Dependence Analysis Of Electricity Consumption And GDP Based On Copula Function

Power industry is the main driving force source of national economic development.Maintaining a coordinated development of the electricity consumption and economic growth in a country is crucial.China's economy is currently in the middle stage of industrialization.China's economy is characterized by high energy-consuming economy, resource export-based economy.Economic development and consumption of electricity has a close correlation. In the power of investment and production decisions, often by studying the relationship of electricity consumption growth rate and the growth rate of gross domestic product, we based on future planning of the gross domestic product data to forecast consumption growth.At the same time, GDP is among the most concerned with the economy of macroeconomic statistics,and it is considered a measure of national economic development of the most important indicators. And because the calculation of GDP growth rate is very complex, many scholars in the study of economic issues, often through the consumption growth rate to determine a country's GDP growth rate. Consumption and GDP What is the relationship that exists between, many scholars have discussed. However, in discussing their relationship, still using the traditional linear correlation coefficient analysis, has great limitations. More popular use of the current correlation function Copula-based research methods to study the focus of this article. This article first introduces the relevance of commonly used indicators and Copula methods, and then collected 1984～2007 years of China's energy consumption and GDP data, building energy consumption and GDP correlation model, and with the classic model of correlation analysis comparing the use of Copula function can achieve better results, results show that there is between the two strong correlation, and further consumption growth rate and the relationship between GDP growth were discussed.Electricity consumption and GDP in constructing the correlation model, first using kernel density estimation method to determine power consumption growth and GDP growth rate of marginal distribution, and then use kernel density estimation method to estimate the joint distribution of the density function, and then find the distribution function, re-use of Sklar's theorem, using interpolation methods derived Copula function Copula finally calculate a variety of relevant indicators, such as Kendall'sτ, Spearman'sρ, and compared with the linear correlation coefficientγ.