Concerns over the excessive use of mobile phones, especially among youths and young adults, are growing. Leveraging administrative student data from a Chinese university merged with mobile phone records, random roommate assignments, and a policy shock that affects peers’ peers, we present, to our knowledge, the first estimates of both behavioral spillover and contextual peer effects, and the first estimates of medium-term impacts of mobile app usage on academic achievement, physical health, and labor market outcomes. App usage is contagious: a one s.d. increase in roommates’ in-college app usage raises own app usage by 4.4% on average, with substantial heterogeneity across students. App usage is detrimental to both academic performance and labor market outcomes. A one s.d. increase in own app usage reduces GPAs by 36.2% of a within-cohort-major s.d. and lowers wages by 2.3%. Roommates’ app usage exerts both direct effects (e.g., noise and disruptions) and indirect effects (via behavioral spillovers) on GPA and wage, resulting in a total negative impact of over half the size of the own usage effect. Extending China’s minors’ game restriction policy of 3 hours per week to college students would boost their initial wages by 0.7%. Using high-frequency GPS data, we identify one underlying mechanism: high app usage crowds out time in study halls and increases absences from and late arrivals at lectures.
Authors
- Acknowledgements & Disclosure
- We thank Hunt Allcott, Luigi Pistaferri, Chris Taber, and various seminar participants for their helpful comments and Chenyan Gong for outstanding research assistance. All errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
- DOI
- https://doi.org/10.3386/w33054
- Pages
- 70
- Published in
- United States of America
Table of Contents
- Introduction 3
- Institutional Background and Data Description 7
- Background Information 7
- Data 10
- Data for Main Analysis 10
- Supplementary Data 11
- Summary Statistics 12
- Peer Effects on App Usage 14
- Reduced-Form Estimates 14
- Separating behavioral spillover effects from contextual effects 16
- Effects on Academic and Labor Market Outcomes 18
- App Usage and Academic Performance 18
- App Usage and Labor Market Outcomes 22
- Robustness and Heterogeneity 24
- Robustness Analysis 24
- Heterogeneity 26
- Evidence on Underlying Mechanism 27
- High-Frequency Location Evidence 27
- Survey Evidence 28
- Conclusion 29
- Appendix 47
- Data Construction 47
- Figures and Tables 47
- Survey Questions 64
