摘要
基于对消费总额及其结构的变动趋势和主要影响因素的分析,文章研究应用多元线性回归模型和自回归求积移动平均模型,考虑人口年龄结构变化、居民可支配收入等因素,预测了中国2018—2035年居民消费总量和2018-2020年中国居民对8类产品的消费量.预测结果表明:1)中国居民消费总量仍保持上升趋势,但消费增速逐步放缓,预计到2035年,中国居民消费总额达到1136011亿元,同比名义增长率呈现先下降后上升的趋势.2)中国居民消费结构不断优化,一方面食品烟酒占比不断下降,到2020年有望下降到27.6%;另一方面,交通通信、教育文化娱乐、医疗保健等服务性消费比重进一步提高,预计到2020年中国服务性消费占比约达到42.7%.基于对预测结果的分析,文章提出了提高居民可支配收入,扩展老年消费市场,扶持服务性消费产业等建议.
Based on the change trend and the main impacting factors analysis of China's household consumption and its structure,considering the population age structure,income and other factors,this study applied multiple linear regression model and the autoregressive integrated moving average model,forecasted China's household consumption in 2018-2035and expenditures on 8kinds of products in 2018- 2020.The results are as follows:1)China's household consumption will keep rising, but the growth rate will gradually reduce.To 2035,China's household consumption will be 113.6trillion yuan.The nominal growth rate will show a downward trend and then rise.2)The consumption structure of China's household consumption will be optimized gradually.On the one hand,the Engel coefficient will fall,which is expected to be 27.6%by 2020.On the other hand,the proportion of services such as transport communication,education and cultural entertainment and medical care will be expected to reach 42.7%by 2020.It is suggested that the disposable income of residents be increased,the consumption market for aged people should be expanded, and the service consumption industry should be supported.
作者
郑杉
刘秀丽
ZHENG Shan;LIU Xiuli(Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049;Center for Forecasting Science,Chinese Academy of Sciences,Beijing 100190)
出处
《系统科学与数学》
CSCD
北大核心
2018年第10期1149-1159,共11页
Journal of Systems Science and Mathematical Sciences
基金
国家自然科学基金项目(71874184,71642006)
中国科学院2018重点部署项目“新时期国民营养与粮食安全研究”中“居民膳食结构对国民营养与健康的影响分析研究”子课题资助
关键词
居民消费结构
人口年龄结构
预测
Consumption structure
population age structure
forecast
