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Input–Output Efficiency of Urban Agglomerations in China: An Application of Data Envelopment Analysis (DEA)

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  • ChuangLin Fang
  • XingLiang Guan
  • ShaSha Lu
  • Min Zhou
  • Yu Deng

Abstract

Urban agglomerations (UAs) in China play a vital role in the distribution of productive forces and constitute the most dynamic and potentially rich core areas for future economic development. However, the rapid economic growth and high-intensity interactions seen in relation to these areas, results of the high population densities and aggregation of industries in UAs, also pose significant ecological threats to the environment. This paper attempts to analyse changing trends in the input–output efficiency of UAs in China based on the data envelopment analysis (DEA) approach. The paper investigates the DEA efficiency of UAs with different population sizes and geographical locations, explores the relationship between the elements that make up a decomposed model of efficiency and compares the efficiency performance of China’s UAs with that of 35 central cities. Moreover, the exogenous factors determining the input–output efficiency of UAs, the question of how to improve UAs’ efficiency performance, as well as the focus of future research are also discussed. A number of valuable implications have been drawn from the study, which may be helpful to the task of understanding more deeply the high-density aggregation effects of UAs in China.

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  • ChuangLin Fang & XingLiang Guan & ShaSha Lu & Min Zhou & Yu Deng, 2013. "Input–Output Efficiency of Urban Agglomerations in China: An Application of Data Envelopment Analysis (DEA)," Urban Studies, Urban Studies Journal Limited, vol. 50(13), pages 2766-2790, October.
  • Handle: RePEc:sae:urbstu:v:50:y:2013:i:13:p:2766-2790
    DOI: 10.1177/0042098013477707
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    Cited by:

    1. Ying Long & Kang Wu, 2017. "Simulating Block-Level Urban Expansion for National Wide Cities," Sustainability, MDPI, vol. 9(6), pages 1-19, May.
    2. Shasha Lu & Xingliang Guan & Chao He & Jiali Zhang, 2014. "Spatio-Temporal Patterns and Policy Implications of Urban Land Expansion in Metropolitan Areas: A Case Study of Wuhan Urban Agglomeration, Central China," Sustainability, MDPI, vol. 6(8), pages 1-26, July.
    3. Ze Xu & Jianjun Zhang & Chu Li & Zhenyu Li & Yongheng Rao & Tianyu Lu, 2017. "A Road to Sustainable Development of Chinese Cities: A Perception of Improving Urban Management Efficiency Based on Two-Level Production Factors," Sustainability, MDPI, vol. 9(12), pages 1-16, November.
    4. Wei Qi & Ying Gao & Qian Zhang, 2017. "Spatiotemporal Dynamics of Beijing’s Urbanization Efficiency from 2005 to 2014," Sustainability, MDPI, vol. 9(12), pages 1-17, November.
    5. Peixin Li & Chen Wang & Xueliang Zhang, 2017. "Did city cluster development help improve labor productivity in China?," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 22(1), pages 122-135, January.
    6. Xiaodong Gong & Jiti Gao & Xuan Liang & Xin Meng, 2018. "Inter-regional spillover and intra-regional agglomeration effects among local labour markets in China," Monash Econometrics and Business Statistics Working Papers 20/18, Monash University, Department of Econometrics and Business Statistics.

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