The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) Note to Task Teams: The following sections are system generated and can only be edited online in the Portal. Please delete this note when finalizing the document. Project Information Document (PID) Concept Stage | Date Prepared/Updated: 18-Jul-2019 | Report No: PIDC27334 Sep 11, 2019 Page 1 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) BASIC INFORMATION A. Basic Project Data OPS TABLE Country Project ID Parent Project ID (if any) Project Name Tonga P171377 Statistical Innovation and Capacity Building in Tonga (P171377) Region Estimated Appraisal Date Estimated Board Date Practice Area (Lead) EAST ASIA AND PACIFIC Oct 21, 2019 Feb 11, 2020 Poverty and Equity Financing Instrument Borrower(s) Implementing Agency Investment Project Financing Tonga Ministry of Finance Tonga Department of Statistics (TDOS) Proposed Development Objective(s) To improve the efficiency of HIES implementation, quality of data production, and accessibility of welfare data in Tonga. PROJECT FINANCING DATA (US$, Millions) SUMMARY-NewFin1 Total Project Cost 1.50 Total Financing 1.50 of which IBRD/IDA 1.50 Financing Gap 0.00 DETAILS -NewFinEnh1 World Bank Group Financing International Development Association (IDA) 1.50 IDA Grant 1.50 Environmental and Social Risk Classification Concept Review Decision Low Track II-The review did authorize the preparation to continue Sep 11, 2019 Page 2 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) Other Decision (as needed) B. Introduction and Context Regional Context 1. The Pacific Island Countries (PICs) are characterized by small populations spread across vast areas. There are eleven Pacific small island countries that are members of the World Bank: Fiji, Kiribati, the Republic of the Marshall Islands, Federated States of Micronesia, Nauru, Palau, Samoa, Solomon Islands, Tonga, Tuvalu, and Vanuatu. These countries have a combined population of about 2.3 million spread across 640 inhabited islands over an ocean area of more than 30 million square km, equivalent to 15 percent of the globe’s surface and approximately the same as the combined area of China, Canada, and the United States. Each of these countries share similar challenges and opportunities as small and remote island economies. They are small in size with limited natural resources, narrowly-based economies, large distances away from major markets, and vulnerable to external shocks; all of which can affect growth and have often led to a high degree of economic volatility. 2. Within the Pacific region, there is substantial heterogeneity between countries. Buoyed by tourism from Asia and the United States, Palau is the richest country in the region, with a higher GDP per capita than the average for developing counties in the East Asia and Pacific Region (see Figure 1) and similar to countries in Central Europe. In contrast, Kiribati, an atoll country increasingly impacted by climate change, has the lowest GDP per capita in the region with a value closer to those found in sub-Saharan Africa. There are also differing access to opportunity. Though the total number of Pacific-born migrants living in OECD countries is now more than 400,000, nearly all (79 percent) come from three countries, Fiji, Samoa, and Tonga.1 An addition 15 percent come from countries with open access agreements (FSM, Marshall Islands and Palau). Five percent came from PNG, Solomon Islands, Vanuatu, with almost none coming from the two atoll countries (Kiribati and Tuvalu). 1 Curtain, Richard Leigh; Dornan, Matthew Selwyn; Doyle, Jesse Jon Gerome; Howes, Stephen. 2017. Labour mobility: the ten billion dollar prize (English). Pacific possible series; background paper no. 1. Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/171661503669342316/Labour-mobility-the-ten-billion-dollar-prize Sep 11, 2019 Page 3 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) Figure 1: GDP per capita 2017 (Current USD) PALAU NAURU EAST ASIA & PACIFIC* FIJI SAMOA TONGA MARSHALL ISLANDS TUVALU MICRONESIA, FED. STS. VANUATU SOLOMON ISLANDS KIRIBATI 0 5000 10000 15000 * EXCLUDES HIGH INCOME 3. In addition, there are within-country disparities in standard of living. There are often important differences between the populations living on the “outer islands� compared to those living on the main island. Those living on the outer islands typically do not have the same access to public services, infrastructure, and economic opportunities, and are therefore more vulnerable and more likely to suffer hardship compared to people living on the main island. There has also been substantial international and inter-island migration in response to climate change and in search of economic opportunities. For the outer islands, this often creates a skewed population structure with only the elderly and sometimes women and children remaining on the outer island, while men look for better income opportunities on the main islands. A more limited number of physically fit people means that activities such as agriculture are reduced, adding to the risks of poverty, fragility, and vulnerability. In some cases, certain settlements may be abandoned entirely. Sectoral and Institutional Context 4. Data deprivation in the PICs hinders evidence-based policy making. Policymakers must consider a range of complex trade-offs regarding service delivery and investments at the national level and identifying priorities in the context of the challenges they face. The evidence based for these decisions, however, is thin. Data collection in the Pacific Island countries lags behind many regions in the developing world in terms of data quality, frequency of collection, and the timeliness of results. 5. Beyond data deprivation, public access to the collected data is another challenge facing the region. Data collection in and of itself is not sufficient: in order to maximize the benefits of the data, it must be made accessible to various stakeholders in the government, donor, academic, NGO, and civil society sectors. Before this can occur, NSOs must first anonymize the data sets to protect the identities of the surveyed households and people. However, anonymization is much more complex in countries with small and highly dispersed populations, as it becomes easier to uniquely identify people based on a broader range of variables. Thus, this process is more costly and time-consuming in the Pacific, and data sets are often only available several years after the surveys are conducted, if at all. Sep 11, 2019 Page 4 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) 6. National Statistics Offices (NSOs) lack funding to meet the prohibitive costs of data collection in the Pacific. The per-interview costs of data collection in the Pacific are some of the highest in the world. These outcomes are partially the result of systemic issues, including sparse populations and high travel costs due to the island geography. However, these issues are compounded by outdated methodologies and inefficient use of technology. Although the systemic challenges will remain a significant factor in data collection costs in the Pacific, there is scope to substantially reduce costs by integrating proven methods from other parts of the world. One example is switching from a diary method for collecting consumption data to a recall method, which can reduce the number of days required at each location, thereby decreasing personnel costs, a significant component of the survey budget. In addition, integrating new technology, such as Computer Assisted Personal Interviewing (CAPI), reduces the need to print and transport paper questionnaires, which has decreased the costs of data collection in certain contexts despite the upfront cost of hardware investment. Box 1. Data deprivation and gender gaps in the Pacific Gender gaps are substantial in the Pacific Island Countries. The World Economic Forum’s 2017 Global Gender Gap includes reporting on Fiji, which was ranked 125th out of 144 countries. Data on labor force participation (Table 1 below) shows large gender gap across the Pacific. Various national surveys point to a large incidence of violence against women, with over half of women in Fiji, the Solomon Islands, Vanuatu, Kiribati, and the Marshall Islands ever experiencing physical and/or sexual violence by an intimate partner during their lifetimes. Table 1. Gender gaps in labor force participation, 2017 Country Male LFP (15+) Female LFP (15+) Gender gap (M – F) Fiji 75.4 40.8 34.6 Samoa 38.9 23.7 15.2 Solomon Islands 80.3 62.5 17.8 Tonga 74.2 45.1 29.1 Vanuatu 79.6 61.5 18.1 Source: World Development Indicators However, the limited availability of data in the Pacific hinders any effort to track progress over time and design policies to address the gender gap in the Pacific. For example, data on labor force participation is only available for the 5 countries above, and not for the remaining 6 PICs that are World Bank member states. PICs rarely conduct Demographic and Health Surveys or Family Health and Safety Studies that typically ask questions on violence against women. The long gaps between HIES rounds has also hindered the tracking of health and education outcomes, as well as other outcomes that specifically tracked for SDG Goal 5, such as asset ownership, mobile phone ownership, and time spent on unpaid domestic and care work. Even when the surveys are conducted, the presentation of gender-disaggregated statistics is not yet commonplace, as can be seen in Table 2 below. Thus, any effort to improve the monitoring of gender outcomes and design of gender-specific policies must include improvements in data collection. Table 2. Presentation of gender-disaggregated data in reporting based on latest HIES surveys Country Latest HIES/ Gender-disaggregated indicator poverty Health Mobile Total # of Education & report P0 by gender access or Labor force phone disaggregated poverty, by of HH head outcomes by stats, by sex ownership indicators in sex sex or use document Fiji 2013/14 N N N N N 0 FSM 2013/14 Y N N N N 1 Kiribati 2014 Y N Y Y N 5 Nauru 2012/13 Y Y Y Y N 6 Sep 11, 2019 Page 5 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) Palau 2014 Y N N N N 3 (expenditure) RMI 2002 Y (income) Y N Y N 8 Samoa 2012/13 Y Y N Y N 3 Solomon 2012/13 Y N N N N 1 Islands Tonga 2016 N N Y Y Y 5 Tuvalu 2010 N Y Y Y N 11 Vanuatu 2010 Y Y N Y N 6 7. Low statistical capacity is another major challenge in addressing data deprivation. According to the World Bank’s Statistical Capacity Index2, the PICs rank below the EAP developing country average. In particular the scores for Source Data, which measures if a country meets international recommendations for collecting five key data sources (agricultural census, health survey, population census, poverty survey, and vital registration system coverage), are well below the EAP average (see Figure 2). Figure 2: Statistical Capacity Index (2017) EAST ASIA & 100 PACIFIC* FIJI 90 KIRIBATI 80 MARSHALL ISLANDS 70 MICRONESIA, FED. STS. 60 NAURU 50 PALAU SAMOA 40 SOLOMON ISLANDS 30 TONGA 20 TUVALU 10 VANUATU 0 METHODOLOGY PERIODICITY SOURCE DATA STATISTICAL * EXCLUDES HIGH INCOME ASSESSMENT CAPACITY INDEX Source: World Bank, datatopics.worldbank.org/statisticalcapacity 2 The World Bank’s Statistical Capacity Indicator is a composite score assessing the capacity of a country’s statistical system . It is based on a diagnostic framework assessing the following areas: methodology; data sources; and periodicity and timeliness. Countries are scored against 25 criteria in these areas, using publicly available information and/or country input. The overall Statistical Capacity score is then being calculated as simple average of all three area scores on a scale of 0-100. See datatopics.worldbank.org/statisticalcapacity for more detail. Sep 11, 2019 Page 6 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) 8. There has been some improvement in statistical capacity over time, but results cannot be sustained. Figure 3 below shows the overall SCI rating for the eleven PICs from 2005 to 2017. With the exception of high income Palau, countries have shown uneven progress. Since the measure depends on the periodicity of data collection, countries will improve immediately after completing a survey. Since funding, however, is irregular and often sourced from development partners, the periodicity cannot reliably be maintained, and the SCI score falls again as the data ages. To break this cycle and increase sustainability, data collection must become more affordable. Figure 3: Statistical Capacity Index (2005 - 2017) 85 EAST ASIA & PACIFIC* FIJI 75 KIRIBATI 65 MARSHALL ISLANDS M I C R O N E S I A , F E D . 55 STS. NAURU 45 PALAU SAMOA 35 SOLOMON ISLANDS 25 TONGA 15 * EXCLUDING HIGH INCOME 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Source: World Bank, datatopics.worldbank.org/statisticalcapacity 9. Secretariat of the Pacific Community – Statistics for Development Division (SPC-SDD) is a key stakeholder in addressing the statistical capacity gap in the region, but it too suffers from resource and capacity issues. SPC-SDD’s primary goal is to “strengthen access to and use of development statistics in policy development and monitoring progress�. SPC-SDD is charged with providing direct support to NSOs in the PICs in conducting data collection, including household surveys, censuses, administrative statistics, price measures, etc., for their 21 member countries and territories (12 of which are World Bank members)3. SPC-SDD has a six-member Statistical Collection team which provides technical assistance on household survey and census rounds, as well as in cleaning and compiling the data. As the complexity of surveys and frequency of data collection has increased in recent years, SPC-SDD has found itself lacking the human and financial resources, as well as the technical capacity, to provide this retail support to its member countries in an adequate manner, particularly regarding improved methods and data analysis. Therefore, the Pacific region lags other parts of the world in adopting new surveying methods and implementing technological improvements. With regard to analysis, other development partners, such as the World Bank, Asian Development Bank, and United Nations Development Programme, have led poverty analysis using the data, mainly through consultants. However, due to the disconnect between the data 3 The Pacific Island Countries and Territories that are SPC members include: American Samoa, Cook Islands, Federated States of Micronesia, Fiji, French Polynesia, Guam, Kiribati, Marshall Islands, Nauru, New Caledonia, Niue, Northern Mariana Islands, Palau, Papua New Guinea, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, Vanuatu, and Wallis and Futuna. Highlights indicate WB member states. SPC membership also includes Australia, France, New Zealand, Pitcairn Islands, and the United States of America. Sep 11, 2019 Page 7 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) collection/cleaning and the analysis, and the lack of continuity and documentation between rounds, it is difficult for countries issue survey reports in a timely manner and to measure national trends in poverty and other key socioeconomic statistics. 10. The SPC-SDD 2018-2020 Business Plan marks a shift in SPC-SDD’s role to a “statistical system leader�. Going forward, SPC-SDD will shift from its retail approach to a role as “coordinator, broker, convenor, promoter and system leader� for statistics in the PICs. Rather than providing technical assistance on its own, the Business Plan calls for SDD to leverage the technical expertise of other development partners and international experts, while also playing a leadership role in the harmonization and modernization agenda through improved documentation and coordination. 11. The Pacific Statistics Methods Board has potential to accelerate the adoption of new methods for data collection and statistical analysis. The PSMB is a newly-formed body that illustrates the changing role of SDD. The PSMB was formed in 2017 as a technical body under the Heads of Planning and Statistics (HOPS) meeting and the Pacific Statistics Standing Committee (PSSC), reporting its key decisions, progress, and achievements to PSSC during their annual meetings. The purpose of the board is to “ensure that relevant best practice standards are developed and are fit for purpose for use in Pacific Island countries and territories for a suite of core censuses and surveys�. The terms of reference for the PSMB charge the group with promoting standardization and harmonization in the methodologies adopted by NSOs in the PICs, seeking out opportunities to incorporate the latest innovations in data collection, and conducting rigorous assessments of feasibility and suitability of these new methods to the Pacific context. The members include Statistics New Zealand (chair), the Australian Bureau of Statistics, UN agencies, and one NSO representative from each of the four Pacific regions: Micronesia, Melanesia, Polynesia, and the small island states, with the World Bank holding observer status. The 2017 HOPS meeting tasked SPC-SDD to provide secretariat support to the PSMB. Relationship to CPF 12. Closing data gaps is a corporate priority for the region. Fiji and Solomon Islands have Country Partnership Frameworks and there is a Regional Partnership Framework for remaining nine Pacific Island countries (Kiribati, Marshall Islands, Federated States of Micronesia, Nauru, Palau, Samoa, Tonga, Tuvalu, and Vanuatu). The latter document, in particular, highlighted significant gaps in socio-economic indicators in most of the PICs. Overall the three documents emphasize the necessity of having a solid foundation for evidence-driven policymaking. 13. The Regional Partnership Framework for the PIC9 emphasizes the need to address persistent knowledge gaps. The RPF highlighted the lack of concrete information on the prevalence and severity of poverty and the specific nature of constraints faced by the poor, as well as the uneven quality and inconsistent methodologies in HIES implementation and poverty analysis. As such, the RPF explicitly lists addressing knowledge gaps as Objective 4.3 and states the need to: 1) provide technical assistance to NSOs and SPC to enhance their data collection and analysis capabilities, and 2) develop and pilot low-cost survey approaches that are financially sustainable. 14. The Solomon Islands CPF points to several key knowledge gaps that hindered the systematic country diagnostic process. Compared to other NSOs in the Pacific, the capacity and resourcing of the Solomon Islands NSO is relatively high. As such, data deprivation is not as severe, with HIES rounds conducted in 2005/6 and 2012/13. However, there are still shortcomings: methodological changes and errors in poverty analytics have made it difficult to draw robust conclusions about poverty and inequality dynamics over time. Sep 11, 2019 Page 8 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) C. Proposed Development Objective(s) Program Level Development Objective To increase availability and access to timely data for policymaking in the Pacific Region. Country Project Development Objective To improve the quality, frequency, and timeliness of welfare statistics in the Pacific Island Countries (PIC). Regional Organization Project Development Objective To strengthen the capacity of the regional organization in coordinating technical assistance to NSOs and fostering improved practices in the region. D. Concept Description The Statistical Innovation and Capacity Building in Pacific Islands Series of Projects (SOP) will support countries in the Pacific region to increase the quality, frequency, and timeliness of socioeconomic statistics. The program envisions one regional organization grant to the Statistics for Development Division (SDD) of the Pacific Community, and two to three country level projects. The grant to the regional organization has planned three components. First, the grant will support the newly formed Pacific Statistics Methods Board (PSMB). The PSMB was created by the 2017 Heads of Planning meeting to promote rigorous approaches to methodological work in regional National Statistics Offices (NSOs). The second component supports SDD to increase their capacity to analyze and provide training in welfare measurement, including the calculation of poverty statistics. The final component provides financing to foster innovation, focused mainly on novel methods of data collection. The country-level grants support the collection of the next one to two rounds of the Household Income and Expenditure Survey (HIES) using improved methods, including a revised questionnaire, electronic data capture and verification, and reduced processing times. In addition, the country projects will provide targeted support to the project implementation teams within the NSOs, including materials and non-statistics technical training. Legal Operational Policies Triggered? Projects on International Waterways OP 7.50 No Projects in Disputed Areas OP 7.60 No Summary of Screening of Environmental and Social Risks and Impacts . Impacts are expected to be limited and easily managed through project design and effective implementation. Sep 11, 2019 Page 9 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) Note To view the Environmental and Social Risks and Impacts, please refer to the Concept Stage ESRS Document. . CONTACT POINT World Bank Kristen Himelein Kastelic Senior Economist/Statistician Borrower/Client/Recipient Tonga Ministry of Finance Implementing Agencies Tonga Department of Statistics (TDOS) Viliami Fifita Government Statistician vfifita@stats.gov.to FOR MORE INFORMATION CONTACT The World Bank 1818 H Street, NW Washington, D.C. 20433 Telephone: (202) 473-1000 Web: http://www.worldbank.org/projects APPROVAL Task Team Leader(s): Kristen Himelein Kastelic Approved By APPROVALTBL Practice Manager/Manager: Sep 11, 2019 Page 10 of 11 The World Bank Statistical Innovation and Capacity Building in Tonga (P171377) Country Director: Sep 11, 2019 Page 11 of 11