我国几类主要物价指数的综合因子提炼分析
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摘要
我国现行编制的几类主要物价指数在宏观经济监控中起着重要的作用,它们各自反映从投资、生产到消费等不同环节价格总水平的变动,但由于现实经济的联动效应,这些指数间又呈现出很强的同升同降态势.针对此现象,运用多元统计中的因子分析方法建立模型,提炼数据中潜在的共同因子,并用主轴因子分析法求解因子载荷系数,用回归法计算因子得分.根据1990到2015年统计资料的实证结果显示,模型能从我国现行主要物价指数中提炼出意义很强的潜在因子,它能全面综合经济各领域的物价波动状况,从而为宏观物价监控提供更科学、丰富的信息.
The major price indexes in China have played an important role in the macroeconomic monitorings and controls. They reflect the changes in total price level from different economic links, such as investment, production,consumption, etc. Owing to the linkage effect of the real economy, these indexes show a strong trend of the same rise and fall. For this problem, the paper used factor analysis to establish the model, and to extract the potential common factors. Moreover, the factor load matrix is solved by the principal axis factoring,and the factor score is calculated by the regression method. According to the empirical results of the statistical datas from 1990 to 2015, the factor analysis can extract the potential factors which can comprehensively integrate the price fluctuation in all areas of the economy, so it can provide more scientific and rich information for the ma-cro-control.
The major price indexes in China have played an important role in the macroeconomic monitorings and controls. They reflect the changes in total price level from different economic links, such as investment, production,consumption, etc. Owing to the linkage effect of the real economy, these indexes show a strong trend of the same rise and fall. For this problem, the paper used factor analysis to establish the model, and to extract the potential common factors. Moreover, the factor load matrix is solved by the principal axis factoring,and the factor score is calculated by the regression method. According to the empirical results of the statistical datas from 1990 to 2015, the factor analysis can extract the potential factors which can comprehensively integrate the price fluctuation in all areas of the economy, so it can provide more scientific and rich information for the ma-cro-control.
引文
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[8]石凯.关于CPI和PPI关系的VEC模型分析[J].统计与决策,2016(3):83-86.
[9]赵建喜,杨永愉,赵丽娜.基于改进因子分析的投资组合问题的研究[J].数学的实践与认识,2015, 45(2):44-49.
[10]傅俊辉,林春培,冯建勇.居民消费价格指数的波动性分析[J].统计与决策,2009(19):43-45.
[11]何光辉.中国CPI与PPI的结构与动态作用机制研究[J].经济科学,2009(4):15-30.
[2]Ang A, Piazzesi M. No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables[J]. Journal of Monetary Economics, 2003, 50(4):745-787.
[3]高惠璇.应用多元统计分析[M].北京:北京大学出版社,2005:295-318.
[4]朱建平.应用多元统计分析[M].北京:科学出版社,2016:126-136.
[5]田茂再.多元统计分析[M].北京:中国人民大学出版社,2016:83-92.
[6]林海明.因子分析精确模型的基本思想与方法[J].统计与信息论坛,2006(5):23-25.
[7]张林泉.因子分析中特征向量和主成分的应用研究[J].数学的实践与认识,2015(2):204-210.
[8]石凯.关于CPI和PPI关系的VEC模型分析[J].统计与决策,2016(3):83-86.
[9]赵建喜,杨永愉,赵丽娜.基于改进因子分析的投资组合问题的研究[J].数学的实践与认识,2015, 45(2):44-49.
[10]傅俊辉,林春培,冯建勇.居民消费价格指数的波动性分析[J].统计与决策,2009(19):43-45.
[11]何光辉.中国CPI与PPI的结构与动态作用机制研究[J].经济科学,2009(4):15-30.
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