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随着经济全球化的深入,一国的经济实力在国家实力中的重要性越来越突出,世界各国都开始疯狂发展经济,以在国际竞争中求得一席之位。GDP(国内生产总值)从某个侧面反映了国家的经济实力,成为了各国衡量经济实力的重要指标。中国从改革开放之后,经济不断发展,GDP数据逐年增加,并呈现一定的规律。若能准确的预测中国之后几年的GDP数据,对国家宏观调控具有重要意义。本文在各项预测方法中选择了时间序列模型作为研究对象。从时间序列的基本概念出发,了解时间序列模型的种类与建模方法,以整套的时间序列建模理论为基础,在我国GDP数据上建立了ARMA模型,应用ARMA模型对2012年我国GDP数据进行预测,其预测结果与实际值之间相差很小,拟合结果比较满意;在此基础上,预测未来三年的GDP数据。
With the deepening of economic globalization, the importance of a country’s economic strength in its national strength has become more and more prominent. All countries in the world are beginning to develop their economy in a frenzied manner in order to gain a place in international competition. From a certain aspect, GDP (gross domestic product) reflects the country’s economic strength and has become an important indicator for all countries in measuring economic strength. After China’s reform and opening up, China’s economy continued to develop. Its GDP data increased year by year and showed certain laws. If we can accurately predict the GDP data of China after a few years, it is of great significance for the state’s macro-control. In this paper, the time series model is selected as the research object in various forecasting methods. Based on the basic concepts of time series, we know the types and modeling methods of time series models. Based on the complete time series modeling theory, ARMA models are established on China’s GDP data. The ARMA model is used to analyze China’s GDP data in 2012 Forecast, the difference between its forecast result and the actual value is very small, and the result of the fitting is satisfactory; on this basis, it forecasts the GDP data of the next three years.