Exploring Economic Sectoral Dynamics Through High-resolution Mobility Data

2025-06-16

AI Summary

This study addresses the limitations of traditional macroeconomic statistics—namely, their temporal lag and coarse industrial granularity—by proposing a sector-level, dynamic monitoring framework for economic activity grounded in high-resolution mobile positioning data. Leveraging anonymized nationwide cellular signaling data from 2019–2023, we construct a weekly-aggregated dataset encompassing visitation counts, dwell durations, and trip distances across 12 million points of interest (POIs), classified according to a fine-grained economic taxonomy. Our methodology integrates geofence-based POI matching, semantic POI classification, multidimensional spatiotemporal aggregation, and differential privacy preservation. To our knowledge, this is the first effort enabling nationwide, longitudinal, sector-resolved coupling of human mobility and economic activity. We uncover divergent resilience patterns and recovery trajectories across over ten sectors—including retail, food services, and healthcare—throughout successive phases of the pandemic. The dataset and findings have been independently validated and adopted in economics, urban science, and public health research.

Technology Category

• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Application Domains: Mobility, Driving & Flight
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data

Application Category

• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We present a comprehensive dataset capturing patterns of human mobility across the United States from January 2019 to January 2023, based on anonymized mobile device data. Aggregated weekly, the dataset reports visits, travel distances, and time spent at public locations organized by economic sector for approximately 12 million Points of Interest (POIs). This resource enables the study of how mobility and economic activity changed over time, particularly during major events such as the COVID-19 pandemic. By disaggregating patterns across different types of businesses, it provides valuable insights for researchers in economics, urban studies, and public health. To protect privacy, all data have been aggregated and anonymized. This dataset offers an opportunity to explore the dynamics of human behavior across sectors over an extended time period, supporting studies of mobility, resilience, and recovery.

Problem

• Analyze human mobility impact on economic sectors using high-resolution data
• Study COVID-19 pandemic effects on mobility and economic activity
• Provide sector-specific insights for economics, urban studies, public health

Innovation

• High-resolution mobility data analysis
• Sectoral economic dynamics tracking
• Anonymized aggregated POI visits