Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks

TL;DR

This paper introduces MetricsAI, an econometrics AI agent capable of performing complex econometric analysis, demonstrating superior performance over benchmarks, and facilitating research and education in social sciences.

Contribution

The paper presents MetricsAI, a specialized AI agent for econometrics that outperforms general models and benchmarks in real-world tasks, with applications in research and teaching.

Findings

MetricsAI outperforms benchmark LLMs in econometrics tasks.

The agent demonstrates robust code generation and iterative refinement.

MetricsAI enhances reproducibility and accessibility in econometrics research.

Abstract

Can AI effectively perform complex econometric analysis traditionally requiring human expertise? This paper evaluates AI agents' capability to master econometrics, focusing on empirical analysis performance. We develop ``MetricsAI'', an Econometrics AI Agent built on the open-source MetaGPT framework. This agent exhibits outstanding performance in: (1) planning econometric tasks strategically, (2) generating and executing code, (3) employing error-based reflection for improved robustness, and (4) allowing iterative refinement through multi-round conversations. We construct two datasets from academic coursework materials and published research papers to evaluate performance against real-world challenges. Comparative testing shows our domain-specialized AI agent significantly outperforms both benchmark large language models (LLMs) and general-purpose AI agents. This work establishes a testbed for exploring AI's impact on social science research and enables cost-effective integration of domain expertise, making advanced econometric methods accessible to users with minimal coding skills. Furthermore, our AI agent enhances research reproducibility and offers promising pedagogical applications for econometrics teaching.