Labour Mobility and Urban Income Convergence in the Greater Bay Area

Abstract

In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), rapid economic integration and an increase in cross-city labour migration are reshaping the regional income distribution pattern. However, it remains inconclusive whether labour mobility accelerates or hinders the convergence of inter-city incomes. Using unbalanced long panel data covering 11 Bay Area cities from 2010 to 2024, this paper examines the dynamics of unconditional and conditional convergence by combining the σ convergence indicator with fixed effects β convergence regression. The model controls for population growth, industrial structure, and fiscal factors, and remains robust when Hong Kong and Macau are excluded, or when three-year moving average variables are introduced. The results show that the cross-sectional dispersion of the log of GDP per capita between cities is declining, which supports the idea of σ-convergence. Further analysis using fixed effects estimation reveals significant conditional β-convergence: each percentage point increase in the relative income gap leads to a growth rate increase of approximately 0.12 percentage points in the next period. Net labour inflow (as measured by the population growth rate) significantly accelerates the rate of convergence in PRD cities, but has a limited effect on Hong Kong and Macau, highlighting regime heterogeneity. Multiple robustness tests verify the direction and magnitude of the results. The policy implications are twofold. First, relax household registration and professional qualification barriers to reduce migration frictions and unleash the convergence dividend of labour mobility. Second, enhance the equalisation of public service provision through fiscal synergies to complement labour mobility and further narrow the income gap. In future, the study could be expanded to include migration flows by skill level and the impact of economic shocks after 2025.