Financial Input Structure and Financial GDP Matching in the Greater Bay Area: A Spatiotemporal Ranking Analysis

Abstract

This study examines the spatiotemporal matching relationship between multi-dimensional financial inputs and financial GDP across 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2024. Five financial input indicators-insurance premium income, fixed capital investment, number of financial employees, total loan balance, and credit bond issuance-are selected, with financial industry GDP as the output indicator. Based on balanced panel data, the entropy weight method is employed to construct a comprehensive financial input index, and a ranking matching approach is adopted to assess input-output coordination. The results indicate that financial development in the GBA maintained steady growth over the period, alongside obvious spatial differentiation, with core cities leading the region and peripheral cities lagging behind. Capital market and banking activities play a dominant role in shaping regional financial disparities. Though the overall matching degree improved gradually, structural mismatches remain a key challenge in several cities. The findings offer empirical support for optimizing resource allocation and promoting balanced, high-quality financial development in the GBA.

Keywords: Guangdong-Hong Kong-Macao Greater Bay Area; Financial Input Structure; Financial GDP; Matching Degree; Entropy Weight Method

DOI: 10.7176/JESD/17-4-02

Publication date: June 30^th 2026