Proposal Description

The release of the 2025 SNA and BPM7 has renewed attention to the critical role of internationally harmonised macroeconomic statistics. Yet economic, financial, and technological systems continue to evolve at a pace that outstrips the revision cycle of statistical manuals. Digitalisation, climate transition, new business models, geopolitical shocks and shifting user expectations create information needs that cannot wait for formal standardisation.
In this context, statistical authorities face a dual responsibility: preserving the stability and international comparability of the statistical system, while ensuring that official statistics remain relevant, credible and responsive to emerging realities. When timely evidence is not provided, the vacuum is quickly filled by partial estimates, weak proxies or misleading narratives. The consequences can affect public trust, policy debates and the perceived authority of official statistics.
This session will examine how statistical authorities can innovate responsibly in the inter revision space. It will explore when and how to develop experimental statistics, how to govern and communicate pre standard outputs, how to manage their lifecycle, and how to prioritise innovation when resources and methodological readiness vary. The session will also draw lessons from recent areas of experimentation, including the digital economy, climate, fintech, crypto assets and real time indicators, and consider the role of international cooperation in preventing fragmentation.

Topics to explore:
• experimental statistics as a bridge between emerging phenomena and future standards
• governance models for non-core or pre-standard statistical outputs
• communicating uncertainty, maturity and revision risk
• balancing user demand versus methodological readiness
• case studies on the digital economy, climate, fintech, global value chains, platform work, crypto-assets, or real-time indicators

Guiding questions:
• What criteria should statistical authorities use to decide when an emerging phenomenon warrants an experimental output, and when it should remain at the research stage?
• How can institutions prioritise innovation areas when resources, expertise and data access are limited?
• What governance arrangements best ensure that pre-standard outputs remain transparent, accountable and clearly distinguished from core statistics?
• How should statistical authorities manage the lifecycle of experimental statistics – from launch to evaluation, revision, integration into standards or discontinuation?
• Which communication strategies are most effective in preventing misinterpretation of early-stage indicators while still meeting urgent user needs?
• What practical lessons can be drawn from recent experiments (e.g., digital economy, climate, fintech, crypto-assets) regarding data access, methodology, collaboration and user engagement?
• How can international cooperation mitigate the risk of divergent national innovations undermining future harmonisation?