Employment growth through labor flow networks

Area of Science:

• Labor Economics
• Network Science
• Economic Sociology

Background:

• Traditional labor economics models worker-firm matching using pools.
• Existing methods lack a comprehensive view of firm-to-firm worker transitions.

Purpose of the Study:

• To develop and characterize a novel labor flow network (LFN) for an entire economy.
• To analyze the topology and community structure of firm-worker interactions.
• To identify high-growth potential firms using network properties.

Main Methods:

• Utilized comprehensive national employment micro-data.
• Constructed a network where firms are nodes and worker migration between firms forms edges.
• Analyzed network properties like topology and community structure.

Main Results:

• Characterized the first economy-wide labor flow network (LFN).
• Demonstrated that a small fraction of firms (under 10%) account for substantial employment growth (nearly 90%).
• Showed LFNs can identify firms with high growth potential and high performance.

Conclusions:

• Labor flow networks offer a new lens for understanding labor market dynamics.
• Firm growth is highly concentrated, with a few firms driving the majority of job creation.
• A model of heterogeneous adaptive agents in a decentralized market can explain observed LFNs.