基于GMDH的宏观经济短期预测模型
A short-term macroeconomic Forecasting model based on GMDH
作者：陈厚积(明尼苏达大学双城分校文理学院， 明尼阿波利斯 55455)；胡晓兵(四川大学机械工程学院)；邓希(四川大学机械工程学院)
Author：CHEN Hou-Ji(School of Arts and Sciences, University of Minnesota Twin Cities, Minneapolis 55455)；HU Xiao-Bing(College of Mechanical Engineering, Sichuan University, Chengdu 610065, China)；DENG Xi(College of Mechanical Engineering, Sichuan University, Chengdu 610065, China)
收稿日期：2020-07-09 年卷（期）页码：2020,57(5):915-919
期刊名称：四川大学学报: 自然科学版
Journal Name：Journal of Sichuan University (Natural Science Edition)
关键字：宏观经济短期预测，GMDH，二次自回归模型
Key words：economic early warning, prosperity index, self-organizing data mining algorithm
基金项目：
中文摘要
传统的宏观经济短期预测研究通常基于定量或定性预测模型，而GMDH 算法兼具定性定量的特点，建立了基于GMDH 自回归模型的混合预测模型数学模型来进行宏观经济短期预测，应用相关的统计数据做实证分析，将所得结果与传统GMDH模型、二次自回归模型进行了比较.结果表明，本文提出的混合预测模型具有良好的预测精度，是一种有效的宏观经济短期预测手段.
英文摘要
Traditional short term macroeconomic forecasting research is usually based on quantitative or qualitative forecasting models, while GMDH algorithm has both qualitative and quantitative characteristics. This work proposes a mixed mathematical prediction model to forecast short term macroeconomic. The model is a combination of GMDH autoregressive model and quadratic autoregressive model. Relevant statistical data are used for empirical analysis, and the results are compared with the traditional GMDH model and the quadratic autoregressive model. The results show that the hybrid forecasting model proposed in this paper has good forecasting accuracy and is an effective means of economic forecasting.
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