Industrial electricity consumption, human capital investment and economic growth in Chinese cities
Yang Chen and
Zheng Fang
Economic Modelling, 2018, vol. 69, issue C, 205-219
Abstract:
We examine the cointegrating and Granger causal relationships between economic growth, industrial electricity consumption and human capital in China using a panel consisting of 210 prefecture cities across a period of 2003–2012. Applying continuously-updated fully modified panel estimation, we find that industrial electricity consumption has a significantly larger impact on economic prosperity than physical and human capital investment. Industrial electricity consumption plays a dominant role to boost growth in the center and the west, while human capital contributes most to the growth of the east. And notably, core cities are the largest beneficiaries from the growth of production inputs. Accounting for heterogeneity and cross-section dependence, results from the Granger non-causality tests suggest that the implementation of electricity-saving strategy is more feasible in inland China without hampering the economic growth and development of human capital. In the east, regulators must make efforts to increase investment in building electricity infrastructure to connect demand with supply to avoid shortage of power having an adverse effect on economic growth. Reducing the urban-rural gap in electricity tariffs and improving development of rural electricity network are rationalized to achieve sustainable economic development for the urban community in China.
Keywords: Industrial electricity consumption; Human capital investment; Heterogeneous panel causality; Chinese cities (search for similar items in EconPapers)
JEL-codes: C50 Q43 Q48 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (34)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:69:y:2018:i:c:p:205-219
DOI: 10.1016/j.econmod.2017.09.021
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