Subject：The Effect of Subsidizing Digital Educational Content: Evidence from a Field Experiment

Guest：Jingcun CAO, Assistant Professor of Marketing, The University of Hong Kong

Host：ZHANG Shuo, Associate Professor, ACEM

Time：10:00-11:30am. Thursday, Dec 14, 2023

Venue：Room B716, Antai Building

Abstract:

The unequal distribution of educational resources has been a major concern of both educators and policymakers around the world. The rise of the digital education industry brings new hope to the problem, but how exactly it affects existing education inequality remains largely unknown. Using data from a unique field experiment by an eBook app, we investigate the effects on K-12 children of improving access to digital educational resources. In particular, our analysis traces out both the short-run and long-run treatment effects of providing children with free access to digital reading resources, and how these effects vary across children with different socioeconomic backgrounds. We find that providing children with free access to digital reading materials leads to a dramatic and immediate increase in reading time for treated children, and that this immediate effect is much larger for children from less developed regions with fewer educational resources. However, children's reading activities decline quickly after the start of their free access. Surprisingly, this decline is much faster for children from less developed regions, despite their strong initial reaction to the treatment. Further evidence suggests that children from more developed regions benefit more from the free access in the long run. Our mechanism analysis further reveals a nuanced complementarity between digital and non-digital education and suggests that the long-run difference in reading patterns likely reflects differing levels of parental involvement in the education of children with different socioeconomic status. We discuss the managerial and policy implications of our study.

Guest Bio：

Dr. Jingcun Cao, Assistant Professor in the Marketing Department at the Faculty of Business and Economics, The University of Hong Kong. Dr. Cao earned his Ph.D. in Marketing from the Kelley School of Business, Indiana University, USA, with a minor in Statistics. His research interests primarily lie in the application of machine learning in marketing, quantitative marketing with big data, new media marketing, mobile app (APP) ecosystems, online education, and empirical studies in the big health sector. Dr. Cao is proficient in a variety of analytical methods, including machine learning, econometrics, statistics, and field experiments, to study consumer behavior and corporate marketing strategy decisions. He has extensive experience in collaborating with businesses in areas such as data empowerment, traffic monetization, precision marketing, and brand positioning. Dr. Cao has taught courses such as Principles of Marketing, Big Data Marketing, and Data Scientist at undergraduate and executive levels at Indiana University, USA, and The University of Hong Kong.