| 摘要: |
| 为了研究我国居民消费水平的变化趋势，将预测我国未来4年（2020—2023年）的居民消费水平，选择的样本数据是从2002—2019年这18年间的我国居民消费水平，构造基于ARIMA(2,1,1)模型、Holt Winters无季节模型以及多元回归模型的诱导有序加权算术平均(IOWA)算子组合预测模型，主要运用使偏差平方和最小的组合预测优化方法预测我国未来4年（2020—2023年）的居民消费水平，并对诱导有序加权算术平均IOWA算子组合预测模型进行了有效性评价；以新发展格局的内循环和外循环为依据，寻找解释变量并建立多元回归模型；研究发现：IOWA算子组合预测模型预测精度大于各单项预测模型，并且各项误差均显著低于单项预测模型，未来4年我国居民消费水平不会有大幅度波动，但有小幅度下降的趋势。 |
| 关键词: 居民消费水平 IOWA算子 组合预测模型 |
| DOI： |
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| Combined Prediction Research on China’s Residents Consumption Level Based on IOWA Operator |
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LI Ying, ZHUANG Ke-jun
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School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Anhui Bengbu 233030, China
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| Abstract: |
| In order to study the changing trend of China’s residents consumption level to predict the residents consumption level in next four years (2020—2023), this paper selects the samples of China’s residents consumption level in 18 years from 2002 to 2019, constructs induced ordered weighted arithmetic averaging (IOWA) operator combination forecast model based on ARIMA (2,1,1) model, Holt Winters no season model and multivariate regression model, mainly uses the combined prediction optimization method with minimizing error square sum to predict the residents consumption level in next four years (2020—2023), evaluates the effectiveness of induced ordered weighted arithmetic averaging (IOWA) operator combination prediction model, searches explanatory variables and sets up multivariate regression model based on inner cycle and outer cycle of new development pattern. Research finds that the prediction accuracy of IOWA operator combination prediction model is higher than that of single prediction model and each error is significantly lower than that of the single prediction model. In the next four years, the consumption level of China’s residents will not fluctuate largely but tend to decline in a small range. |
| Key words: resident consumption level IOWA operator combined prediction model |
