Research On China’s Consumer Price Index

CPI is an essential statistical indicator of macroeconomic performance of a country or a region, and also an important basis for economic analysis and decision-making of the general price level, monitoring and regulating national accounts. There are a lot of inadequacies in China’s CPI system currently, such as the survey sample is not so representative; rationality of weight determination is uncertain; CPI architecture lacks of diversity. Therefore further study of CPI is necessary.We compare China’s CPI with other countries from the establishment steps as well as the architecture, summarize recommendations of improving China’s CPI methodology. In order to explore statistical regularities of CPI, we select price indexes which are related to CPI. We use cointegration and vector error correction (VEC) model to study the relationship between them. The results show that the CPI is affected by the food price index, residence price index, retail price index and industrial producer prices index in the long term. To improve the CPI compilation, we try to improve the weight of CPI sub-index by reducing traced-back years from4years to2years, we can conclude that shorten traced-back years can better adapt to the rapidly changing structure of consumer. For the purpose of improving applicability of the CPI structure, we compile comprehensive as well as A, B, C stratified Price Indexes for urban and rural residents of different income levels to respectively reflect the overall level as well as the low, middle and high-income sectors of the consumer price level in China’s urban and rural areas. At last, we discuss the reasons for the inconsistency of the CPI and public feelings from the connotation of CPI.The innovation of this paper is to shorten the traced-back years of CPI weights as adjustment, so the weight information can be timely updated. We compile A, B, C stratified Price Indexes for urban residents and rural residents. We calculated stratified CPI monthly data of urban and rural residents of2012to reflect the different consumer price levels of residents with different consumption structures.