Harnessing Generative AI to Transform Economic Research: Insights and Practical Applications
1. Sarita hemnani, Goa Institute of Management, Goa, Postdoctoral Researcher, India
2. Tanvi Bhatt, Goa Institute of Management, Goa, Lecturer, India
Generative artificial intelligence (AI), especially large language models (LLMs) like ChatGPT, offers tremendous promise for economic analysis. In this paper, we look at six main areas where LLMs might be helpful to economists: brainstorming and suggestions, writing, studies and background, data analysis, coding, and algebraic derivations. The study proposes that economists may significantly increase their efficiency by scripting micro-tasks using generative AI and provides concrete implementation instances by classifying LLM capabilities from experimental to very helpful. Cognitive automation driven by AI will have far-reaching consequences for economics in the future since productivity increases are directly proportional to the rate of AI system performance improvement. Access the most recent instructions and updates on the most cutting-edge creative AI features in economics with the associated online tools.
Productivity Gains Writing Assistance Mathematical Derivations Data Analysis Economic Research Background Research ChatGPT Cognitive Automation Coding
Generative AI, particularly LLMs like ChatGPT, offers immense potential to transform economic research. Economists can achieve substantial productivity gains by leveraging these tools across various research tasks and staying ahead in an increasingly competitive field. The ongoing development of AI systems promises even more significant enhancements in the future, heralding a new era of cognitive automation in economics.
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The author takes full responsibility for the entire study process, including design, data collection, analysis, and manuscript writing.
No grants from public, commercial, or non-profit funding agencies supported the research, authorship, or publication of this article.
There is no software or tools usage information relevant to this research.
All authors declare the absence of any conflicts of interest.
My gratitude goes to those who assisted in this study and manuscript preparation, and to the anonymous reviewers for their constructive insights.
There are no data available for sharing in this work.