Search results for: ""

This paper builds on PARIS21’s research on data use in policymaking, as well as the wider literature on evidence-informed policy. The barriers and enablers to data use identified through PARIS21’s work relate to all stages of the data cycle, from planning and production, to analysis, communication and use. As such, the recommendations outlined in this paper target a range of actors from both the policymaking and data cycles. These include national statistical offices (NSOs), other government ministries and agencies, civil society organisations (CSOs), journalists, academia and development partners.

Data producers, including national statistics offices and ministries, face an increasing demand for timely and disaggregated data that allows for targeted government interventions where they are most needed. This growing concern highlights the need to support the development of countries' data capacities to enable them to meet the demand for information from different users.

In this context, AI solutions provide opportunities to make data production processes more efficient, make data more accessible, and support the use of data in policy-making cycles. This discussion paper explores how artificial intelligence (AI) can be used in data value chains, navigating potential risks and seizing opportunities and outlines the role of the international community in leveraging technology responsibly.

Statistics are crucial for policy making that directs sustainable development and improves people’s lives. Data and statistics allow governments to design, implement, monitor and evaluate progress towards national and international commitments. A country’s capacity to produce and use statistics is therefore key to ensuring timely and accurate development policies.

This discussion paper covers three foundations of statistical capacity: leadership skills, strategic planning, and engagement between data users and producers. The paper proposes six action-oriented approaches to improve the foundations of statistical capacity, exploring lessons learned and examples from various countries. It highlights good practices and challenges associated with strengthening statistical capacity to enable countries to develop better official statistics that can help improve lives.

Taken as a snapshot, financing for data and statistics in the 2025 PRESS report gives cause for optimism. Overall funding has increased, thanks in particular to a rebound in support from DAC donors - the longstanding backbone of assistance to data and statistics. However, while recent years have brought numerous challenges that have tested but not undermined international support for national statistical systems, continuing to operate in a state of constant crisis will eventually take its toll.

This document describes the proposed Programme of Work and Budget (PWB) for the PARIS21 Secretariat in 2023, supporting the ambition of the 2021-2025 Strategy and Results Framework. It is built on extensive consultation with our partners, including through our 2022 Fall Meetings.

The PARIS21 annual progress reports detail the partnerships' activities and achievements throughout the year, including its country activities, capacity building, PRESS report and work alongside other partners such as through the Bern Network to ensure that financing development data remains a political priority.

This document describes the proposed Programme of Work and Budget (PWB) for the PARIS21 Secretariat in 2022, supporting the ambition of the 2021-2025 Strategy and Results Framework. It is built on extensive consultation with our partners, including through our 2021 Fall Meetings.

The PARIS21 annual progress reports detail the partnerships' activities and achievements throughout the year, including its country activities, capacity building, PRESS report and work alongside other partners such as through the Bern Network to ensure that financing development data remains a political priority.

Artificial intelligence is reshaping how data are collected, processed and shared. For national statistics offices, especially in low- and middle-income countries, the question is no longer whether to use AI, but how to do so responsibly and at scale. This paper presents a framework for becoming "AI-ready", for NSOs to understand and advance institutional readiness in their journey to responsible AI adoption.

This case study, developed with support from the Partnership in Statistics for Development in the 21st Century (PARIS21), documents the experience of the Dominican Republic, where the national statistics office (ONE) has emerged as a key actor in the preparation of national climate reports, ensuring the quality of the underlying data. Through close collaboration with the National Council for Climate Change and Carbon Market (CNCCMC) and the Ministry of Environment and Natural Resources (MMARN), ONE has helped enhance the production and use of climate statistics in the country, consolidating its institutional role in ensuring that the information it generates is timely, reliable, and accessible.