TY - JOUR
T1 - Spatial patterns and influencing factors of financial agglomeration in Guangdong-Hong Kong-Macao Greater Bay Area
AU - Wei, Yujun
AU - Wang, Mengbin
AU - Wei, Xiaokun
AU - Yuan, Fan
AU - Fan, Jie
AU - Ba, Shusong
PY - 2024
Y1 - 2024
N2 - The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) represents a significant economic zone with a diverse financial landscape. Understanding the spatial distribution of financial resources within this area is crucial for promoting balanced economic growth and financial development. This study investigates the spatial patterns of financial agglomeration in the GBA, identifying key influencing factors and assessing their impact on the region’s financial landscape. We employ the entropy value method to evaluate financial agglomeration levels across the GBA’s cities. Additionally, we use spatial econometric techniques to analyze the spatial correlations and the Geo-Detector model to determine the primary factors influencing financial agglomeration. The analysis reveals an overall increase in financial agglomeration, with significant disparities among cities. Key factors driving this agglomeration include transportation infrastructure, overseas trade, foreign direct investment (FDI), and technological advancements. Hong Kong and Shenzhen display notable unevenness in the distribution of financial industries. The interplay between finance, technology, and industrial sectors suggests considerable development potential. Understanding and optimizing the spatial distribution of financial resources is essential for fostering high-quality financial development and sustainable economic growth in the GBA. This study provides insights that can inform policy decisions aimed at enhancing financial integration and cooperation within the region.
AB - The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) represents a significant economic zone with a diverse financial landscape. Understanding the spatial distribution of financial resources within this area is crucial for promoting balanced economic growth and financial development. This study investigates the spatial patterns of financial agglomeration in the GBA, identifying key influencing factors and assessing their impact on the region’s financial landscape. We employ the entropy value method to evaluate financial agglomeration levels across the GBA’s cities. Additionally, we use spatial econometric techniques to analyze the spatial correlations and the Geo-Detector model to determine the primary factors influencing financial agglomeration. The analysis reveals an overall increase in financial agglomeration, with significant disparities among cities. Key factors driving this agglomeration include transportation infrastructure, overseas trade, foreign direct investment (FDI), and technological advancements. Hong Kong and Shenzhen display notable unevenness in the distribution of financial industries. The interplay between finance, technology, and industrial sectors suggests considerable development potential. Understanding and optimizing the spatial distribution of financial resources is essential for fostering high-quality financial development and sustainable economic growth in the GBA. This study provides insights that can inform policy decisions aimed at enhancing financial integration and cooperation within the region.
U2 - 10.1371/journal.pone.0306301
DO - 10.1371/journal.pone.0306301
M3 - Journal article
C2 - 39088454
SN - 1932-6203
VL - 19
JO - PLOS ONE
JF - PLOS ONE
IS - 8
M1 - e0306301
ER -