Abstract
In modern time, time series analysis is especially used to establish a relatively simple model. And it can be used to forecast economic data, interpretation and hypothesis testing. Time series model was originally forecast primarily as a support tool. Therefore, economists create a set of methods that time series can be decomposed as the trend, seasonal, cyclical, and no rules of composition. 1970, Box and Jenkins proposed time series analysis theory which base on the theory of random. So that time series analysis methods rose to a new level, and the prediction accuracy greatly improved. Stationary time series and non-stationary time series come form different data generating processes, they have different contents, properties and analysis technique. Autoregressive moving average model （ARMA model） is an important method of time series. It is a mixed form of autoregressive model (AR model) and moving average models (MA model).
Energy is an important guarantee of national development and security. And it is the power to promote the system of economical society operation. But energy using will cause serious ecological problems in the environment. Energy is the lifeblood of the economy. And it is an important guarantee of the development of national economy and the people's standard of living increase. Chinese economy is in a stable period of development so that energy demand in the coming decades will be rapid growth. Dependence on world energy markets of china will continue to increase. Therefore, the paper will use the ARMA model and the calendar year 1990-2007 national energy elasticity coefficient of energy development and the relationship between national economic growth analysis and forecasting, and in 2008 electricity consumption in each province to do cluster analysis.
Key words: ARMA model energy national economy
