AI and Human Capital Accumulation: Aggregate and Distributional Implications
"This paper examines how anticipated advances in artificial intelligence (AI)– which compress middle-skill wage premia but increase returns to high-level expertise– reshape human capital investment, labor supply, saving, and inequality."
Yang Lu, and Eunseong Ma
Better and Faster Decisions with Recommendation Algorithms
"This study helps understand behavioral mechanisms underlying recommendation algorithms and sheds light on the design of choice architecture with the assistance of artificial intelligence."
Songfa Zhong, Yiting Chen, and Ziye Wu
Working Paper
Mining Chinese Historical Sources At Scale: A Machine Learning-Approach to Qing State Capacity
"We propose a supervised machine-learning approach to the natural language processing of Chinese historical data."
Wolfgang Keller, Carol H Shiue, and Sen Yan
Forthcoming in the journal Historical Methods
The Emergence of Economic Rationality of GPT
"This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences."
Songfa Zhong, Chen Yiting, Liu Xiao Tracy, and Shan You
Proceedings of the National Academy of Sciences, 2023, 120 (51) e2316205120
Trading against Algorithms: Price Dynamics and Risk-sharing in a Market with Q-learners
"When rational investors have strong risk-sharing motives for trading, we show that Q-learners can (i) earn trading profits and (ii) improve average investor utility, even though they increase the volatility of prices."
Martin Szydlowski, and Snehal Banerjee
Understanding the Mechanism of Altruism in Large Language Models
"Altruism is fundamental to human societies, fostering cooperation and social cohesion. Recent studies suggest that large language models (LLMs) can display human-like prosocial behavior, but the internal computations that produce such behavior remain poorly understood. We investigate the mechanisms underlying LLM altruism using sparse autoencoders (SAEs)."
Songfa Zhong, Shuhuai Zhang, Shu Wang, Zijun Yao, Chuanhao Li, Xiaozhi Wang, Tracy Xiao Liu
When Experimental Economics Meets Large Language Models: Evidence-based Tactics
"Inspired by principles from experimental economics with insights from LLM research in artificial intelligence, we outline key considerations in the experimental design and implementation stage, and perform two sets of experiments to assess the impact of these considerations on LLMs' responses."
Songfa Zhong, Shu Wang, Zijun Yao, Shuhuai Zhang, Jianuo Gai, and Tracy Xiao Liu
Working Paper