Research On The Correlation Mechanism Of China's Financial Cycle,Business Cycle And Monetary Policy

With the outbreak of the international financial crisis and the continuous improvement of domestic financial openness,the impact of financial shocks on the real economy has become increasingly prominent.Through the international transmission mechanism and the amplification and acceleration mechanism in the financial market,financial risks have caused the financial system to change the regular pattern of macroeconomic operation significantly,which has brought new challenges to my country's macroeconomic regulation.The financial cycle refers to financial economic activities gradually form the continuous fluctuations and cyclical changes through the transmission of the financial system under the impact of internal and external factors.It comprehensively reflects the fluctuation dynamics of various financial variables at different stages,which including money supply,credit,asset prices,exchange rates,and interest rates,et al.Therefore,studying and grasping the fluctuations characteristics of the financial cycle will not only understand the operating rules of the financial system,but also reveal the influence mechanism of the financial sector on the real economy.Through reasonable measurement of the financial cycle,real-time monitoring and analysis of the fluctuations characteristics of the financial cycle and its macroeconomic effects,it is helpful to promote the reform and development of China's financial market,improve the countercyclical adjustment effect of macroeconomic policies,and realize the stable and sustainable development of the national economy,which have important theoretical value and practical significance.This paper takes the measurement of China's financial cycle as the entry point,and the macroeconomic and monetary policy effects of the financial cycle as the main research object.By constructing econometric models that takes the financial cycle as an endogenous variable,empirically analyzing the relationship between the financial cycle,business cycle and monetary policy.The research content,main research conclusions and innovations of this paper include the following aspects:1.The measurement and dynamic analysis of China's financial Cycle and business cycle.This paper constructs a four-regime Markov switching dynamic bi-factor(MS-DBF)model,and puts the financial cycle and business cycle in a unified framework for measurement,analysis and prediction.By imposing certain constraints on the joint transition probability matrix of the financial cycle and the business cycle in the model,the smooth probability estimated by the model can effectively describe the time-varying advancement of the financial cycle to the business cycle at different stages.In addition,comparing with the traditional univariate Markov switching(MS)model or the bivariate Markov switching vector autoregression(MS-VAR)model,the model constructed in this paper can reasonably infer the stages of the financial cycle and business cycle,examine the joint transition dynamics between the financial cycle and the business cycle,and predict the future short-term trends of the financial cycle and the business cycle by the forecast probability.The main research conclusions are as follows:(1)Since 2002,China's financial cycle and business cycle have experienced five complete cycles.There is an obvious peak-to-valley staggered phenomenon between the financial cycle and the business cycle.After time difference correlation analysis,the financial cycle leads the business cycle for 6 months,and the correlation coefficient is 0.761.(2)During the sample period,the financial cycle and the business cycle showed high synergy,and the duration of the "synchronization" of the two fluctuations was greater than the duration of the"non-synchronization".After the 2008 financial crisis,both the financial cycle and the business cycle are mainly in the contraction phase.The transition probability between the financial cycle and the business cycle is asymmetry between the different states.In the expansion phase,the financial cycle's ability to predict the business cycle is greater than the contraction stage.(3)According to the out-of-sample forecast probability results,from July 2019 to December 2019,the financial cycle is expected to enter the contraction phase with a high probability,while the business cycle is still in the expansion phase with a large probability.2.Research on the volatility characteristics and interactive relationship between China's financial cycle and business cycle based on frequency domain analysis.Combining with the existing literature,this paper integrates the current main time series frequency domain analysis methods:the spectrum analysis based on Fourier transform,frequency domain Granger causality test and the wavelet analysis method,and apply the three methods to study the cyclical fluctuation mechanism and internal connection of the financial and business cycles in the frequency domain.Firsty,this paper takes the financial cycle and the business cycle as the empirical research object,and compares the ability of spectrum and wavelet analysis methods to capture time series frequency domain information in the process of single spectrum or cross spectrum estimation in detail.Secondly,the wavelet filtering method based on discrete wavelet transform and the wavelet power spectrum estimation method based on continuous wavelet transform are effectively combined together,and the fluctuation characteristics of the financial cycle and the business cycle are analyzed from the perspective of frequency band analysis.In addition,the concept "energy spectrum" of physics is introduced into the field of economics,and the proportion of energy spectrum in different frequency bands of the financial and business cycles is measured to compare and analyze the structural heterogeneity of the financial cycle and the business cycle in the frequency domain.The main research conclusions are as follows:(1)Both the spectral analysis and the wavelet analysis methods measure that the financial cycle and business cycle have a major cycle fluctuation at a period length of about 40 months and the business cycle have a sub-cycle fluctuations at a period length of 23 months.In addition,the wavelet analysis method also measured that there is a mid-cycle fluctuation at a period length of about 90 months in both the financial cycle and the business cycle.(2)The financial cycle is closely related to the cyclical fluctuations of the business cycle,which reflects the strong correlation between the financial cycle and the business cycle in the medium and long-term fluctuations,indicating two The formation mechanism of the periodic fluctuations of the sequence has a close internal connection.(3)In the entire frequency domain,the financial cycle basically precedes the business cycle,and the financial cycle can be used as a leading indicator to predict the future trend of the business cycle.This is consistent with the frequency domain Granger causality test results of financial cycles and business cycles,that is,the financial cycle is the frequency domain Granger causes of the business cycle.However,since 2015,the advancement of the financial cycle to the business cycle is gradually weakening.3.Research on the interactive influence mechanism of China's financial cycle and monetary policy.This paper uses the time-varying Granger causality test method based on Bootstrap rolling window estimation and the MS-Granger causality test method to study the non-linear interaction between China's monetary policy and the financial cycle.This paper innovatively uses the empirical results of the time-varying Granger causality test to describe the Granger causality between monetary policy and the financial cycle in a probabilistic form,and compares the results with which of the MS-Granger causality test.The main conclusions include:(1)The time interval in which the financial cycle has a significant impact on monetary policy is mainly concentrated around the rising phase or peak of the financial cycle,that is,the period of high risk in the financial system.(2)Monetary policy has a certain time lag in its response to the financial cycle.When my country's financial market is overheated,it will attract the attention of policy authorities and adopt a steady and moderate monetary policy in the future to deal with possible financial situations.Hidden risks.(3)Both methods measure that before and after the 2008 financial crisis and since the emergence of my country's excessive financial leverage in 2017,the interaction between the financial cycle and monetary policy has increased significantly.4.Research on the internal transmission mechanism of an economic system incorporating financial cycle.First of all,a look-back IS-Phillips model is established,and the relative size of the monetary policy loss function under different conditions is used to infer whether the monetary authority should regard"financial stability" as one of its"pegging targets",and on this basis above,the monetary policy response is derived.Secondly,on the basis of the traditional new Keynesian model including the IS curve,the Phillips curve and the monetary policy rules,the financial cycle is introduced into the model as an endogenous variable,thereby constructing a simultaneous equation model consisting of price-based monetary policy,financial cycle,business cycle and core inflation rate.Finally,the simultaneous equation model is extended to the VAR model system,and a four-variable TVP-VAR model is established.Through the estimation results of the isochronous impulse response function,the transmission path and control effect of monetary policy and time-varying effects of the financial cycle on other variables are analyzed.The main research conclusions are as follows:(1)Introducing the financial cycle into the monetary policy rule equation,that is,taking "financial stability" as one of the "pegging targets" when the monetary authority implements policies can effectively reduce the welfare loss of monetary policy.In addition,through sensitivity analysis,it can be known that whether monetary authorities are concerned about the "short-term effects"or "long-term effects" of monetary policy,preventing systemic financial risks and promoting the stable development of financial markets are one of the goals that cannot be ignored in monetary policy.(2)The financial cycle has a significant impact on the macro-economy and price levels,but the impact presents obvious "heterogeneity"characteristics at different points in time,that is,when the financial market is in an overheating stage,financial factors have an impact on the real economy.And the impact of the price level is obviously stronger than that of the financial market stability stage and its duration is longer.(3)Monetary policy can effectively control the financial market at different points in time and its effectiveness has been significantly enhanced during the financial boom.However,the use of "financial stability" as one of the monetary authorities' regulatory goals has significantly increased the complexity and control of the monetary policy transmission path The uncertainty of the effect makes it significantly more difficult for the monetary authorities to formulate control policies.5.Based on the cutting-edge economic growth at risk model(GaR)to analyze and predict the downside risks of China's economic growth.This paper applies it to analyze and forecast the downside risks of China's economic growth,and constructis the quantile regression model,which consists of the quantile forecast value of the real GDP growth rate as the dependent variable and the current real GDP growth rate,policy uncertainty and financial condition index as the independent variables.By introducing a partial t distribution to fit the estimated value of the quantile predicted,the model can calculate the predicted conditional probability density of the real GDP growth rate.Finally,based on the denstiy,at the 5%quantile level,this paper evaluates the downside risk of China's economic growth before and after the impact of the Covid-19 epidemic.The main research conclusions are as follows:(1)The current economic growth rate and financial cycle will have a positive impact on future economic growth,and the uncertainty of economic policies will have a negative impact on future economic growth.To influence.(2)Before the epidemic hit(the fourth quarter of 2019),assuming that there is no new crown pneumonia epidemic,the economic policy is relatively stable and favorable financial factors under the promotion,economic growth in 2020 will have a certain upward momentum;during the impact of the epidemic(the first quarter of 2020),the downside risk of future economic growth will increase,but assuming that even if there is no countercyclical macro-control policy to adjust,the epidemic will impact The negative impact of the economic growth will also gradually weaken,and economic growth has an inherent motivation for self-recovery;after the impact of the epidemic(the second quarter of 2020),future economic growth will be further restored,reflecting the steady and positive economic situation,but the economy The downside risks of growth may intensify.This is a problem that cannot be ignored.(3)According to the results of robustness analysis,this paper uses the current economic growth rate,economic policy uncertainty and financial cycle as explanatory variables to model is robust,and the estimation results of partial t distribution are also reliable.