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国内生产总值GDP是我国国民经济的重要的综合统计指标,也是我国经济核算体系中的核心统计指标,它反应了一国的经济实力,结构布局和市场规模,对其进行分析预测的过程中,能得到重要的理论和现实的意义。而在经济预测中ARIMA模型既考虑了随机波动所造成的干扰,又体现了经济现象对时间序列的依存,对于短期趋势来说,其预测效果较为准确,是使用率较高的方法之一。本文时间序列的理论为基础,考虑ARIMA模型的应用原则,以1984至2013年我国GDP序列数据为基础,运用Eviews软件,建立时间序列模型,做出分析与预测。
Gross domestic product (GDP) is an important comprehensive statistical indicator of our country’s national economy as well as a core statistical indicator in our country’s economic accounting system. It reflects the economic strength, structural layout and market size of a country. During its analysis and forecast, , Can get important theoretical and practical significance. In the economic forecasting, the ARIMA model not only considers the interference caused by stochastic volatility, but also reflects the dependence of economic phenomena on the time series. For the short-term trend, the forecasting effect is more accurate and is one of the methods with higher utilization rate. Based on the theory of time series, this paper considers the application principle of ARIMA model. Based on China’s GDP sequence data from 1984 to 2013, we use Eviews software to establish the time series model and make analysis and prediction.