Combining Dynamic Mode Decomposition and Difference-in-Differences in an Analysis of At-Risk Youth
- Resource Type
- Conference
- Authors
- Choi, Marc Andrew; Huang, Siyu; Qi, Hengyuan; Scialanga, Marco; McMullen, Emerson; Moreno, Axel Sanchez; Lou, Yifei; Bertozzi, Andrea L.; Brantingham, P. Jeffrey
- Source
- 2022 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2022 IEEE International Conference on. :4664-4673 Dec, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Mathematical analysis
Big Data
Approximation algorithms
Eigenvalues and eigenfunctions
Performance analysis
Behavioral sciences
Dynamical systems
dynamic mode decomposition
difference in differences
causal inference
factor analysis
- Language
We analyze the impact of the Los Angeles Mayor’s Office of Gang Reduction Youth Development (GRYD) prevention programming using quasi-experimental data. We model the evolution of questionnaire scores and apply Dynamic Mode Decomposition (DMD) to describe the asymptotic behavior of the dynamical system. The analysis indicates that risk decreased for youth who enrolled in GRYD prevention services, while it increased or remained the same for those who were in the control group. We augment these observations using a difference-in-differences (DID) model, showing that the decrease in risk can be attributed to enrolment in prevention services. We draw a connection between DMD and DID using both mathematical analysis and empirical evidence from the questionnaire data. Combining DMD and DID with factor analysis, we investigate the effectiveness of prevention services with respect to different attitudinal domains. We conclude that gang prevention is most effective in impacting attitudes towards negative peer obedience and least effective in impacting attitudes towards violence for self defense. Our analytical approach can be extended to other types of repeated questionnaires.