Can Markets Balance Growth and Inequality? Researchers Explore the Trade-Off.
01-22-2025

Prof. Simina Branzei, assistant professor of Computer Science at Purdue University, is author of a study that analyzes the balance of economic growth and inequality in markets. The findings are published in the Proceedings of the Royal Society A. Photo supplied by Simina Branzei.
Can Markets Balance Growth and Inequality? Researchers Explore the Trade-Off.
Economic inequality is rising worldwide, with profound consequences for societal stability. Can markets be designed to balance growth and inequality? A team of researchers tackled this question by analyzing a simplified mathematical model that captures the evolution of production-based economies over time. Their findings, published in Proceedings of the Royal Society A (https://royalsocietypublishing.org/doi/10.1098/rspa.2024.0533), explore how market dynamics shaped by human behaviors—such as tit-for-tat responses—impact economic outcomes.
“Though abstract, the model illustrates how growth and inequality can naturally emerge and co-exist in decentralized markets,” says Simina Branzei, a computer science professor at Purdue University and one of the study’s authors.
The study was a collaboration between Branzei; Ruta Mehta, computer science professor at the University of Illinois Urbana-Champaign; and Noam Nisan, computer science professor at the Hebrew University of Jerusalem. The project began during their time at the Simons Institute for the Theory of Computing, where they came together to explore the intersection of computation and economics.
Central to the model is a classic market mechanism known as Trading Posts, where agents—such as individuals or firms—bring to the market goods they produce and a monetary budget. Agents place bids on items, with prices determined by the total bids placed, and goods allocated in proportion to these bids. The acquired goods become raw materials for future production, while the earnings from sales provide agents with their next trading budget. To adapt in subsequent rounds, agents adjust their bids using tit-for-tat responses to past returns.
The Trading Posts mechanism also finds applications in today’s digital economy, modeling competition among blockchain miners. Miners invest resources, like electricity, to solve hash puzzles and have a success probability proportional to their investment.
The study shows these market dynamics yield an optimal economic growth rate, matching the efficiency of an ideally managed economy. Despite the limited perspective of individual agents, information flows gradually across the network through local interactions, enabling the discovery of globally efficient trade patterns.
However, the dynamics also lead to unbounded inequality, with rich and poor agents emerging and the gaps between their fortunes expanding over time. Furthermore, in some cases, an agent can accumulate a significant fortune without participating in any efficient production cycle, if they instead have robust connections with agents in key positions. This illustrates how free-riding can emerge in interconnected markets.
According to the team, what sets this study apart is its examination of how human behaviors, like tit-for-tat responses, shape economic systems. The model highlights a delicate trade-off: taxing wealthier participants can reduce inequality, but overtaxing risks stifling growth and leaving everyone worse off. This mirrors challenges faced in real-world economies, where growth does not always ensure equitable wealth distribution, emphasizing the need for market designs that account for human behavior.
“As modern markets increasingly operate on online platforms, their evolution can now be studied in unprecedented detail, opening the door to advanced economic simulators,” says Branzei. Tools like AI-driven simulators, already being developed by companies, can simulate complex market dynamics and reveal the long-term effects of different economic policies. This has the potential to guide policymakers in addressing challenges like inequality and fostering sustainable growth.
This research was supported by the National Science Foundation, the European Research Council, the European Union’s Horizon Programme, and the Israeli Science Foundation.
About the Department of Computer Science at Purdue University
Founded in 1962, the Department of Computer Science was created to be an innovative base of knowledge in the emerging field of computing as the first degree-awarding program in the United States. The department continues to advance the computer science industry through research. US News & Reports ranks Purdue CS #8 in computer engineering and #19 and #18 overall in graduate and undergraduate computer science. Additionally, the program is ranked 6th in cybersecurity, 8th in software engineering, 13th in systems, 15th in programming languages and data analytics, and 18th in theory. Graduates of the program are able to solve complex and challenging problems in many fields. Our consistent success in an ever-changing landscape is reflected in the record undergraduate enrollment, increased faculty hiring, innovative research projects, and the creation of new academic programs. The increasing centrality of computer science in academic disciplines and society, and new research activities—centered around foundations and applications of artificial intelligence and machine learning, such as natural language processing, human computer interaction, vision, and robotics, as well as systems and security—are the future focus of the department. cs.purdue.edu
Contributor:
Simina Branzei, assistant professor of Computer Science at Purdue University
Written by Cheryl Pierce, lead marketing and public relations specialist for the Purdue University College of Science