There is a contradiction between the unified monetary policy and the unbalanced regional economic development, and the existence of this contradiction will definitely affect the implementation effect of monetary policy. Based on the specific situation of Hainan's economic and financial operation, this paper analyzes the role of monetary policy adjustment in Hainan's economic development over the years, and analyzes the difference between Hainan's monetary policy implementation effect and the national level, and puts forward that monetary policy should pay attention to regional differences in formulation and implementation, which is more objective, comprehensive and effective.
Keywords: differences in the implementation effect of monetary policy
First, the theoretical analysis of the influence of regional differences on the implementation effect of monetary policy.
Unbalanced regional economic development in China is a problem faced by macro-control policies, and fiscal policies show concern for regional differences through national debt and transfer payments. Monetary policy is also an important macro-control policy, but at present, China's monetary policy is mainly based on total adjustment in the process of formulation and implementation, taking a national chess game. The main advantage of this is that the state can regulate and control the total social supply and demand from the total amount, promote the basic balance between the two, and ensure the realization of macroeconomic goals. However, due to the differences in regional economic environment, financial development level and transmission channels, the contradiction between the unified national monetary policy and the unbalanced regional economic development will inevitably affect the final implementation effect of monetary policy. Therefore, the author believes that the formulation and implementation of China's unified monetary policy should also take into account the differences in regional economic development.
Second, the regional economic and monetary policy implementation effect difference analysis
The implementation effect of monetary policy is ultimately reflected in prices and output. In the process of analysis, we should consider the way of monetary policy transmission. At present, the transmission channels of China's monetary policy mainly include credit transmission, interest rate transmission and exchange rate transmission. The difference of regional economic development will inevitably have a certain impact on the transmission of monetary policy. Combined with the specific situation of N province, this paper analyzes the main transmission channels of monetary policy in this province, analyzes the influence of monetary policy transmission on investment, consumption, import and export, residents' income and savings, industrial structure, employment, etc., and finally considers the influence on prices and output. The purpose of this part is to study the influence of different monetary policy measures on local prices and output, including the adjustment of deposit reserve ratio, interest rate, rediscount rate and rediscount quota, refinancing, open market operation, exchange rate changes and some selective monetary policy tools. This paper focuses on the empirical analysis of the transmission effect of 1998-2004 monetary policy at the regional economic level, focusing on the frequent adjustment of policy tools 1998-2000.
(A) sample selection and analysis methods
Sample selection of monetary policy tools: Since 1998, we have mainly used monetary policy tools such as interest rate, deposit reserve ratio, refinancing, rediscount and credit policy. Considering that the monetary policy tools of credit policy cannot be quantified, we ignore the credit policy tools in the sample selection of monetary policy tools.
The sample range of deposit reserve in 2000 was 1998 1 month to1February, with a total of 36 samples. The sample range of loan interest rate is from April 1998 to February 65438+2000, with 33 samples, and the maximum lag period is 36 months.
The refinancing rate, refinancing amount, rediscount rate and rediscount amount range from 1998 10 to 2004 10, with 72 samples.
Sample selection of intermediary target: we choose the total loan as the intermediary target, and the total loan data is the corresponding loan balance of the current month and the loan balance of the future 1, 2, …, 33 months.
Final target sample selection: We choose GDP and consumer price index as the final target, and the sample selection range of GDP is 1998 to the fourth quarter of 2004, with 28 samples per quarter. The sample of the price index is the consumer price index, the sample range is 1998 to the fourth quarter of 2004, and there are 28 samples by quarter.
Analysis method: Using spss software to calculate Pearson correlation coefficient between various monetary policy tool indicators and intermediate target (loan balance in the current period or several months), and between intermediate target (loan balance) and current GDP and consumer price index. By analyzing the changing trend of correlation coefficient, the effectiveness of various monetary policy tools is evaluated. (Note: Pearson correlation coefficient is a measure of linear correlation between two variables. The symbol in front of the correlation coefficient indicates the direction of correlation, and its absolute value indicates the degree of correlation. The greater the correlation coefficient, the stronger the correlation.
Significance (two-tailed): the probability of bilateral significance test. ) Analyze the influence of one-way change of monetary policy instrument variable A (including 1, one-year loan interest rate, 2, one-year refinancing interest rate, 3, one-year rediscount interest rate, 4, statutory reserve ratio) on total loan B, and the influence of total loan B on final target vector C( GDP) and vector D (price).
(2) research hypothesis
According to the theory of monetary policy effectiveness, we put forward the following specific assumptions:
Suppose 1: the loan interest rate is negatively correlated with the total loan amount. Theoretically, reducing the loan interest rate can reduce the financing cost of enterprises, stimulate investment, stimulate consumption, and then improve the willingness of enterprises to lend. Therefore, the lower the loan interest rate, the more bank loans will be.
Hypothesis 2: The refinancing rate is negatively correlated with the total loan. The downward adjustment of the refinancing rate has greatly increased the willingness of commercial banks to apply for loans from the central bank, thus increasing the total amount of refinancing, correspondingly increasing the total amount of funds supplied by commercial banks, and further increasing the willingness of commercial banks to lend to enterprises.
Hypothesis 3: The rediscount rate is negatively correlated with the total loan amount. The reduction of rediscount rate increases the willingness of commercial banks to apply for rediscount from the central bank, so the amount of rediscount increases, which correspondingly increases the willingness of commercial banks to increase discounts to enterprises, and will further increase the total amount of loans from commercial banks to enterprises.
Hypothesis 4: The deposit reserve ratio is negatively correlated with the total loan amount. Reducing the deposit reserve ratio will increase the money multiplier, and then increase the money supply and the total social credit. Therefore, the deposit reserve ratio is negatively correlated with the total amount of loans.
Hypothesis 5: the total amount of loans is positively correlated with GDP. The increase of total loans directly stimulated the increase of investment and expenditure, which led to the rapid economic expansion.
Hypothesis 6: The total loan amount is positively correlated with the price index. The increase of the total loan will stimulate the increase of investment and output to a certain extent, and the income will also increase, which will lead to the rise of prices.
(3) Empirical test
Inspection shows that
1. The correlation coefficient between loan interest rate and loan amount reached -0.846 in the current month, the highest value was -0.942 in the seventeenth month, and it fell back to -0.823 in the twenty-fourth month. The results show that the loan interest rate and loan amount are significantly negative at the level of 0.0 1, which strongly supports our hypothesis 1. Linear regression is made between the loan interest rate and the loan balance in17th month, and a linear model is obtained: y=-56.097x+ 1284.465y, where y represents the loan balance in17th month and x represents the loan interest rate.
2. The correlation coefficient between the refinancing interest rate and the loan amount reached -0.839 in the current month, reached the highest in17th month: -0.930, and fell back to -0.843 in the 23rd month. The results show that the refinancing interest rate and loan amount are significantly negative at the level of 0.0 1, which strongly supports our hypothesis 2. The refinancing rate is linearly regressed with the loan balance in the17th month, and the linear model y=-28.363x+ 1063.999 is obtained, where y represents the loan balance in the17th month and x represents the refinancing rate.
3. Analyze the correlation between the refinancing amount, rediscount amount and loan balance: the sample range of refinancing amount and rediscount amount is 1998 10 to 200 1 February * *, and the loan balance is the corresponding loan balance in the current month and the loan balance in the next 32 months.
Through analysis, it is found that the maximum correlation coefficient between the refinancing amount and the loan balance in the current month and the loan balance in the following months appears in1September (0.4 17). The refinancing amount is linearly regressed with the loan balance in1September, and a linear model is obtained: y =14.136 x+917.589.
The rediscount amount and loan balance in the current month have a strong correlation with the loan balance in the following month, and the maximum correlation coefficient appears in the 30th month (0.8 15). Linear regression is made between the rediscount amount and the loan balance in the 30th month, and a linear model is obtained: y =163.826x+921.252.
If the sample range of refinancing amount and rediscount amount is from 1998 10 to 2004 10 * * 72 samples, and the loan balance is the corresponding loan balance in the current month, we can find that the correlation coefficient between refinancing amount and loan balance is -0. 124, and the rediscount amount and loan balance are. There is no significant linear correlation between them.
If the sample range of refinancing amount and rediscount amount is 42 samples from July 2000 to February 2003, and the loan balance is the corresponding loan balance in that month, the correlation coefficient between refinancing amount and loan balance is -0.090, and the correlation coefficient between rediscount amount and loan balance is -0.536. The former has no significant linear correlation, while the latter has a strong negative correlation.
If the sample range of refinancing amount and rediscount amount is 36 samples from June 1999 to May, 2002, and the loan balance is the corresponding loan balance in that month, the correlation coefficient between refinancing amount and loan balance is -0.5 13, and the correlation coefficient between rediscount amount and loan balance is 0.684.
Through the above analysis, it is found that the correlation between variables is very inconsistent for different sample intervals, so the author thinks that there is no linear correlation between the refinancing amount and rediscount amount and the loan amount during this period.
4. The correlation coefficient between the deposit reserve ratio and the loan amount in the current month reached -0.734. Among them, it reached the highest in the thirteenth month: -0.848, and fell back to -0.728 in the twenty-ninth month. The results show that the deposit reserve ratio and loan amount are significantly negative at the level of 0.0 1, which strongly supports our hypothesis 4. The deposit reserve ratio is linearly regressed with the loan balance in the13rd month, and a linear model is obtained: y=-2275.577x+ 1077.086, where y represents the loan balance in the13rd month and x represents the deposit reserve ratio.
5. Correlation analysis of GDP-loan balance: the sample range of loan balance is 65438+28 samples from the first quarter of 0998 to the fourth quarter of 2004, and the GDP sample is the corresponding quarterly GDP value. The results show that the seasonal correlation coefficient is 0.784, and there is a strong positive correlation at the significance level of 0.0 1, which strongly supports our hypothesis 5. The loan balance is linearly regressed with the current GDP, and a linear model is obtained: y=0.2 12-60.548, where y represents the current GDP and x represents the loan balance. 6. Correlation analysis of consumer price index and loan balance: the loan balance sample range is1from the first quarter of 1998 to the fourth quarter of 2004, with 28 samples. The consumer price index sample is the corresponding quarterly consumer price index. The correlation coefficient is 0.447, which shows a significant positive correlation at the significance level of 0.05, thus strongly supporting our hypothesis 6. The loan balance is linearly regressed with the current consumer price index, and a linear model is obtained: y=0.008x+9 1.960, where y represents the current consumer price index and x represents the loan balance.
Three. Main conclusions
(1) Main conclusions
1, the analysis results show that the interest rate of monetary policy instruments and the deposit reserve ratio are strongly negatively correlated with the intermediary target at the level of 0.0 1, while the refinancing rate is not correlated with the rediscount rate and the intermediary target; There is a strong positive correlation between the intermediate target and the final target GDP at the level of 0.0 1, and a significant positive correlation with the price index at the level of 0.05. Based on this, we believe that in emerging market countries, loan interest rate and deposit reserve ratio are still very important monetary policy tools because interest rates have not been marketized, and the total amount of credit plays an important role in analyzing the impact of monetary policy on regional economy, while the refinancing interest rate and rediscount interest rate have little impact on N provinces with relatively backward bill market. On the premise of considering the influence of a variable itself, the deposit reserve ratio has a strong negative correlation in the current period, and the correlation coefficient reaches the maximum in1March, and its utility begins to decrease after1June; There is a strong similarity between the loan interest rate and the deposit reserve ratio, and there is a strong negative correlation between them in the current period. The correlation coefficient reaches the maximum in1July, and the duration is 24 months respectively. The strong correlation between the intermediary target and the final policy target GDP appeared in the quarter, and the significant correlation with the price index also appeared in the quarter. Undoubtedly, China's monetary policy has achieved remarkable results in N provinces, and has had a significant impact on actual output and price changes.
3. Without considering the mutual influence, the statutory deposit reserve ratio lags behind the national level for the shortest time (13 months), and the loan interest rate (17 months) lags behind the national level for three months. On the contrary, the loan interest rate is 24 months, which is 4 months shorter than the national level, and the statutory reserve ratio is 29 months, which is the same as the national level (29 months). Why does the monetary policy tool in N province lag behind the whole country for a long time and last for a short time? The main reason is that the degree of economic monetization in N province is low and the development of capital market is relatively backward. The effect of implementing refinancing interest rate and rediscount interest rate in N provinces is not obvious. The main reason is the low degree of monetization in N provinces, especially the relatively backward bill market, which leads to the failure of the two policy tools. Therefore, considering the obvious regional differences and unbalanced development of China's economy and finance, in order to make monetary policy more in line with the actual situation of regional economy and finance, some feasible regional monetary policies should be formulated appropriately, so as to enhance the effectiveness and regional differences of monetary policy transmission.
policy advice
First, it is suggested that regional differences should be properly considered on the basis of unified national monetary policy. Implement a nationwide graded monetary policy, or a differentiated monetary policy or a regional monetary policy. Second, it is suggested to use hierarchical monetary policy to adjust the rational allocation of funds, projects and technologies nationwide. Thirdly, it is suggested that the money market and the capital market develop in harmony and enhance the interaction between the two markets, which is of great significance for improving the transmission efficiency of monetary policy and financial markets. Therefore, it is necessary to further strengthen the guidance of financial markets, promote the simultaneous development of money markets and capital markets, and give full play to the role of financial markets in the transmission of monetary policy. Secretary hodgepodge network