Large Language Models in Economics

The rapid advancement of large language models (LLMs) has introduced transformative possibilities in the field of economics. We explore the emerging applications, benefits, and limitations of LLMs in economic research, policy analysis, and forecasting. By leveraging their ability to process and generate natural language at scale, we employ LLMs for tasks ranging from automating literature reviews and summarising economic reports to simulating agent behavior and enhancing macroeconomic modeling. Examining the challenges associated with the use of LLMs, including issues of data bias, transparency, and the interpretability of generated outputs, we offer a critical assessment on how LLMs can complement traditional econometric tools and improve decision-making while maintaining methodological rigor. We provide perspectives on future research directions and the potential for LLMs to reshape the boundaries of economic inquiry.