Interview with Chris Giles and Joel Suss

In this episode of EconThoughts, A&M Managing Director and host Filippo Gaddo speaks with Financial Times economists Chris Giles and Joel Suss, winners of this year’s Rybczynski Prize for their paper The Text-as-Data Revolution and the Value of Financial News. Their work sits within a broader methodological shift made possible by large-scale digitisation and advances in machine learning — a shift Filippo highlights with reference to recent economic-history research that uses text-based methods to reconstruct GDP per capita back to the 1600s. Building on this new frontier, Chris and Joel show how modern language models can extract meaningful economic sentiment from millions of FT articles and turn unstructured text into a coherent, quantifiable macroeconomic signal.The conversation explores why their approach is genuinely novel: instead of relying on traditional keyword-based news indices, their two-stage LLM pipeline evaluates both article sentiment and topic relevance, generating a daily “macro mood” index that captures the tone of global economic reporting with far greater nuance. They describe how this index not only traces historical turning points — from wars to the global financial crisis to the tentative upswing of 2017–18 — but also contains forward-looking information. In fact, their methodology outperforms standard benchmarks, and even the Federal Reserve staff’s own forecasts, in predicting US inflation over a 12-month horizon. Looking ahead, they outline expanding applications: sector-level sentiment, geopolitical-risk indices, tools for policymakers tracking real-time soft data, and eventually an integrated product enabling users to drill from global trends to specific industries. Their work demonstrates how text-as-data can deepen our understanding of macroeconomic dynamics and complement traditional indicators in an increasingly complex policy environment.Chris Giles is the Financial Times’ Economics Commentator. Formerly the newspaper’s long-standing Economics Editor, he writes a regular column and produces the FT’s weekly economics newsletter. His work focuses on macroeconomic policy, fiscal strategy, inflation dynamics, and global economic trends. Chris has spent decades reporting from capitals around the world and is recognised for his accessible, analytically grounded approach to interpreting economic data and policy debates.Joel Suss is a journalist and quantitative researcher at the Financial Times, specialising in data science, economics, and the application of advanced machine-learning tools to journalism. He co-develops the FT’s Monetary Policy Radar indices, including the “macro mood” sentiment measure discussed in this episode. Before joining the FT, Joel worked in academia and policy-focused research, with interests spanning macroeconomics, political economy, and computational social science.