Sectoral strategies for the development of statistics
Sectoral and subject-matter statistics support :
- Sector policy and program design,
- implementation and monitoring in thematic areas of the development work of government
- private institutions, and
- civil society.
Sectoral and subject-matter statistics thus often reflect the country’s development priorities for the society, the economy, and the environment in specific sector. Users of sectoral and subject-matter statistics are decision and policy makers, planners, program implementers, and service deliverers at the national and local levels. These include the ministries/agencies, local government units, the private sector/industry groups, and civil society organizations, academics and researchers, and the citizens.
Sectoral and subject-matter statistics constitute a substantial part of the official statistics in a country, arguably, more than large-scale censuses and surveys data. They serve as essential building blocks of the country’s national statistical system. As they address demand for increased granularity and hence more relevance of statistics in citizen-centered policy, they also manifest to the inclusive characteristic of the national statistical system.
Sectoral and subject-matter statistics come from various sources, primarily from administrative, regulatory, and monitoring systems of government (e.g., registration, licensing, reporting, and surveillance). Some data are provided by censuses and surveys, research, and scientific measurement but there are other sources that remain underdeveloped and/or largely untapped, including big data and citizen-generated data , data disaggregation, etc.
Production of sectoral and subject-matter statistics follows the generic statistical business process model in varying degrees and with varying levels of quality of output across data sources. Better quality of data is expected from censuses and surveys and scientific studies/measurements while less quality is widely observed in data from most administrative data systems.
Economies and societies constantly evolve with new issues and concerns emerging or as consequence of certain situations such as economic crises, social disturbances, natural disasters, and pandemics. The production of more relevant disaggregation of statistics, primarily sectoral and subject-matter statistics along with subnational statistics, needs to be among the priorities of the national statistical system.
- Assess existing or established administrative data systems in selected priority sectors and/or subject-matter areas (e.g., education, health, disability, agriculture, environment, or poverty, civil registration, gender, disaster management, and governance, etc.). Step 3.1 | Step 3.2 | Step 3.3 | Step 3.4
- Explore and assess yet untapped data sources (e.g., big data, sensor data, citizen-generated data, routine reporting and monitoring data).
- Identify most relevant and priority users of data and their needs.
- Analyze existing data in relation to priority data needed by key users and other potential data.
- Examine existing relevant legal frameworks and policies, resources, and capacities of key ministries/agencies.
- Identify strategic goals and key outputs toward improvement of sectoral and subject-matter statistics. Step 4.2 | Step 4.3
- Identify specific actions and corresponding costs, as well as key risk factors and mitigating measures. Step 5.1 | Step 5.2 | Step 5.3
- Prioritize the improvement of administrative data systems in priority sectors and subject-matter areas (e.g., capacity development, research and development, financing, etc.)
- education management information system,
- health management information system,
- civil registration systems
- social welfare monitoring systems,
- business registration and monitoring system, including e-commerce,
- governance information system,
- transportation management information system,
- environment and climate change monitoring, and
- hazard and disaster information systems, including that on natural disasters and pandemics.
- Early warning information systems (e.g for food security, etc.)
- Establish institutional partnerships between NSO and the relevant ministries/agencies mandated in the selected priority sectors and/or subject-matter areas. Step 6.3
- explore cross-cutting strategies and inter-sectoral linkages (agriculture and environment, health and environment, infrastructure, etc.)
- Consider partnerships with big data sources such as data science firms, telecommunication companies, and other service providers to share data and/or help develop applications to extract data.
- Study and consider existing systems of civil society organizations (many are location-specific) including citizen-generated data to produce statistics on specific issues.