Abstract
Over the past three decades, China’s economy has witnessed remarkable growth, with an average annual growth rate over 9%. However, China also faces great challenges to balance this spectacular economic growth and continuously increasing energy use like many other economies in the world. With the aim of designing effective energy and environmental policies, policymakers are required to master the relationship between energy consumption and economic growth. Therefore, in the case of North China, a multivariate model employing panel data analysis method based on the Cobb-Douglas production function which introduces electricity consumption as a main factor was established in this paper. The equilibrium relationship and causal relationship between real GDP, electricity consumption, total investment in fixed assets, and the employment were explored using data during the period of 1995–2014 for six provinces in North China, including Beijing City, Tianjin City, Hebei Province, Shanxi Province, Shandong Province and Inner Mongolia. The results of panel co-integration tests clearly state that all variables are co-integrated in the long term. Finally, Granger causality tests were used to examine the causal relationship between economic growth, electricity consumption, labor force and capital. From the Granger causality test results, we can draw the conclusions that: (1) There exist bi-directional causal relationships between electricity consumption and real GDP in six provinces except Hebei; and (2) there is a bi-directional relationship between capital input and economic growth and between labor force input and economic growth except Beijing and Hebei. Therefore, the ways to solve the contradiction of economic growth and energy consumption in North China are to reduce fossil energy consumption, develop renewable and sustainable energy sources, improve energy efficiency, and increase the proportion of the third industry, especially the sectors which hold the characteristics of low energy consumption and high value-added.
Highlights
With the implementation of the “Reform and Opening-up” policy in the early 1980s, China has achieved rapid economic growth, especially in manufacturing, which has emerged as the largest industry
Yu and Wu [44] analyzed the dynamic relationship between capital, labor force, electricity consumption and economic growth taking electricity demand as an input of the Cobb-Douglas production function in China during the period of 1990–2012, and the results indicate that the labor is the main driving force of the economic growth in China, the contribution rate of capital goes up steady, and the contribution of electricity to economic growth increases in fluctuation
We can obtain that, generally speaking, the real total investment in fixed assets makes the largest contribution to real gross domestic product (GDP) growth, followed by the electricity consumption
Summary
With the implementation of the “Reform and Opening-up” policy in the early 1980s, China has achieved rapid economic growth, especially in manufacturing, which has emerged as the largest industry. Lin [18] employed co-integration and error correction model to study the relationship between electricity consumption and economic growth in China, and the results show that there is a long-term equilibrium relationship between GDP, capital, labor force and electricity demand. In order to accurately compare the different contributions of electricity consumption and the input of labor force and capital investment to the economic growth of six provinces in North China, including Beijing, Tianjin, Hebei, Shanxi, Shandong and Inner Mongolia, the panel data model is employed to analyze the co-integration and causal relationships between these variables in different provinces. The exploration on the contribution of energy consumption, capital investment and labor force to the economic growth and the causal relationship among these variables is conducted in this paper, based on the data of six provinces in North China employing panel data model in a single sector production function framework.
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