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“Parsing the pulse: Decomposing macroeconomic sentiment with LLMS”

Abstract

Macroeconomic indicators provide quantitative signals that must be pieced to gether and interpreted by economists. We propose a reversed approach of parsing press narratives directly using Large Language Models (LLM) to recover growth and inflation sentiment indices. A key advantage of this LLM-based approach is the ability to decompose aggregate sentiment into its drivers, readily enabling an interpretation of macroeconomic dynamics. Our sentiment indices track hard-data counterparts closely, providing an accurate, near real-time picture of the macroe conomy. Their components–demand, supply, and deeper structural forces–are in tuitive and consistent with prior model-based studies. Incorporating sentiment indices improves the forecasting performance of simple statistical models, pointing to information unspanned by traditional data

����ͷ�� the speaker

is Acting Head of the Monetary and Economic Department and Head of Economic Analysis and Statistics. He is a member of the Bank’s senior management team.

Language

English.

This is a free seminar. Registration is mandatory.

Cold lunches are provided to registered participants.

In partnership with

This is a joint event held with the European Stability Mechanism and the Department of Finance of the ����ͷ��.