The Analysis Of Leading Factors And Forecast On Inflation In China

The inflation forecast is a foundation for effective implementation of the central bank’s monetary policy. Through theoretical analysis, we know that CPI is the most reliable indicator to measure the inflation and is widely used. If we predict the CPI index and the development trend of China’s economy can be known, what’s more it play a role in warning on inflation. If the central bank develop appropriate monetary policy based on inflation forecasts results, it will help to avoid the time lag of monetary policy, facilitate the proper guide and stabilize the market forecasts, and ultimately improve the effectiveness of monetary policy.This paper starts from econometrics Statistics and econometric analysis are comprehensively used. The main line of the paper is China’s CPI forecasting. It makes an in-depth look on China’s CPI forecasting, the forecasting model. It also predicted CPI forecasting analysis, empirically.Beginning from the fluctuations in China’s CPI and other economic time series, we study two kinds of forecasting models, namely the cointegration regression forecasting model and the seasonal ARIMA model. They monitor and warn the fluctuations of CPI, provide valuable reference to macroeconomic policy-making. Co-integration regression prediction model takes full advantage of leading indicators of the CPI, but also to avoid excessive loss of freedom in the multiple regression prediction model. Seasonal ARIMA model fully take into account the CPI seasonal factors, greatly improving the CPI short-term prediction accuracy.In order to establish cointegration regression forecasting mode, the Impulse Response and Variance Decomposition are used in this paper to choose the leading indicators of CPI in China. The leading time of them are also established. Then, China’s leading indicators system of CPI is built. On this basis, principal component analysis is used to fully extract the leading indicator information, and reduce the dimensions of the comprehensive leading indicators system.The main contents of this article:First, to introduce the research background and significance of this article, and review the theory, to sort out the theory of inflation; Secondly, select the relevant leading indicators of CPI, and use econometric models to take the empirical method to screen leading indicators; Thirdly, establish integrated leading indicators, combine integrated leading indicators and CPI data to make a regression prediction model to forecast the CPI; fourthly, establish ARIMA prediction model of CPI; Fifthly, compare the prediction models and forecast results of it, given the thinking and recommendations.