjusted against disbursement of the subsequent DLI. DLIs 23. Nine DLIs have been agreed which support and incentivize achievement of desired project outputs/outcomes. In the pricing of individual DLIs, two factors have been considered: (a) the relative importance of the indicator and (b) the need to match disbursements with cash outflows on project activities. Table 2.1. List of DLIs with Annual Disbursement Values - Pricing of DLIs (US$, millions) DLIs FY20/21 FY21/22 FY22/23 FY23/24 FY24/25 Total DLI#1: Reduction in the average time lag between 0.000 1.500 1.500 1.500 1.500 6.000 end of fieldwork and public release of survey data DLI#2: Survey-related methodological studies 1.000 0.250 0.250 0.250 0.250 2.000 completed and published on MOSPI website DLI#3: Increase in the number of core surveys 0.925 1.000 1.000 1.000 1.000 4.925 released according to the adopted Advance Release Calendar (ARC) Page 64 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) DLIs FY20/21 FY21/22 FY22/23 FY23/24 FY24/25 Total DLI#4: Number of states incorporated into the 1.000 2.000 2.400 2.400 1.200 9.000 Statistical Business Register (SBR) DLI#5: National Quality Assurance Framework 0.500 0.500 0.500 0.500 0.500 2.500 (NQAF) is used for National Factsheet Indicators DLI#6: National Factsheet Indicators on Indian 0.250 0.250 0.250 0.250 0.250 1.250 economy are released quarterly on MOSPI’s website DLI#7: Beta statistics are publicly released on 0.000 0.000 0.250 0.250 0.250 0.750 MOSPI’s website DLI#8: Number of legacy surveys available for use in 0.000 0.000 0.600 0.300 0.600 1.500 the online tabulation tool DLI#9: Number of Layers accessible through online 0.400 0.400 0.400 0.400 0.400 2.000 mapping tool (incl. through APIs) Total 4.075 5.900 7.150 6.850 5.950 29.925 Eligible Expenditure Program (EEP) 24. The EEPs will consist of project-related investments (goods, non-consulting services, consulting services, training, and operating costs) and part of salaries of staff at the NSO. 25. The project-related investments include (a) the cost of appointing consultants (through an HR agency); (b) procurement of hardware and software and its maintenance cost during the project lifetime; (c) studies to augment the quality of statistics; (d) training, capacity building, communication, and change management; and (e) project management support, including consultants at the PMU and rental office space. The contract for appointment of a PMC is being funded by the GoI and is part of the counterpart funding—thus not within the EEP scope. 26. The achievement of the PDO is dependent on the core government staff of the NSO. A part of the salaries of the staff deployed at the following division headquarters of the NSO (in New Delhi) is accordingly considered in the EEP: i) NAD, ii) ESD, iii) SSD, iv) PSD and v) SSPU, the PMU for the project 27. The salaries of the above-mentioned divisions at the NSO are clearly identifiable in a separate budget head. Table 2.2 reflects the actual expenditure and budget estimates for the identified budget head: Table 2.2. Actual Expenditure and Budget Estimates for the Identified Budget head for salaries (INR, millions) 2018–19 2018–19 2017–18 2019–20 Budget head Budget Revised Actuals Budget Estimates Estimates Estimates 3454-02-02-204-01-01-01 345 397 395 416 28. As this staff will be responsible for delivering the World Bank-funded project in addition to other responsibilities, it has been agreed to include 30 percent of the NSO salaries as attributable EEP for the project. Page 65 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Table 2.3. Detailed Breakup EEP for the Project (INR, millions) Particulars Year 1 Year 2 Year 3 Year 4 Year 5 Total Consultants 366.60 366.60 366.60 366.60 366.60 1833.00 NSO staff salaries 120.00 120.00 120.00 120.00 120.00 600.00 Hardware/software 142.00 145.00 74.00 84.00 84.00 529.00 Studies/surveys 0 157.50 75.00 75.00 92.50 400.00 Capacity building and e-course development 14.80 74.80 59.80 29.80 14.80 194.00 Workshops/seminars/conferences 46.00 46.00 43.80 43.80 40.00 219.50 Travel 8.10 8.10 8.10 8.10 8.10 40.50 Advocacy (SDGs) 0 20.00 10.00 10.00 10.00 50.00 Innovation budget 0 29.0 25.00 25.00 25.00 104.00 Consultants housed within the PMU 50.00 50.00 50.00 50.00 50.00 250.00 Operating cost 6.00 8.50 8.50 8.50 8.50 40.00 Total (year-wise) 750.00 1030.00 840.80 820.80 819.50 4260.00 Total (year-wise) in US$, millions 10.61 14.44 11.84 11.56 11.54 60.00 Disbursement Schedule 29. Loan funds will be disbursed against the DLIs achieved, under the following category(ies) subject to the allocated amount, reported EEP, and the disbursement percentage as indicated in Table 2.4: Table 2.4. Project Categories, Amount of Loan Allocated and Percentage Expenditure to Be Financed Amount of the Loan Percentage of Expenditures to Category Allocated Be Financed (US$) (Inclusive of Taxes) (1) EEP under Components 1–4 of the 29,925,000 53% of the amount of EEP project, except the contract for services of reported a PMC (2) Services of a PMC 0 0% (3) Front-end fee 75,000 Amount payable pursuant to Section 2.03 of Legal Agreement in accordance with Section 2.07 (b) of the General Conditions (4) Interest Rate Cap or Interest Rate Collar Amount due pursuant to premium Section 4.05 (c) of the General Conditions Total Amount 30,000,000 50% External Audit 30. The C&AG will be the external auditor for the project. The scope of audit will be according to the ToR agreed with the office of the C&AG. The audit report for the project will be submitted by the PMU to the World Bank within nine months from the close of the financial year. Page 66 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Implementation Support 31. As implementation progresses, it will involve review of financial and audit reports. In the initial years, the project staff may require support/training on project FM and disbursement procedures and guidance on contract management. The World Bank will undertake at least semiannual implementation support missions to ensure that agreed FM arrangements are appropriately followed. Conclusion 32. The project has acceptable FM arrangements to account for and report on project expenditures including (a) use of funds in an efficient and economical manner for the purposes intended, (b) preparation of accurate and reliable periodic financial reports, and (c) acceptable audit/assurance arrangements. FM arrangements for the project are fully reliant on ‘use of country systems’, that is, predicated on the GoI’s extant systems which are assessed as satisfactory. 33. The fiduciary (FM) risk for the project is being assessed as Moderate. The project has centralized accounting at the New Delhi PAO and will follow standardized processes on web-based portals. This will be the first experience for the NSO to implement a World Bank-funded IPF lending instrument. To ensure smooth project implementation, regular hand-holding support in the initial phase is proposed along with the appointment of an FM consultant to further strengthen the PMU. Page 67 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) ANNEX 3: Procurement COUNTRY: India National Programme for Improving the Quality of Statistics in India 1. Applicable procurement rules. The procurement of goods and consulting and non-consulting services to be financed by the loan will be carried out in accordance with the World Bank’s Procurement Regulations for IPF Borrowers (dated July 2016; revised November 2017 and August 2018), and the provisions of the Loan Agreement. No works procurement is envisaged. If there is conflict between government decrees, rules, and regulations and the World Bank Procurement Regulations, then World Bank’s Procurement Regulations shall prevail. The project will use the online tool STEP to prepare, clear, and update its Procurement Plan, for monitoring procurement activities and for communication between the borrower and the World Bank. Unless otherwise agreed with the World Bank, the World Bank’s Standard Procurement Documents, RFPs, and Forms of Consultant Contract will be used. Procurement under national procedures will be carried out based on National Procurement Procedures conditions agreed with the GoI. The Project will make use of Government of India’s National Informatics Centre (NIC) platform, assessed against Multilateral Development Bank (MDB) requirements, to carry out bidding in the Project for procurement of goods, consulting and non-consulting services. 2. Summary from PPSD. The project has prepared its PPSD document which has involved a supply market analysis to facilitate a satisfactory procurement outcome. According to its PPSD, procurement spend is approximately 54 percent of the World Bank loan (US$30 million) and approximately 33 percent of the total project cost. Based on the need assessment including of various divisions of MOSPI, the project may use GeM for procurement of goods and non-consulting services up to the threshold for RFQ, that is, US$100,000. Based on the PPSD, a Procurement Plan has been prepared to set out the selection methods to be followed during project implementation in the procurement of goods and non-consulting and consultancy services financed by the World Bank. The category-wise breakdown of procurement spend is as follows: Table 3.1. Category-wise Breakdown of Procurement Spend Approximate Approximate Category of Procurement Procurement Spenda Category of Procurement Procurement Spendc (INR, crores) (INR, crores) Goods 40.90 Goods 40.90 Non-consulting services 10.00 Non-consulting services 10.00 Consultancy servicesb 63.75 Consultancy servicesd 88.75 Total 114.65 Total 139.65 Note: a. Approximately 54 percent of World Bank loan of INR 213 crores; b. Excludes PMC cost of INR 25 crores; c. Approximately 33 percent of total project cost of INR 426 crores; d. Includes PMC cost of INR 25 crores. 3. Procurement profile under the project is likely to include, but is not limited to, the following: Page 68 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Table 3.2. Procurement Profile under the Project Selection Methods and Market Procurement Activity Description, Category Approach Options; Approximate Remarks and Approximate/Estimated Cost Estimated Duration of Contract Selection of PMC Consultancy RFP - Quality- and Cost-Based The contract is services Selection (QCBS) expected to be signed Approximate cost: US$3.5 million by the end of PMC selection following QCBS is February 2020. Approximately 5.8% of the total being financed 100% using GoI project cost funds. 36 months (extended until project completion period depending on need and performance) Selection of an IVA to verify Consultancy –Direct Selection IVA selection is achievement of DLRs services Lump-sum payment proposed as per provisions of Approximate cost: US$0.175 million 60 months Paragraph 3.23 (c) of Section III of the Approximately 0.3% of the total Regulations project cost Hiring of HR and payroll Non- Request for Bids (RFB) - Open management firm consulting services 60 months Approximate cost: US$1.4 million (excluding reimbursable/pass- through expenditure) Approximately 2% of the total project cost Selection of a firm for third-party Consultancy RFP - QCBS assessment of Computer Aided services General Survey Instrument for the 12 months DQAD of MOSPI Approximate cost: US$0.036 million Approximately 0.06% of the total project cost Selection of a firm for third-party Consultancy RFP - QCBS assessment of NQAF for survey data services for the DQAD of MOSPI 12 months Approximate cost: US$0.036 million Approximately 0.06% of the total project cost Selection of a firm for third-party Consultancy RFP - QCBS assessment of NQAF for services Page 69 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Selection Methods and Market Procurement Activity Description, Category Approach Options; Approximate Remarks and Approximate/Estimated Cost Estimated Duration of Contract administrative data quality of 12 months different divisions of MOSPI Approximate cost: US$0.285 million Approximately 0.47% of the total project cost IT equipment (multiple procurement Goods RFB - Open Multiple procurement packages) packages according to 3–6 months project design, for Approximate cost: US$4.4 million example, e-learning centers are to be Approximately 7.31% of the total established in Year 3 project cost of the project. Requisite software and related Goods RFB - Open hardware for digitization of UFS for GIS Mapping 3-– months Approximate cost: US$1.4 million Approximately 2.3% of the total project cost Consultancy for e-courses Consultancy RFP - QCBS development (courses spread out services over project period) Lump-sum payment Approximate cost: US$1.4 million 18 months Approximately 2.3% of the total project cost Consultancy for preparation of Consultancy RFP - QCBS Contract is proposed documentary videos for advocacy on services to be extended based SDGs Lump-sum payment on performance. Approximate cost: US$0.5 million 12 months Approximately 0.82% of the total project cost Consultancy for fieldwork and Consultancy RFP - QCBS production of NCAs for SSD services Lump-sum payment Approximate cost: US$5.0 million 36 months Approximately 8.3% of the total project cost Pilot surveys for SDGs Consultancy RFP - QCBS services Page 70 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Selection Methods and Market Procurement Activity Description, Category Approach Options; Approximate Remarks and Approximate/Estimated Cost Estimated Duration of Contract Approximate cost: US$0.215 million Lump-sum payment Approximately 0.36% of the total 36 months project cost Table 3.3. Procurement and Contract Approaches Best and Final Offer No Negotiations No 4. Client capability assessment. The project will be directed, controlled, monitored, and coordinated by the PMU established for the project under the CAP vertical of the NSO under the auspices of MOSPI. The PMU, MOSPI, will be headed by the designated project director and will be aided by the PMCs hired under the project. Activities under the project will cover procurement requirements of various divisions under MOSPI such as the FOD, DQAD, SDRD, DIID, SSD, ESD, NAD, and PSD, some of which have regional and zonal offices (for example, the FOD and DQAD) as their extended arms of implementation in various cities of India. While MOSPI has implemented the World Bank-financed Development Policy Loan under the Statistical Strengthening Project in 2010–2011, it has no experience of or exposure to the World Bank’s applicable Procurement Regulations and their requirements. Contract management systems are also not well established. Other risks identified include limited and weak procurement capacity regarding selection of consulting services including development of market-responsive ToR and provision of oversight and monitoring of results. 5. Mitigation measures agreed with the client include providing training in the World Bank’s Procurement Framework. The PMC will have a procurement expert to provide procurement-related support and coordinate with various divisions of MOSPI on their procurement requirements. Timely disclosure of procurement and contract award information and timely audits will facilitate bringing in transparency and accountability in the procurement process. Redress of procurement-related complaints in accordance with provisions of the Procurement Regulations will contribute to mitigating the risk of discretion and/or external interference in the procurement process and instill confidence in the bidding community. The World Bank will arrange for training in the World Bank’s Procurement Framework and provide handholding support on a need basis. 6. Procurement capacity building. It is recommended that key procurement staff of the PMU, MOSPI, be sent to Indian Institute of Management, Lucknow, or the Administrative Staff College of India, Hyderabad, from time to time to attend procurement training on the World Bank Procurement Framework applicable to the project. The project can also avail of the free Massive Open Online Course on public procurement (www.procurementlearning.org) offered by the World Bank to build their capacity. 7. Procurement planning. For each contract to be financed by the loan, the different procurement methods or consultant selection methods to be used, the need for prequalification, estimated costs, prior- review requirements, and time frame will be reflected in the Procurement Plan to be agreed between the borrower and the World Bank team. The Procurement Plan will be uploaded in STEP by the PMU, MOSPI, and the approved Procurement Plan will be disclosed on the project website and the World Bank’s Page 71 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) external website. The Procurement Plan for the first 18 months of project implementation will be submitted to the World Bank through STEP; will lay out the appropriate, fit-for-purpose market approach and selection methods for procurement of goods and non-consulting and consulting services financed by the World Bank; and will be updated at least annually or as required to reflect the actual project implementation needs and improvements in institutional capacity. 8. STEP. The project will implement STEP, a World Bank procurement planning and tracking system, which would provide data on procurement activities and establish meaningful and measurable benchmarks. The World Bank will arrange STEP training for nominated officials involved in the procurement transaction in the project. 9. Operating costs. As defined in the Appendix to the Legal Agreement pertaining to this project, operating costs mean the reasonable and necessary expenditures incurred by the project implementing entity including costs of operation; rent and maintenance of offices; utilities; communication costs, and training and travel allowances of project beneficiaries and project staff related to project implementation, coordination, and monitoring. 10. eProcurement. Currently, MOSPI is using the eProcurement system for its procurement. The project shall enhance its capacity for eProcurement and shall make use of the GoI’s NIC platform assessed by the World Bank against MDB requirements for procurement of goods and consulting and non- consulting services estimated at INR 2 lakhs and above. 11. Advance contracting for project readiness. For effective project implementation and timely start- up, the project has initiated advance contracting of selection of PMCs estimated at the equivalent of US$3.5 million approximately (approximately 5.8 percent of the total project cost) to be financed 100 percent using GoI funds. 12. Record keeping. All records pertaining to award of tenders/selection of consultants, including tender notification/advertisement, register pertaining to sale and receipt of bids, bid/proposal opening minutes, bid/technical and financial evaluation reports and all correspondence pertaining to bid evaluation, communication sent to/with the World Bank in the process, bid securities, and approval of invitation/evaluation of bids/proposals would be maintained by the PMU, MOSPI. 13. Contract management. The PMU, MOSPI, under the overall guidance and oversight of the designated project director will be responsible for overall procurement and contract management under the project. Contract management (other than for the PMC, IVA and HR firm) will be decentralized to various divisions of MOSPI. The procurement official at the PMU, MOSPI, aided by the PMC and identified thematic area experts from various divisions of MOSPI will monitor progress and supervise overall implementation of procurement activities to ensure that the intended benefits and outcomes of contracts under the project are achieved on time, within the estimated budget, adhering to health and safety requirements, avoiding and managing complaints and disputes that may arise effectively and fairly, and ensuring that timely payments are made to suppliers/vendors/contractors/consultants contracted under the project. 14. Complaint-handling mechanism. A complaint-handling mechanism to address procurement- related complaints under the project will be developed and implemented by the PMU, MOSPI, to the Page 72 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) satisfaction of the World Bank. Upon receipt of complaints, immediate action would be initiated to acknowledge the complaint and to redress it within a reasonable time frame. All complaints will be addressed at levels higher than the level at which the procurement process was undertaken, or the decision was taken. Any complaint received will also be forwarded to the World Bank for information, and the World Bank would be kept informed after the complaint is redressed. 15. Procurement thresholds and prior review thresholds. Table 3.1 describes various procurement methods to be used for activities financed by the loan. Table 3.4. Procurement Thresholds Procurement Approach and Method Thresholds (US$ equivalent) Open International (Goods, IT, and non-consulting >10 million services) - RFB Open National (Goods, IT, and non-consulting >100,000 and up to 10 million services) - RFB National RFQ (Goods/non-consulting services) Up to 100,000 Direct Selection With prior agreement, based on justification Framework Agreement For goods/non-consulting services: According to paragraphs 6.57–6.59 of Section VI of the Procurement Regulations For consulting services: According to paragraph 7.33 of Section VII of the Procurement Regulations. According to paragraph 46 of Section VI of the Commercial Practices Regulations Consulting services (Firms) CQS Consultant’s Qualifications Based Selection: According to requirements of paragraphs 7.11 and 7.12 of Section VII of the Procurement Regulations Least Cost Based Selection, Fixed Budget Based Selection: In justified cases QCBS, Quality-Based Selection: In all other packages Short list of national consultants Up to 800,000 16. Procurement prior review thresholds.17 Based on the current procurement risk rating of ‘Moderate’, the World Bank will prior review the following contracts: (a) Goods and IT: All contracts > US$4 million equivalent (b) Non-consulting services: All contracts > US$4 million equivalent (c) Consulting services - Firms: All contracts >US$2 million equivalent 17Determination of whether a contract meets the prior review threshold is based on the following: (a) the total value of the contract, including all taxes and duties payable under the contract; (b) a contract whose cost estimate was below the World Bank’s prior review threshold is subject to prior review if the price of the lowest evaluated responsive bid (or, in the case of consulting services, the financial offer of the selected firm) exceeds such threshold at the bid evaluation stage; and (c) in the case of a slice and package arrangement, the prior review threshold is determined based on the aggregate value of individual contracts to be awarded under such arrangement. Page 73 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) (d) Consulting services - Individuals: All contracts > US$400,000 equivalent (e) Direct selection: The justification of Direct Selection for all contracts 17. The above thresholds are for the initial 18-month implementation period. Based on the procurement performance of the project, these thresholds may be subsequently modified. Even for large- value post review cases, the inputs of the World Bank on technical specifications will be obtained by the project. Irrespective of the thresholds, ToR shall be prior reviewed by World Bank. The prior review thresholds will also be indicated in the Procurement Plan. The Procurement Plan will be subsequently updated annually (or at any other time if required) and will reflect any change in the prior review thresholds. The details of National Procurement Procedures are outlined in the Procurement Plan. 18. Prior review contracts. In the case of contracts subject to prior review, the PMU, MOSPI, will seek the World Bank’s no-objection before granting/agreeing to (a) an extension of the stipulated time for performance of a contract that either increases the contract price or has an impact on the planned completion of the project; (b) any substantial modification of the scope of goods, IT system; non- consulting services, or consulting services and other significant changes to the terms and conditions of the contract; (c) any variation order or amendment (except in cases of extreme urgency) that, singly or combined with all variation orders or amendments previously issued, increases the original contract amount by more than 15 percent; and (d) the proposed termination of the contract. Complaints received in all prior review cases shall be sent to the World Bank for review and the response to the complaint in such cases shall be cleared with the World Bank. Complaints with allegations of fraud and corruption shall be shared with the World Bank, irrespective of the thresholds. 19. Disclosure of procurement information. The following documents shall be disclosed on the project website: (a) Procurement Plan and its updates; (b) an invitation for bids for procurement of goods, IT systems, and non-consulting services; (c) Request for Expression of Interest for selection/hiring of consulting services; (d) contract awards of goods, IT system procurement, and non-consulting services procured following international and national procedures; (e) a list of contracts/purchase orders placed following RFQ procedures on a quarterly basis; (f) a list of contracts following direct contracting on a quarterly basis; (g) an annual financial and physical progress report of all contracts; and (h) an action taken report on the complaints received on a quarterly basis. 20. The following details shall be sent to the World Bank for publishing on the United Nations Development Business and the World Bank external website: (a) Specific Procurement Notice (that is, invitation for bids) for procurement of goods, IT systems, and non-consulting services using open international procedures; (b) Requests for Expression of Interest above US$800,000; (c) contract award details of all procurement of goods, IT systems, and non-consulting services using open international procedure; and (d) a list of contracts/purchase orders placed following Direct Contracting/Selection procedures on a quarterly basis. Further, the implementing agency will also publish on their websites any information required under the provisions of ‘suo moto’ disclosure as specified by the Right to Information Act. 21. National Procurement Procedure conditions. National competition for the procurement of goods, IT systems, and non-consulting services according to the established thresholds will be conducted Page 74 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) in accordance with paragraphs 5.3–5.5 of Section V of the Procurement Regulations and the following provisions: (a) Only the model bidding documents for National Competitive Procurement agreed with the GoI Task Force (and as amended for time to time) shall be used for bidding. (b) Invitations to bid shall be advertised on a widely used website or electronic portal with free open access at least 30 days before the deadline for the submission of bids, unless otherwise agreed in the approved Procurement Plan. (c) No special preference will be accorded to any bidder either for price or for other terms and conditions when competing with foreign bidders, state-owned enterprises, small-scale enterprises, or enterprises from any given state. (d) Except with the prior concurrence of the World Bank, there shall be no negotiation of price with the bidders, even with the lowest evaluated bidder. (e) GeM set up by Ministry of Commerce, GoI, will be acceptable for procurement under RFQ method. (f) At the borrower’s request, the World Bank may agree to the borrower’s use, in whole or in part, of its electronic procurement system, provided that the World Bank is satisfied with the adequacy of such system. (g) Procurement will be open to eligible firms from any country. This eligibility shall be as defined under Section III of the Procurement Regulations. Accordingly, no bidder or potential bidder shall be declared ineligible for contracts financed by the World Bank for reasons other than those provided in Section III of the Procurement Regulations. (h) The RFB/RFP document shall require that bidders/proposers submitting bids/proposals include a signed acceptance in the bid, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s Anticorruption Guidelines, including without limitation the World Bank’s right to sanction and the World Bank’s inspection and audit rights. (i) The borrower shall use an effective complaints mechanism for handling procurement- related complaints on time. (j) Procurement documents will include provisions, as agreed with the World Bank, intended to adequately mitigate against environmental, social (including sexual exploitation and abuse and gender-based violence), health, and safety risks and impacts. 22. Oversight and monitoring by the World Bank. All contracts not covered under prior review by the World Bank will be subject to post review during implementation support missions and/or special post review missions, including missions by consultants hired by the World Bank. High-risk procurements, if any, will be identified for increased procurement and contract management support and indicated in the Procurement Plan. The World Bank team will provide additional due diligence and independent review of the contract performance of such identified procurements. Page 75 of 77 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 23. Frequency of procurement supervision. The World Bank will normally carry out implementation support missions, including review and support on procurement, on a semiannual basis. Mission frequency may be increased or decreased based on the procurement performance of the project. Page 76 of 77