江苏省GDP时间序列分析模型及其运用
时间:2020-02-28 20:21 来源:毕业论文 作者:毕业论文 点击:次
| 摘要国内生产总值（GDP）是现代国民经济核算体系的核心指标，在国民经济发展过程中，GDP无疑是衡量一个国家综合实力的重要指标。国内生产总值（GDP）是指在一定时期内，一个国家或一个地区的经济活动中所生产出的最终商品和劳务的市场价值，常被认为是衡量国家或地区经济状况的最佳指标。这个指标不仅能从总体上独度量国民产出和收入规模，也能从总体上度量经济波动和经济周期状态。成为宏观经济中最受关注的经济数据，被认为是衡量国民经济发展，判断宏观经济运行状况的一个重要指标，也是政府制定经济发展战略和政策的一个重要指标。对它进行分析并作出及时准确地预测具有重要的实际意义和理论意义。45650 本文在时间序列分析理论的基础上，运用时间序列模型对江苏省GDP进行研究和预测，以江苏省1978到2013年36年的国内生产总值（GDP）为数据基础资料，利用EVIEWS软件进行时间序列分析，包括数据的平稳化处理、模型识别、参数估计、建立时间序列模型、并对模型进行检验，综合各种条件，根据AIC信息准则确定最终模型为自回归移动平均模型ARIMA(1，1，(2))。利用该模型对江苏省GDP进行2008-2013年静态预测，将预测值与实际值进行比较，结果表明相对误差在5%以内，模型预测效果较好。因此，继续用ARIMA(1，1，(2))模型对江苏省GDP未来五年进行预测。 [毕业论文关键词]： 时间序列分析法；国内生产总值；ARMA模型；ARIMA模型；预测 Abstract Gross domestic product (GDP) is the core of modern national economic accounting system, in the process of the development of national economy, GDP is the important index to measure a country's comprehensive strength. Gross domestic product (GDP) is to point to in a certain period, a country or a region's economic activity in the produce market value of final goods and services are often considered to be the best indicators of national or regional economic conditions. This index can not only overall measurement scale of national output and income alone, also can measure the overall economic fluctuations and economic cycle. Become the most closely watched economic macroeconomic data, is regarded as a measure of national economic development, the judgment is an important indicator of macroeconomic performance, also is the government to make economic development strategy and policy of an important indicator. To analyze it and make a timely and accurate prediction has important practical significance and theoretical significance. In this paper, on the basis of the theory of time series analysis, using the time series model to study and predict GDP in jiangsu province and in jiangsu province from 1978 to 2013 in 36 years of gross domestic product (GDP) as the data basic data, use EVIEWS software for time series analysis, including the tranquilization of data processing, model identification, parameter estimation, time series model is established, and the test model, integrated all sorts of conditions, information according to the AIC criterion to determine the final model for the autoregressive moving average model ARIMA (1, 1, (2)). By using the model 2008-2013 static projections for GDP in jiangsu province, the predicted values and actual values, the results show that the relative error within 5%, the model prediction effect is better. Therefore, continue to use ARIMA (1, 1, (2)) model to predict GDP over the next five years in jiangsu province. [Key Words]： Gross domestic product (GDP) ； ARMA model；ARIMA model；predict 目 录 摘 要 I Abstract…II 1 绪论 - 1 - 1.1研究背景和现状 - 1 - 1.1.1研究背景 - 1 - 1.1.2 国内外研究现状 - 1 - 1.2 本文的主要研究工作 - 1 - (责任编辑：qin) |