Construction of Urban Agglomerations to Promote the Economic Growth of Counties: Causal Inference Based on Double Machine Learning

Harnessing the effects of radiation-driven urban agglomerations on county-level economic growth is essential for fostering regional coordinated development. This study uses panel data from 152 counties in the Yangtze River Delta from 2000 to 2021 to evaluate how urban agglomeration construction influences county economic growth. A combination of double machine learning models and causal mediation analysis is used to measure policy impacts and identify underlying mechanisms. The findings highlight several key points: (1) Urban agglomeration construction significantly and positively influences county economic growth. This result remains reliable after various checks, including different model specifications and changes in dependent variables, confirming the robustness of the findings. (2) The positive effect of urban agglomeration construction on county economic growth occurs mainly through two pathways: increasing industrial clustering and promoting urbanization within counties. Both factors play a substantial role in economic expansion at the county level. (3) The impact of urban agglomeration construction on county economic growth varies across different urban agglomerations. Specifically, the Shanghai urban agglomeration shows the strongest marginal effect on economic development, while the Ningbo urban agglomeration exhibits the weakest effect. Notably, the Hefei urban agglomeration does not show a significant effect on county economic growth during the study period. This research provides new insights for developing countries aiming to optimize regional spatial planning and improve county-level urbanization amid ongoing urban development.