Seasonal Adjustment And Influence Analysis Of China's Purchasing Managers' Index

After the economic crisis in 2008,Chinese economy has experienced a long-term recovery and adjustment,and gradually returned to a stable state of growth.As a "barometer" of macroeconomics,the purchasing managers' index(PMI)has aroused the wide concern of scholars since its promulgation.With its authority,reliability and leading ability,this index has become an important guideline for the government to formulate macro-control policies,adjust the market structure and the management system of enterprises,and has been the hot area of research in recent years.PMI with its reliability and forecasting ability has become an important guideline for the government to formulate macro-control policies and to adjust the market structure and management system of enterprises.The purchasing managers' index is caculated by weighted monthly questionnaire survey data of managers,showing seasonal characteristics to a certain extent,and there is a certain correlation between the purchasing managers' index and the related economic and industry indicators because of the PMI's leading characteristic.In order to reveal the self-law of development and changing trend of the PMI index,provide policy guidance and theory evidence in macro-economic control,industrial economic monitoring,business activity risk aversion and enterprise production and management decision-making,this paper mainly studies PMI of China from three different aspects.It firstly focuses on the seasonal factors of PMI of manufacturing industry in China.The seasonal adjustment and component decomposition of PMI of manufacturing industry from2008 to 2016 are carried out by using the method of seasonal adjustment model of state space.The results show that(1)the seasonal effect of PMI in official manufacturing industry is obvious,the annual fluctuation is obvious;(2)the seasonal factors obtained by decomposition are mainly affected by circular factors;(3)the trading day effect is less significant to influence on PMI of manufacturing industry in China;(4)compared with Kalman filter,the effect of square root information filtering on component decomposition is more accurate.The second content in the paper is the relationship between two kinds of PMI and CPI in China.Through a series of methods such as unit root test,cointegration test,Granger causality test,impulse response function,and vector error correction mode model,this paper explores the relationships between Chinese manufacturing purchasing manager index,non-manufacturing purchasing manager index and consumer price index and the influence.There is a stable relationship of long-term dynamic equilibrium between the two groups of indicators.In the short term,the previous manufacturing PMI had a stronger impact on the consumer price index than the non-manufacturing one,and the manufacturing PMI impacted on the consumer price index faster than the non-manufacturing sector.Thirdly,this paper makes a short-term prediction of PMI of manufacturing industry in China.The model type suitable for fitting PMI of manufacturing industry is determined by unit root test,and the ARMA model of PMI in the manufacturing industry is established by determining the order of model by BIC criterion.The paper carries out the short-term prediction of the index data in the next 6 periods.A variety of error tests prove that the model have a good fitting effect and high accuracy.