Xiaochen Zhang is an Assistant Professor of Applied Economics at Duke Kunshan University. Specializing in regional and urban economics, as well as population studies, Professor Zhang’s research focuses on migration, aging, and policy evaluation.
Professor Zhang recently concluded his research project “Population Aging, Regional Innovation, and Productivity: Evidence from China,” which was supported by a CSCC Faculty Research & Creative Activity Grant. The project examines the influence of population aging on local labor markets and innovation, within the context of China’s knowledge-based economy and its evolving demographic structure.
Using census and patent data from 2000 to 2015, Professor Zhang’s identified a U-shaped relationship between the median age of urban populations and their innovation output, indicating that cities with younger or older age profiles tend to be more innovative than those in the middle age range. This paradigm-shifting discovery, which diverges from similar European studies, could have wider implications for managing demographic changes in fast-aging economies. We are honored to have the opportunity to sit down with Prof. Zhang and delve deeper into his research findings through our questions.
For those unfamiliar with the topic, could you briefly explain what “regional innovation” means within the context of your research? Also, could you summarize your findings regarding the optimal age composition for fostering innovation capacities in China’s prefecture-level cities?
In my research, I examine innovative capabilities, typically quantified by patent counts, at a sub-national level. There is widespread concern about the detrimental effects of population aging on innovation, founded on the belief that younger individuals are usually more inventive. However, previous studies provide inconclusive evidence on the overall impact of an aging population on productivity. In this study, we also looked at the interations between different age groups, and we want to study the nature of these dynamics – we are examining whether different age groups are substitutes or complements when they’re working together.
In this study, we also looked at the interations between different age groups, and we want to study the nature of these dynamics – we are examining whether different age groups are substitutes or complements when they’re working together.
You have mentioned finding a U-shaped relationship between median age and patent applications in Chinese cities. What may be the underlying factors contributing to this pattern, and how do these factors differ from findings in other countries, such as Germany?
The U-shaped relationship was the ultimate motivation for my collaborator and me to investigate the actual influence of age on innovation. Specifically, the substitution and complementary effects of diverse age groups jointly determine the shape of this curve.
For students interested in pursuing research in economics, particularly in the areas of migration and aging, what advice would you offer to help them get started?
I recommend that students take a course in econometrics (ECON203) as soon as they can, ideally completing it by the end of the first semester of their junior year. Early in their preparation for their Signature Work, I strongly advise taking a few 300-level electives in economics. These courses will equip students with the necessary skills to start real econ research.
In what ways have student research assistants contributed to your project, and what skills or insights have they gained through their involvement?
I once recruited a student to develop machine learning models, such as random forest trees, which is a widely used algorithm. My training as an economist provided an understanding of how these models could be applied in my storytelling, but my coding expertise is limited. This is where student research assistants become invaluable — they can help build models from the ground up.
Looking forward, what are the primary objectives for the next phase of your research? How might you expand the scope of your analysis to deepen our understanding of the dynamics between aging and innovation?
My goal is to present my working paper at conferences and get it published soon.
