Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 513, Issue -, Pages 189-201Publisher
ELSEVIER
DOI: 10.1016/j.physa.2018.08.168
Keywords
Capital market; Industrial structure upgrading; Spatial spillover effect; Spatial panel data model
Categories
Funding
- National Natural Science Foundation of China [61603011, 6177029]
- Beijing Social Science Foundation [16JDGLC005]
- International Postdoctoral Exchange Fellowship Program, China [20170016]
- UPE, Brazil [PFA2016, PIAEXT2016]
- FACEPE, Brazil [APQ-0565-1.05/14]
- CAPES, Brazil
- CNPq, Brazil
- NSF, USA [PHY-1505000, CMMI-1125290, CHE-1213217]
- DTRA, USA [HDTRA1-14-1-0017]
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Using the theoretical framework of spatial econometrics, we estimate the impact of capital markets, i.e., stock markets, medium-and-long term bond markets, and medium-and-long term loan markets, on industrial structure upgrading (ISU) across 31 provinces in China from 1998 to 2015. We apply an explanatory spatial data analysis (ESDA) to detect the presence of spatial dependence and use a spatial Durbin model (SDM) to examine spatial distribution and spatial association. Although our overall estimation results from the 31 provinces indicate a degree of correlation between capital markets and industrial structure upgrading, the magnitude of spatial spillover effects in three sub-markets on ISU differ. We divide the 31 provinces into four economic zones, and explore the impact of three submarkets on ISU in the eastern zone, central zone, western zone, and northeastern zone. Using our results, we provide policy suggestions that better facilitate ISU in China. (C) 2018 Elsevier B.V. All rights reserved.
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