The Time Variability Of Mixed Phillips Curve In China

Inflation rate is an important indicator to measure a country's macroeconomic performance.The dynamic relationship between inflation and output has always been the focus of economists,and it is also the basis for the monetary authorities of various countries to regulate the economy.For the central bank,the trade-off between the inflation and output directly affects the objectives and implementation process of monetary policy,which in turn affects the operational effectiveness of the policy.The Phillips curve is an important tool for studying the relationship between unemployment and wages,unemployment and prices,and output and price.It provides a more effective method for judging the current economic situation and provides a reference for monetary authorities to formulate macroeconomic policies.At present,the domestic research on Phillips curve mainly focuses on two aspects.One is the test of the applicability of the traditional Phillips curve in China;the other is the specific expression of the Phillips curve in China,mainly make a research based on the theoretical exploration of inflation expectations,inflation inertia,and output,and put forward corresponding policy recommendations.However,these studies all assume that the economic environment is running smoothly,and the Phillips curve of the fixed coefficient model is used to study the economic situation of our country,lacking dynamic nature.The 2008 financial crisis has had a great impact on the economies of all countries.The Chinese economy has rebounded rapidly after experiencing the bottom of 2008,and the inflation rate has also risen sharply.In recent years,China's economy has entered a new normal,the economic structure has undergone profound changes,the economic environment is complex and changeable,and the structural changes have all indicated that the shape of the Phillips curve has changed and the reaction coefficient has undergone a structural transformation.Based on the pricing behavior of micro-vendors,this paper uses the state space model-Kalman filtering method to characterize the time-varying characteristics of the mixed Phillips curve,and research the relationship between inflation-output,inflation-inflation inertia,and inflation-inflation expectations.The time-varying characteristics are presented in the form of a graph.This paper selects the data from the first quarter of 2001 to the first quarter of 2018 as the research basis,and selects the inflation rate,output gap,and inflation expectation as economic variables.The quarterly CPI is used as a measure of inflation rate,and the HP filter method is used to estimate the inflation expectation.After the seasonal adjustment of the actual output,the value of the output gap is obtained by using the HP filter method to calculate the potential output.In this paper,the state space model is constructed.The Kalman filtering method is used to estimate the structural parameters in the model.The depth parameters of the model are estimated by GMM method.The results show that the model can fit the Chinese economy well,and the mixed Phillips curve in China has time-varying characteristics.At the same time,the impact of inflation inertia and inflation expectations on inflation is also time-varying.The inertia of inflation has a greater impact on inflation.This paper is divided into six parts.The main contents and structure are as follows:The first part is the introduction part of the thesis,which mainly introduces the research background,theory and practical significance of this paper.From the perspective of the time-varying characteristics of Phillips curve,it studies the literature at home and abroad.Carry out combing and elaboration.Introduce the overall research framework and method of this paper.Finally point out the innovation and deficiencies of this paper.The second part analyzes the existence of the time-varying variation of the Chinese mixed Phillips curve.Firstly,it introduces the development process of the Phillips curve,and then analyzes the possibility of the existence of the Phillips curve when it is based on the reality.The third part is based on the pricing behavior of micro-vendors,based on Calvo's(1983)staggered pricing model,the economic model of the mixed Phillips curve is derived,which lays a theoretical foundation for the empirical analysis below.The fourth part is the construction of the state space measurement model.The state space model and the Kalman filter method are briefly introduced,and the mixed Phillips curve model is expressed in the form of state space.Introduced the selection of output gaps,inflation expectations,and inflation rates,as well as specific treatment methods,and conducted a stationarity test and cointegration test on these variables.The fifth part first compares the indicators of inflation expectations.The results show that the HP filtering method is used to decompose the potential components of inflation as a measure of inflation expectations.Then the structural parameters and depth parameters of the time-varying mixed Phillips curve are estimated.The hypothesis that the mixed Phillips curve has time-varying characteristics is verified,and the coefficients of each variable are economically interpreted according to the model results.The sixth part is the conclusion part of the thesis and puts forward corresponding policy recommendations.From the conclusion,China's mixed Phillips curve has time-varying,output gap,inflation inertia and inflation expectation have a significant positive effect on inflation.And this effect has time-varying characteristics.The innovation of this paper is that firstly,the inflation expectation metrics are compared,and the data obtained by HP filtering method is selected as the metric of inflation expectation,which makes the model fit better.Secondly,it is used on the basis of micro theory.The Phillips curve is mixed to study the time-varying,and the coefficients of inflation-output,inflation-inflation inertia,and inflation-inflation expectations are analyzed.Finally,the state space model is selected to study the time-varying and characterize the time-varying.The GMM estimation method is used for the estimation of the depth parameter,but there may be a problem of the tool variable that is not considered in depth,and only the general over-identification problem is considered.