Multiple Statistical Analysis of the Influencing Factors of the Retail Price Index

Xinying Wan
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Abstract

— With the improvement of the income level of people, our country's economic level has continued to improve. However, due to the differences in geographical and historical conditions in various regions, there is a large gap in the level of economic development in various regions of our country, and there are also significant differences in the prices of different commodities. This article uses the multiple linear regression and Principal Component Analysis (PCA) by SAS to explore the impact of the Retail Price Index (RPI) and different factors, such as the Producer Price Index (PPI) of agricultural production materials and the PPI of industrial production, the Purchasing Price Index (PRI) of industrial producers, and the Price Index of Investment in Fixed Asset.
零售价格指数影响因素的多元统计分析
——随着人民收入水平的提高,我国经济水平不断提高。但由于各地区地理和历史条件的差异,导致我国各地区经济发展水平存在较大差距,不同商品的价格也存在较大差异。本文采用SAS的多元线性回归和主成分分析(PCA),探讨零售价格指数(RPI)与农业生产资料生产者价格指数(PPI)、工业生产生产者生产者价格指数(PRI)、固定资产投资价格指数等不同因素的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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