Assessing Statistical Needs in Belize for data-driven decision-making Summary of the Statistical Institute of Belize (SIB) Statistical Needs Assessment Authors: The authors are all affiliated with the World Bank’s Poverty and Equity Global Practice for Latin America and the Caribbean. Jacobus Joost de Hoop. Senior Economist. (World Bank) Alejandro Medina-Giopp. Senior Monitoring and Evaluation Specialist. (World Bank). Gabrielle Michelle Hulse. Secondee. (World Bank) General review: World Bank’s Poverty and Equity Global Practice for Latin America and the Caribbean . This publication is produced by the World Bank Group, through the Poverty and Equity Global Practice for Latin America and the Caribbean in collaboration with the Statistical Institute of Belize (SIB). Total or partial reproduction of this document is authorized, without commercial purposes, providing the source is properly cited. January 2024 Washington D.C. – United States of America 2 Index Index .................................................................................................................................................................. 3 Figures ............................................................................................................................................................... 3 Charts ................................................................................................................................................................ 3 Acronyms and Abbreviations ......................................................................................................................... 4 Key Words ......................................................................................................................................................... 4 Assessing Statistical Needs in Belize for data-driven decision-making ................................................... 5 Abstract ............................................................................................................................................................. 5 National Context ............................................................................................................................................... 5 Statistical Needs Assessment Methodology ................................................................................................ 7 Findings ............................................................................................................................................................. 7 Data Producers ................................................................................................................................................ 7 Coordinators ..................................................................................................................................................... 8 Promoters of Data Use .................................................................................................................................... 8 Capacity ............................................................................................................................................................ 8 Priorities ............................................................................................................................................................ 9 Conclusion and action plan ............................................................................................................................ 9 Priority actions for improvement .................................................................................................................... 9 Annexes........................................................................................................................................................... 11 Figures Figure 1 SPI Overall Score for Belize in 2023 ............................................................................................. 5 Figure 2 Belize SPI Score by pillars .............................................................................................................. 6 Figure 3 Belize SNA Global Score................................................................................................................. 7 Charts Chart A1. 1 Data Production ........................................................................................................................ 11 Chart A1. 2 Methodologies ........................................................................................................................... 12 Chart A1. 3 Human Resources .................................................................................................................... 12 Chart A1. 4 IT Infrastructure ......................................................................................................................... 13 Chart A1. 5 Organization and Structure ..................................................................................................... 13 Chart A1. 6 Analysis and Indicators ............................................................................................................ 14 3 Acronyms and Abbreviations BNSS Belize National Statistical System CPA Country Poverty Assessment D4P Data for Policy (World Bank’s index) e-GDDS Enhanced General Data Dissemination System HBS Household Budgetary Survey IMF International Monetary Fund LAC Latin America and the Caribbean LFS Labor Force Survey MICS Multiple Indicator Cluster Surveys MPI Multi-Dimensional Poverty Index NADA National Data Archive (Open-source microdata cataloging system) NSDS National Strategy for the Development of Statistics NSO National Statistical Office NSS National Statistical System ODIN Open Data Inventory SDDS Special Data Dissemination Standard SIB Statistical Institute of Belize SNA Statistical Needs Assessment SPI Statistical Performance Indicators STATCAP Statistical Capacity Project WBG World Bank Group Key Words Statistical Performance Indicators, Belize Data Assessment, Indicators, Poverty statistics, Statistical Needs, NSS Coordination, Dissemination Gaps, Data Use, Statistical Capacity, Data development plans. 4 Assessing Statistical Needs in Belize for data-driven decision-making Summary of the Statistical Institute of Belize (SIB) Statistical Needs Assessment January 2024 Abstract This note presents findings of a Statistical Needs Assessment (SNA) of the Statistical Institute of Belize (SIB). The aim of the assessment is to inform efforts to enhance the national statistical system for data driven decision-making. Belize has shown good progress in the development of its statistical infrastructure. Some challenges persist in data collection, coordination, and usage. Key priorities include developing the National Strategy for the Development of Statistics (NSDS), integrating administrative data, and addressing resource constraints. Strengthening these areas will bolster SIB's capacity as a pivotal data producer and coordinator for informed policymaking. National Context A few global tools can be used to benchmark the performance of Belize’s national statistical system (NSS) to that of other countries. One of these is the World Bank’s Statistical Performance Indicators (SPI). This index evaluates a country’s national statistical system in its entirety, incorporating users, producers, and partners at various levels. It aims to identify strengths and weaknesses of the NSS and guide performance improvements and investments. The SPI score covers five areas: data use, data services, data products, data sources, and data infrastructure, with specific attributes called dimensions, that make up the components of each area. Scores range from zero to 100, where 100 implies a perfect score on all dimensions in an area. As shown in Figure 1, Belize’s overall score for 2023, the combined aggregate of the five areas, was 65.1. This score represented substantial progress from the 2016 score of 47.7, marking an increase of 36.58%. With this increase, Belize has nearly reached the average score of other countries in the LAC region, but it still lags other upper middle-income countries. 75 70 65 65.1 64.2 60 61.6 58.2 55 56.1 56 51.4 50 47.7 45 40 2016 2017 2018 2019 2020 2021 2022 2023 Belize Latin America and the Caribbean Upper middle-income Figure 1 SPI Overall Score for Belize in 2023 5 Figure 2 illustrates Belize’s progress over time in each of the pillars. The Data Services pillar (services that connect data users with data producers, facilitating interaction) exhibits the most significant improvement, with its score rising from 9.7 in 2016 to 64.9 in 2023. This improvement is attributed to advances in 7 out of 8 indicators, including data openness and coverage (ODIN score) 1, SDDS/e- GDDS subscription2, non-proprietary format, download options, and survey metadata3. All other pillars score above 60 in 2023, with the exception of Belize’s Data Infrastructure (including regulatory aspects and quality standards). Although it increased from a score of 30 in 2016, at 55 the score continues to be below all other pillars. 90 80 70 60 50 40 30 20 10 0 2016 2017 2018 2019 2020 2021 2022 2023 Data use Data services Data products Data sources Data infrastructure SPI score overall Figure 2 Belize SPI Score by pillars Gaps highlighted by the SPI correspond with other analytics such as the World Bank’s Data for Policy (D4P) index which measures crucial statistical operations that are vital for monitoring economic and social development. The D4P index suggests weaknesses in Belize’s business data. These measures can be useful in pinpointing critical areas and prioritizing them accordingly. 1 From 2020 to 2022, Belize's overall ODIN score rose from 40 to 45, driven by increases in both data openness (accessibility) and coverage (availability) scores. Its performance is similar to the Central America regional average of 45 in 2022. Link: https://odin.opendatawatch.com/Report/countryProfileUpdated/BLZ?year=2022 2 The Special Data Dissemination Standard (SDDS) and the Enhanced General Data Dissemination System (e- GDDS) are frameworks established by the International Monetary Fund (IMF) to guide the production and dissemination of statistics by member countries. 3 This indicator checks whether NADA microdata cataloging is available for surveys produced by NSO. NADA is an open source microdata cataloging system. 6 Statistical Needs Assessment Methodology To further shed light on the performance of Belize’s NSS and opportunities for statistical capacity strengthening, the SIB and the World Bank jointly coordinated on a Statistical Needs Assessment. The SNA is conducted through a self-assessment questionnaire organized in six main sections, covering the entire National Statistical System (NSS): organizational structure and infrastructure, human resource management and training, data collection, data analysis, development of key indicators, and IT infrastructure and systems. Each main section includes sub-sections detailing specific topics. Respondents select one of five responses ranging from 4 (best) to 0 (worst) for each question. The objective of this note is to summarize the main findings of the SNA and priority actions for improvement. Findings Based on the self-assessment completed by SIB, Belize performs moderately measured against most of the components of the Global SNA. As illustrated by Figure 3, SIB’s strongest area is its human resources. On this outcome, the SIB has an almost perfect score. The weakest area is data collection and openness. The remainder of this note assesses strengths and gaps identified by the SNA within each of these components that affect the SIB’s ability to carry out its role as an NSO. The overall score achieved is 2.85 out of 44. 1. Organization and Infrastructure 4.0 3.0 6. Methodologies 2.0 2. HR Issues 1.0 0.0 5. IT Infrastructure & 3. Data Collection and Systems openness 4. Data Analysis and Indicators Figure 3 Belize SNA Global Score Data Producers As data producers, SIB achieves 50% of the most relevant statistical production for an NSO (See Chart A1.1 in the appendix). Strong points are the regular administration of censuses and surveys along with a regular labor survey. The SIB also collects valuable insight on education statistics and macroeconomic data. The gaps relate to other significant data sources such as administrative data 4The scores attained in the LAC region by Surinam and Haiti were 2.32 and 1.68, respectively. In Africa, the average score for 16 SADC country members is 2.56. 7 and economic census. There is no assessment of the administrative records within the country nor an integrated system to collate such records. This is an important gap, because this type of data matters for the development and monitoring of policy and programs. Other areas of improvement include the limited use of business registries and availability of other social statistics such as education and health. The SIB has recently implemented some innovations in the generation of poverty statistics. Until recently, poverty estimates relied on data from the Household Budgetary Survey (HBS) and the Country Poverty Assessment (CPA). However, due to the infrequent nature of these surveys, the SIB has adjusted the biannual Labor Force Survey (LFS) questionnaire to generate poverty estimates more regularly. Each year, the SIB now includes a survey module to measure multidimensional poverty in one round of the labor force survey. In the other round of the labor force survey, the SIB intends to include a survey module to measure monetary poverty. In terms of health statistics, the SIB typically conducts the Multiple Indicator Cluster Surveys (MICS) every five years. However, the most recent survey took place in 2015. The 2020 round was initially postponed due to the Census, and subsequently due to the COVID-19 pandemic. The next round is scheduled for 2024. Coordinators The SIB, by means of the SIB Act of 2006, has complete authority to serve as coordinator for the NSS and manage activities with statistical implications performed by agencies that contribute to the NSS. To institutionalize these activities, the National Strategy for the Development of Statistics (NSDS) is underway and will address the main gap of this component, namely that the SIB does not coordinate data collection across NSS agencies. In the interim, the SIB engages in bilateral institutional arrangements for data sharing with agencies such as the Tax department and Social Security Board. However, these activities need to be standardized by a coordination mechanism and guided by relevant methodologies (See Chart A1. 2 Methodologies) to effectively fulfil this role. Lastly, the SIB has no advisory council to gauge the input of outside experts and stakeholders from the public and private sectors. Promoters of Data Use With the data available, SIB adequately publishes statistics on access to services, labor, and education. There is also reasonable information available on poverty, complemented by SIB’s most recent use of data – the Multi-Dimensional Poverty Index (MPI). While this is a positive development for poverty data, no consumption aggregates are readily available for use. Additionally, the SIB publishes crucial health indicators such as the under-5 mortality rate (produced by the Ministry of Health) on its BNSS portal; child immunization rates are produced annually but not published Besides the preceding analyses listed, no analysis is available to the public concerning business activities, national accounts, and government finances (See Chart A1. 6 Analysis and Indicators). Data pertaining to these sectors is either not available or collected by external agencies. Capacity This pillar is SIB’s best performing component according to the statistical needs assessment. The score indicates a high caliber of capacity in human resources especially as it relates to trainings, internal policies, pool of specialized staff, and favorable compensation. The SIB also demonstrates competency in its data collection and dissemination. Although there is not a large repository of information (laws, reports, evaluations) to be made available to the public, increasing data access is 8 still an avenue to pursue towards strengthening SIB’s capacity. This will also benefit compliance with international standards such as the IMF Special Data Dissemination Standards (SDDS) and Open Data Inventory 2022/2023 ranking. Priorities To advance Belize’s statistical performance, there are several key priorities for the SIB in accordance with the gaps identified in the assessment. Firstly, the SIB should continue the development and validation of the NSDS with relevant stakeholders. A strategy inclusive of institutional arrangements, capacity-building, governance structures, data development plans, and resource mobilization can serve as a solid foundation for implementation. With the strategy as its basis, the next priority is the assessment and integration of administrative data. As the weakest element of the data collection, a SIB focus on statistical capacity building is warranted. Its inclusion in the NSDS will support the harmonization of data with the Medium-Term Development Strategy indicators to improve national planning. Lastly, ensuring that personnel and infrastructural needs continue to be met is key to tend to the growing demands on the organization. This includes leveraging technology for data generation, knowledge management, and public communications, and onboarding additional human resources. Resource limitations have stunted progress before and to avoid these bottlenecks, SIB should include strategic action points and programs to address the data production gaps in their budget. Conclusion and Action plan SIB possesses a great capacity to effectively carry out current analyses and dissemination. To advance its performance as an NSO, the SIB will need to build on present structures to facilitate the assumption of additional functions especially as it relates to their role as producers and coordinators of national data. The following table summarizes the actions plans derived from this assessment. Priority actions for improvement SIB Role as Coordinator 1 Develop and validate the NSDS with relevant stakeholders. • Finalize the development of the NSDS. • Strengthen SIB's capacity as NSS coordinator of sector data. Explore the creation of a data council or equivalent. • Secure support for resource mobilization to implement the NSDS. • Establish an advisory council to assess input from external experts and stakeholders from public and private sectors. 2 Leverage technology to facilitate data generation, knowledge management, and public communications. • Invest in modern data collection tools and technologies to streamline data generation processes. • Implement a robust knowledge management system. • Develop user-friendly online platforms for public communication and engagement with data, including interactive dashboards and data visualization tools. 9 • Provide training to staff on the use of technology for data generation, management, and communication. SIB Role as Data Producer 3 Discuss medium- and short-term strategies for statistical production through administrative data. • Conduct an inventory of administrative records to assess data availability and identify digitization needs. • Organize capacity building workshops to diagnose the quality of administrative records and devise improvement plans. • Adopt the DDI standard for data documentation of administrative records. • Create a catalog of administrative records to facilitate data access and usage. • Provide training on utilizing administrative data for statistical production. 4 Harmonize NSS data collection with the Medium-Term Development Strategy indicators to improve national planning. • Identify existing gaps and overlaps between NSS data collection and Medium-Term Development Strategy indicators. • Develop a framework for aligning NSS data collection methodologies with Medium- Term Development Strategy indicators. • Establish mechanisms and training for monitoring and evaluation of the Development Strategy, focusing on key indicators to improve national planning. 5 Onboard the additional human resources needed to coordinate data collection activities among NSS agencies. • Assess the current staffing needs for effective coordination of data collection activities. • Develop job descriptions, recruitment plans, and onboard new staff. • Establish communication channels and workflows to facilitate coordination among NSS agencies. 6 Include data production gaps in programmatic budget or, if needed, identify other potential funding including from international partners, such as the regional STATCAP project for Central America promoted for the World Bank. • Evaluate existing programmatic budgets to identify gaps in funding for data production activities. • Develop a funding proposal outlining the specific needs for addressing data production gaps, including potential funding sources from international partners. • Collaborate with relevant stakeholders to advocate for the inclusion of data production funding in programmatic budgets or secure alternative funding sources to address identified gaps. STATISTICAL CAPACITY 7 Improve the strategy for data dissemination, • Conduct capacity building sessions on data documentation, data cataloguing, dissemination, and anonymization for SIB staff. 10 • Review and update the Microdata Access Policy to facilitate data access for all potential users, currently is more focused on researchers. • Increase data availability in machine readable formats through the website portal Annexes Annex 1 SIB’s Statistical Needs Assessment Results by Domain Surveys Types and Frequency 4.0 Other registers - tax 3.0 administration, judiciary, Censuses etc. 2.0 1.0 0.0 Statistical Business Economic and service data Registers collection Administrative data Social statistics Chart A1. 1 Data Production 11 Household Income and Expenditure Surveys Methodology 4.0 3.5 3.0 Agricultural production 2.5 survey Statistical Business (crops/livestock) 2.0 Registers Methodology 1.5 1.0 0.5 0.0 Other registers - tax Censuses of administration, Agriculture judiciary, etc. Population Censuses Chart A1. 2 Methodologies Wage level in comparison with other government agencies 4.0 3.0 2.0 Training and retention of Promotion policies, IT and IT-related 1.0 gender issues specialized professionals 0.0 Training on the future Training and retraining statistical cadre in the programs country Chart A1. 3 Human Resources 12 Data Center 4.0 3.5 3.0 Data Collection, 2.5 Exchange, Data Dissemination 2.0 Transmission, and Openness Processing and 1.5 Storage 1.0 0.5 0.0 Geography (GIS) Data Dissemination Data Privacy & Confidentiality Chart A1. 4 IT Infrastructure Law on Statistics and Related Acts 4.0 3.5 3.0 2.5 Relationship with Other 2.0 Government Agencies' 1.5 Statistical Council, Data Data Producers and 1.0 User Groups Data Users – Data Exchange Protocols 0.5 0.0 Organization of NSO- Organization of data HQ and Regional collection Offices Chart A1. 5 Organization and Structure 13 Macro indicators & National Accounts 4.0 Other Indicators Poverty indicators 3.0 2.0 Government Finance 1.0 Labor Statistics Statistics (GFS) 0.0 Health & Indicators of business Demographics activity Indicators Access to services Education Indicators Chart A1. 6 Analysis and Indicators 14