(The following topics include but are not limited to)
Track 1: Econometrics
Machine learning in econometrics
Real-time data analysis
Alternative data application
Data privacy and ethics
Predictive modeling
Robustness and model validation
High-dimensional econometrics
Time series innovation
Structured estimation based on big data
Spatial econometrics 2.0
Digital experimentation
Financial econometrics
Measurement challenges
Network econometrics
Computational innovation technologies
Deep learning applications
Policy analysis and evaluation
Reproducibility and ethical issues
New data types
Track 2: Big Data
Big data analysis methods
Data mining and knowledge discovery
Real-time data processing and application
Big data and cloud computing
Data visualization technology
Data privacy and security
Big data and social network analysis
Big data-driven decision support systems
Big data and sustainable development
Big data finance
Big data applications
Big data and artificial intelligence
Track 3: Mathematical Statistics
Applied mathematics
High-dimensional data analysis
Statistical machine learning
Bayesian statistical methods
Survival analysis and event models
Non-parametric statistical methods
Experimental design and analysis
Big data statistical methods
Causal inference in statistics and economics
Small sample economic statistical methods
Economic analysis of networks and social media
Economic cycle analysis and statistical modeling
Application of multivariate statistical methods in economic analysis