Banrep paper proposes LLM-driven forecast method
Sequential design enables economists to study ‘information environment’
Economists at the Central Bank of Colombia (Banrep) have developed a method of forecasting inflation using large language models (LLMs).
Their findings, published in a working paper on October 16, emphasise how the “information environment” shapes the forecast process.
The team used a sequence of six progressively more detailed sets of contextual information to see how forecasts evolved as models were fed additional facts about the economic environment. The researchers used OpenAI’s model GPT-4o
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