The Impact of Financial Crisis on Electricity Demand: A Case Study of North China

Abstract

The electricity consumption and economic growth are highly correlated. The financial crisis in 2008 brought a negative effect on China's economic growth, which also influenced the electricity consumption. The electricity demand of North China region was also greatly influenced by this financial crisis, the whole social electricity consumption growth rate of which decreased by 14.31% in 2008 compared to that in 2007. In order to analyze the random impulse effect of the financial crisis on the demand of electricity in North China, the monthly data is decomposed into deterministic trend, stochastic impact effect, and periodic trend using the Beveridge-Nelson decomposition method. After comparatively analyzing the impulse effect of the financial crisis on electricity consumption of six provinces in North China, we can draw the conclusions: (1) the electricity consumption of the whole society and the secondary industry are under larger negative impacts, and the random impulse effect of the secondary industry is more intense; and (2) the impact of the financial crisis on the tertiary industry, which is mainly influenced by seasonal changes, is smaller. Finally, some policy implications are proposed.

Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis

“…For China, Yuan et al (2010) showed that the decline in exports due to the crisis led to a 7.33% decrease in GDP and a 9.21% decrease in energy consumption. Zhao et al (2016) confirmed these results for China by considering electricity consumption, which decreased by 14.31% in 2008.…”

Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

“…During the data preprocessing step, the B-N disintegration approach is used to disintegrate the nonlinear and unstable wind electric power data series into a deterministic component, a cyclic term, and a stochastic impact effect. In previous research, the B-N decomposition method has been used to discuss the influence of a financial crisis on GDP and electricity consumption [48,49]. For this research, we explore the possibility of applying the B-N decomposition method to a wind power forecasting issue.…”

“…If it is verified that the data sequence has a first-order difference, the details of the procedures of the B-N disintegration approach are as below [49,51,52].…”

The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data

“…All the statistical analysis and model regressions were processed statistically by STATA12.0 software. In addition to income, residential electricity consumption can be influenced by a variety of factors, such as the electricity price, the alternative energy price, the urbanization rate, geographic characteristics, and the weather [9][10][11][12][13][14][15]. Similar to Schmalensee et al [8], we include only per capita income in the reduced function, leaving the other explanatory variables uncontrolled for the following reasons.…”

“…The true underlying relationship, however, is typically non-deterministic, and each country's relationship takes a unique form. Yoo and Lee detected an inverted U-shaped relationship between per capita electricity consumption and per capita income in OECD (Organization for Economic Co-operation and Development) and developed countries [14]. McNeil and Letschert described an S-shaped relationship between household income level and appliance ownership [15].…”