Research
The Emergence of Economic Rationality of GPT
with Yiting Chen, Tracy Xiao Liu, and Songfa Zhong
Proceedings of the National Academy of Sciences, 2023, 120(51), e2316205120.
Abstract: As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT's decisions with utility maximization in classic revealed preference theory. We find that GPT's decisions are largely rational in each domain and demonstrate higher rationality score than those of human subjects in a parallel experiment and in the literature. Moreover, the estimated preference parameters of GPT are slightly different from human subjects and exhibit a lower degree of heterogeneity. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender, but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.
Working papers
How General Are Measures of Choice Consistency? Evidence from Experimental and Scanner Data with Mingshi Chen, Tracy Xiao Liu, Shu Wang, Songfa Zhong, Yanju Zhou
Abstract: Choice consistency with utility maximization, as a key assumption in economics, has been extensively used to evaluate decision quality of individuals and to predict real-world outcomes across different contexts. Here we investigate the generalizability of consistency measures derived from budgetary decisions in the lab-in-the-field experiment and purchasing decisions using supermarket scanner data. In the first study, we observe a lack of correlation between consistency scores derived from risky decisions in the experiment and those from supermarket food purchasing decisions. In the second study, we observe moderate correlations between experimental tasks and low to moderate correlations across purchasing categories and over time periods within the supermarket. Moreover, consistency in the two settings exhibits distinct predictive validity in predicting consumer behavior. These results suggest that choice consistency, as a measure of decision quality, may be better characterized as a multidimensional skill set rather than a single-dimensional ability.