Inflation: Frontiers of Research and Policy

Why It Matters

Modernizing inflation measurement with real‑time private data will give policymakers sharper tools for monetary decisions, while reshaping the statistical agencies’ role in a data‑rich economy.

Key Takeaways

• Traditional inflation metrics rely on outdated 20th‑century survey methods.
• Private‑sector scanner data can produce real‑time price and quantity indices.
• The RESET project aims to replace surveys for high‑frequency CPI components.
• Partnerships with firms like Circona enable AI‑driven economic measurement.
• Modernized metrics promise more granular, timely inflation insights for policymakers.

Summary

The NBER‑hosted conference “Inflation: Frontiers of Research and Policy” highlighted a growing consensus that the United States’ inflation measurement framework is anchored in 20th‑century survey methods and is ill‑suited for today’s fast‑changing economy. Speakers, including Jim Piterba and the Reset Demonstration team, outlined how the Economic Measurement Research Institute and its Reset project aim to modernize price and quantity statistics by tapping into private‑sector scanner data and AI‑driven analytics.

Key insights emphasized the heavy burden of traditional surveys, the mismatch between revenue and price data, and the rapid turnover of products that current systems cannot capture efficiently. By partnering with data aggregators such as Surkana and Circona, the Reset team is constructing near‑census, monthly price and quantity indices for roughly two‑thirds of consumer goods, using item‑level UPC‑SKU information to generate Laspeyres‑type and superlative indices that are more timely and granular than the official CPI.

Notable examples included a reference to a teenage‑founded AI firm now valued at $1 billion, which can automate survey responses, and the adoption of similar scanner‑based approaches by statistical agencies in New Zealand, Australia, and the Netherlands. The presenters also demonstrated a pilot price index for food‑at‑home items, comparing it directly to the CPI and highlighting the potential to address chain‑drift and turnover issues in future iterations.

The implications are profound: policymakers could receive real‑time, high‑resolution inflation signals, improving monetary policy decisions and reducing the reporting lag that hampers economic analysis. Moreover, the role of federal statistical agencies may shift from data collection to data stewardship, overseeing the integration of private‑sector streams while ensuring confidentiality and methodological consistency.