# Dynamic Evolution and Convergence of the Coupled and Coordinated Development of Urban–Rural Basic Education in China

## TL;DR

This study examines how urban and rural basic education in China has developed together and become more balanced over time.

## Contribution

The paper introduces a novel method to measure and analyze the coordination and convergence of urban–rural basic education in China.

## Key findings

- The coordination level of urban–rural basic education improved significantly from 2011 to 2023, with decreasing disparities.
- High coordination in neighboring regions promotes local improvement, while low coordination hinders it.
- The study finds clear trends of convergence in urban–rural education development across China.

## Abstract

Understanding the coupled and coordinated development of China’s urban and rural basic education systems is crucial for fostering their interaction and synergistic growth. Using China’s provincial panel data from 2011 to 2023, this study measures the coupled and coordinated development level of urban–rural basic education (CCD-URBE) via the entropy weight method, G1-method and coupling coordination degree model. On this basis, the Dagum Gini coefficient decomposition method, traditional and spatial Markov chain models, as well as convergence test models are employed for empirical research. The results show that: (1) During the study period, the CCD-URBE across the nation and the four major regions improves significantly. Both intra-regional and inter-regional disparities show a consistent downward trend. Inter-regional disparities are the main source of the overall disparities, and the contribution rate of transvariation density to the overall disparities exhibits the most significant increase. (2) The CCD-URBE demonstrates strong stability, as most regions tend to maintain their original CCD-URBE grades. Meanwhile, neighborhood grades moderate the local transition probability significantly. Neighborhoods with high CCD-URBE promote the upward improvement of the local CCD-URBE, while those with low CCD-URBE inhibit it. (3) The CCD-URBE across the nation and the four major regions shows obvious trends of σ-convergence, absolute β-convergence, and conditional β-convergence. The central region, which has lower CCD-URBE, exhibits higher convergence speed. Based on these findings, targeted policy implications are derived.