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Fiscal decentralization, financial efficiency and upgrading the industrial structure: an empirical analysis of a spatial heterogeneity model

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  • Jianmin Liu
  • Xiaomei Hu
  • Jinguang Wu

Abstract

From the perspective of spatial heterogeneity and using data from 281 prefecture-level cities in China over the 2003–2012 period, we empirically test the interactions and differences in the spatial effects through which fiscal decentralization and financial efficiency influence the upgrading of regional industrial structure. The results indicate that regional differences in fiscal decentralization and financial efficiency lead to significant spatial heterogeneity in upgrading the industrial structure. The interaction mechanism between fiscal decentralization and financial efficiency plays a positive role in promoting the upgrading of the regional industrial structure, which is subject to organic integration between fiscal systems and financial development. Moreover, there is significant spatial dependence in the effects of fiscal decentralization and financial efficiency on upgrading the regional industrial structure, the ‘high-lying-land’ effects and the ‘low-lying-land’ effects coexist in the spatial pattern.

Suggested Citation

  • Jianmin Liu & Xiaomei Hu & Jinguang Wu, 2017. "Fiscal decentralization, financial efficiency and upgrading the industrial structure: an empirical analysis of a spatial heterogeneity model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 181-196, January.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:1:p:181-196
    DOI: 10.1080/02664763.2016.1252733
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    References listed on IDEAS

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    1. James P. LeSage, 2004. "A Family of Geographically Weighted Regression Models," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 11, pages 241-264, Springer.
    2. Yee Leung & Chang-Lin Mei & Wen-Xiu Zhang, 2000. "Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model," Environment and Planning A, , vol. 32(1), pages 9-32, January.
    3. Lee, Jong-Wha, 1996. "Government Interventions and Productivity Growth," Journal of Economic Growth, Springer, vol. 1(3), pages 391-414, September.
    4. Wahab, Mahmoud, 2011. "Asymmetric output growth effects of government spending: Cross-sectional and panel data evidence," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 574-590, October.
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    Cited by:

    1. Tinghui Wang & Qi Fu & Yue Wang & Mengfan Gao & Jinhua Chen, 2022. "The Interaction Mechanism of Fiscal Pressure, Local Government Behavioral Preferences and Environmental Governance Efficiency: Evidence from the Yangtze River Delta Region of China," IJERPH, MDPI, vol. 19(24), pages 1-22, December.
    2. Yuchen Song & Jingshu Ma & Shuai Guan & Yongfu Liu, 2022. "Fiscal Decentralization, Regional Innovation and Industrial Structure Distortions in China," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    3. Malkina, M. Yu., 2018. "The determinants of budget revenues of Russian regions," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 4(3), pages 95-104.
    4. Xu, Yujie & Wang, Yinan, 2023. "Has financial development made income more equal? – From the perspective of regional development imbalance," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Decai Tang & Ziqian Zhao & Wenwen Shen & Jianqun Zhang & Yuehong Kong & Valentina Boamah, 2022. "Research on the Impact of Digital Finance on the Industrial Structure Upgrading of the Yangtze River Economic Belt from the Perspective of R&D Innovation," Sustainability, MDPI, vol. 15(1), pages 1-14, December.

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