Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)

Addressing regional disparities while pursuing sustainable development has become a critical policy challenge. This study develops a meta parallel two-stage dynamic range directional measure (RDM) directional distance function (DDF) data envelopment analysis (DEA) model to evaluate the efficiency of poverty reduction (SDG 1) and decent work and economic growth (SDG 8) across 30 provinces in China. Given uneven regional development, the provinces are grouped into eastern, central, and western regions, and kernel density estimation is employed to examine the spatial and temporal evolution of efficiency. The results indicate that: (1) The overall efficiency is moderate, with an average score of 0.67, highest in the eastern region, followed by the western, and lowest in the central region. (2) The efficiency of SDG 8 (0.93) significantly exceeds that of SDG 1 (0.87), while the regional ranking remains consistent with the overall efficiency. (3) The technology gap among the three regions shows dynamic changes: the western region has overtaken the eastern region to become the most advanced. In contrast, the central region continues to lag, and its gap with the other regions is steadily widening. First pubished online 29 October 2025

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Publication Details

Journal
Technological and Economic Development of Economy
Published
2025-10-29
DOI
https://doi.org/10.3846/tede.2025.24894
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
0.00

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article

Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)

Mingle Chen, Yung‐ho Chiu, Wei Hu, Yanan Sun et al.
Technological and Economic Development of Economy
Efficiency Analysis Using DEA
article

Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)

Mingle Chen, Yung‐ho Chiu, Wei Hu, Yanan Sun, Tao Shi-gui, Li Ji, Tai‐Yu Lin
article en

Abstract

Addressing regional disparities while pursuing sustainable development has become a critical policy challenge. This study develops a meta parallel two-stage dynamic range directional measure (RDM) directional distance function (DDF) data envelopment analysis (DEA) model to evaluate the efficiency of poverty reduction (SDG 1) and decent work and economic growth (SDG 8) across 30 provinces in China. Given uneven regional development, the provinces are grouped into eastern, central, and western regions, and kernel density estimation is employed to examine the spatial and temporal evolution of efficiency. The results indicate that: (1) The overall efficiency is moderate, with an average score of 0.67, highest in the eastern region, followed by the western, and lowest in the central region. (2) The efficiency of SDG 8 (0.93) significantly exceeds that of SDG 1 (0.87), while the regional ranking remains consistent with the overall efficiency. (3) The technology gap among the three regions shows dynamic changes: the western region has overtaken the eastern region to become the most advanced. In contrast, the central region continues to lag, and its gap with the other regions is steadily widening. First pubished online 29 October 2025

Technological and Economic Development of EconomyVol. 32(2)
Nanjing Normal University (CN), Soochow University (TW), Nantong University (CN), Lexington City Schools (US), Xi’an Jiaotong-Liverpool University (CN), National Cheng Kung University (TW)
Government of Jiangsu Province, National Social Science Fund of China
Openalex Percentile: Top 63%
Efficiency Analysis Using DEA
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