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Imbalance measurement of regional economic quality development: evidence from China

Author

Listed:
  • Qiang Liu

    (Capital University of Economics and Business
    Beijing Key Laboratory of Megaregions Sustainable Development Modelling)

  • Shengxia Xu

    (Capital University of Economics and Business)

  • Xiaoli Lu

    (Capital University of Economics and Business)

Abstract

Imbalance of regional development trends is strongly correlated over time and across provinces, paralleled the growth of the economic quality and even influenced by exogenous variables. In this paper, a regional ‘two-way’ theory based on ‘input and output’ is proposed, reflecting the current state of economic quality development comprehensively. An ‘inverse absolute dispersion method’ came up with calculating the Quality of Economic Imbalance in Regional Development (QEIRD) after the measurement of economic quality is obtained by the total factor productivity (TFP). Moreover, the distribution of Chi-square is fitted to classify the grades of QEIRD, and the causes of QEIRD are analyzed via exogenous variables and regional decomposition under the panel data from China at the provincial level. The results indicate that the new method of measuring QEIRD based on TFP is scientific and reasonable in China at the country level. Secondly, the results obtained from the three regional decomposition ways are highly consistent, showing that the QEIRD from China has been diminishing, though not continuously and more so in some periods and regions, and being in a transition from stage three to stage two. Thirdly, the mainspring of total QEIRD is from the between-regions QEIRD; however, the rate of the within-region QEIRD is increasing cannot be neglected. In addition, exogenous variables have a crucial role in reducing QEIRD; it is a long-term and unremitting efforts to achieve stage one and move toward coordinated regional development in China.

Suggested Citation

  • Qiang Liu & Shengxia Xu & Xiaoli Lu, 2020. "Imbalance measurement of regional economic quality development: evidence from China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(2), pages 527-556, October.
    • Handle: RePEc:spr:anresc:v:65:y:2020:i:2:d:10.1007_s00168-020-00994-4
    DOI: 10.1007/s00168-020-00994-4
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    Cited by:

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    2. Kai Chen & Feng Guo & Shuang Xu, 2022. "The Impact of Digital Economy Agglomeration on Regional Green Total Factor Productivity Disparity: Evidence from 285 Cities in China," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    3. Xu Shengxia & Liu Qiang & Lu Xiaoli, 2021. "Measuring the Imbalance of Regional Development from Outer Space in China," Journal of Systems Science and Information, De Gruyter, vol. 9(5), pages 519-532, October.
    4. Peng Wang & Cong Cen & Xiaoyan Lin, 2023. "Internet development and the spatial optimization of regional productivity: Evidence from China," Growth and Change, Wiley Blackwell, vol. 54(4), pages 912-939, December.

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    More about this item

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • R5 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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