## IT’S TIME TO MODERNIZE MEASURES OF GROWTH

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**Canonical URL:** [IT’S TIME TO MODERNIZE MEASURES OF GROWTH](https://www.imf.org/-/media/files/publications/fandd/article/2025/12/riley.pdf)

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### Assessment: why current statistics lag the data-driven economy
- Assessments of the world’s economies may be off by trillions of dollars because existing metrics for GDP, consumer prices, productivity, and similar aggregates struggle to match rapid changes in technology, business models, and consumer behavior.
- Without accurate statistics, policymakers lack timely signals for when to "step on the gas" to counter a recession or "pump the brakes" to slow inflation.
- The core national accounts are based on concepts articulated in the United Nations System of National Accounts (SNA) and consumer inflation measurement is guided by the IMF’s consumer price manual; these conceptual frameworks are being challenged by digitalization and globalization.

### The rewired, data-driven economy: intangibles and invisible activity
- The data-driven economy relies heavily on intangibles such as software, marketing databases, and “organization capital.”
- In many advanced economies, businesses invest at least as much in intangibles as in buildings and factories, amounting to hundreds of billions of dollars and more likely trillions of dollars.
- Research cited indicates that 50% of intangible investments in advanced economies are essentially data investments that economic accounts are only starting to include as part of an update to the SNA this year.
- Digital services often consumed for free (search engines, social media, open-source software) are typically uncounted in household consumption, yet experimental willingness-to-pay studies indicate substantial value:
  - Preliminary research on the UK estimated the nominal value of digital leisure services produced by households at 8 percent of nominal GDP.
- Multinational enterprises’ use of intangibles can cause profit shifting and mismatches in where production inputs and revenues are recorded.

### Implications for macroeconomic aggregates and productivity measurement
- Mismeasurement affects GDP, trade balances, and productivity; researchers have reallocated multinational output across countries using employment or sales to illustrate distortions.
- Some small, open economies (example: Ireland and Denmark) supplement GDP with other aggregates less sensitive to globalization effects.
- Quality adjustment challenges:
  - Rapid innovation and new/improved products make it difficult to measure quality improvements.
  - A 2021 approach for telecommunications suggested stronger quality-adjusted growth; implemented alongside other methods, it reduced the estimated UK productivity slowdown in the decade after the 2008 financial crisis by a quarter of a percentage point.
- National statistical agencies have adopted diverse methods for adjusting digital product quality, affecting measured inflation and growth and cross-country comparability.

### Harnessing new data sources: opportunities and hurdles
- Today’s economy produces new data from digital interactions that could improve timeliness, accuracy, and granularity of economic statistics, but realizing this requires expanded capabilities and potentially heavy up-front costs.
- Challenges to using private-sector and administrative data include statistical noise, potential double counting, inadequate samples, legal and privacy constraints, and the need for trusted institutions and data-sharing agreements.
- Positive developments and examples:
  - The 2025 revision to the SNA is the first since 2008 and seeks to better capture digitalization, globalization, environmental sustainability, and well-being.
  - Statistical agencies in The Netherlands, Australia, and Canada have incorporated point-of-sale data into consumer price indices; the UK statistical agency is also progressing in this area.
  - During the pandemic, private-sector data helped provide high-frequency national and local economic indicators.
  - Research benchmarking private-sector data against representative national statistics highlights necessary adjustments and the value of blended data approaches.
- Methodological and technical investments needed:
  - Development of new economic/statistical methods, proofs of concept, and data exploration methods.
  - Investments in technologies for processing large-scale, messy data and in legal frameworks for data sharing.
  - Blended production of key statistics using private-sector, public administrative, and survey data under direction of national agencies.

### Policy recommendations and a way forward
- Strengthen investment in economic statistics infrastructure to avoid losing the ability to monitor the economy and guide policy.
- Implement the 2025 SNA revision and updates to the IMF’s balance of payments manual widely and promptly.
- Foster collaboration and coordination:
  - Between public and private sector data owners, across government agencies, and supported by legal and technical frameworks.
  - International collaboration among statistical agencies and with academic research institutions.
- Institutional and capacity priorities:
  - Build trusted institutions, data-sharing agreements, and technical capabilities at national statistical agencies.
  - Encourage collaborative models similar to existing initiatives (examples noted in the text include the Economic Statistics Centre of Excellence at King’s College London and national research institutes), recognizing that statistical agencies cannot resolve all issues in isolation.
- Maintain statistical rigor: trusted statistics must be produced in an accountable, transparent manner with impartiality and equal access to prevent noise from filling the information gap.

*Rebecca Riley, F&D, DECEMBER 2025*

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_Source: https://www.imf.org/-/media/files/publications/fandd/article/2025/12/riley.pdf_