“…The model has wide compatibility and can be used to construct functions by considering the presence of exogenous variables as lagged values of endogenous variables, depending on the statistical meaning of the data. The VAR model is able to regress multiple sets of correlated time series, and it is also widely used to analyze the effect of a single stochastic variable on the whole system and to analyze the impact of mutual shocks between time series [16]. A linear regression model has been established between the level of financial management and regional GDP in this paper, and the model's expression is:…”
This paper constructs a vector autoregressive (VAR) model between the level of financial management and regional GDP. Through the Granger causality test, the panel data at the financial management level and regional economic phenomena are studied, and the empirical distributions in the stationary situation are given by combining the stochastic simulation method. The auxiliary regression equations are established separately for constrained and unconstrained conditions, and the test statistic is constructed to determine whether there is Granger causality between the variables. Finally, from the actual data, a one standard deviation shock is applied to LATS and LGDP, and a response model with a lag of 100 periods is chosen to obtain the impulse response of the level of financial management and regional economic growth. The results show that the impact of the regional economy on the level of financial management is zero in the first period and then increases continuously, reaching a maximum response of 0.0233 in the 49th period, which indicates that there is a bidirectional promotional effect between the level of financial management and the regional economy and that the effect is not very strong but lasts for a long time.
“…The model has wide compatibility and can be used to construct functions by considering the presence of exogenous variables as lagged values of endogenous variables, depending on the statistical meaning of the data. The VAR model is able to regress multiple sets of correlated time series, and it is also widely used to analyze the effect of a single stochastic variable on the whole system and to analyze the impact of mutual shocks between time series [16]. A linear regression model has been established between the level of financial management and regional GDP in this paper, and the model's expression is:…”
This paper constructs a vector autoregressive (VAR) model between the level of financial management and regional GDP. Through the Granger causality test, the panel data at the financial management level and regional economic phenomena are studied, and the empirical distributions in the stationary situation are given by combining the stochastic simulation method. The auxiliary regression equations are established separately for constrained and unconstrained conditions, and the test statistic is constructed to determine whether there is Granger causality between the variables. Finally, from the actual data, a one standard deviation shock is applied to LATS and LGDP, and a response model with a lag of 100 periods is chosen to obtain the impulse response of the level of financial management and regional economic growth. The results show that the impact of the regional economy on the level of financial management is zero in the first period and then increases continuously, reaching a maximum response of 0.0233 in the 49th period, which indicates that there is a bidirectional promotional effect between the level of financial management and the regional economy and that the effect is not very strong but lasts for a long time.
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