An Impact Of Monetary And Bank SLOS On The Financial Accelerator Effect

The research object of the financial accelerator effect is the model besed on multisector in this article.There mainly are following three contents about the financial accelerator research at home and abroad:the existence of financial effect;the asymmetry and regional differences;the research above is fruitful,but there are some problems exist.To make up for the insufficiency of the research above,this article base on the theory of economic fluctuation and financial accelerator,and set up DSGE model from the view of macro economic factor,then analysis the financial effect of credit shock、monetary and other impact which consider bank SLOS index synchronously.In this article,the DSGE model simulation test and the empirical test based on the TVAR model are used to verify the financial accelerator effect respectively.The simulation test part constructs the DSGE model which contains five parts: family, manufacturers, banks, retailers and monetary authorities. After the logarithm linearization, the 17 equations are constructed including 17 parameters. Parameters are evaluated by using the method of maximum likelihood estimation, and MATLAB is used for simulation test. This paper selects six observed variables, gross domestic product(GDP)(Yt) respectively, the price index CPI calculation(PIt) and the rate of inflation, money supply Mt(Ct), social consumer goods total(Bt), interest rates(Rt), investment in fixed assets completed Total(It), the sample interval for the third quarter of 1 quarter of 2005 to 2015, all the data were seasonally adjusted, and use the consumer price index will be nominal values are converted to real values, in order to eliminate the impact of price factors. Under the different bank SLOS of, through the use of MATLAB for simulation test, simulate the pulse results show that shocks can bring about fluctuations in containing the financial accelerator fluctuations larger and bank SLOS in different areas of, caused by the impact of the volatility significantly different.Empirical analysis using China’s Quarterly Macroeconomic Data(only the observable variables), first used the principal component analysis method to construct bank SLOS index, structure index, and also the selection of output, consumption, investment, credit, currency and inflation as a variable, with SLOS as threshold variables, using the TVAR Model for out of limits, respectively in the high and low areas on output and other variables impact. TVAR Model test results show that considering SLOS under different regimes, the credit crunch in gaoqu system to output and consumption to bring greater volatility, monetary policy on output bring greater volatility, and other variables in the low areas bring greater volatility. Proposed to further improve the construction of China’s credit market, will the boom index of central bank survey into the monetary considerations of formulation, augmented inverse application of monetary cycle, screed fluctuations in the economy, and promote the healthy and orderly development of the economy.