5.1.1. Data Processing

We regard all the drawn data normalization and its characteristic of volatility is shown in Figure 3. To avoid the occurrence of pseudo-regression before building VAR model, we need test the stationarity of data by Augmented Dickey-Fuller (ADF) test and the results are described in Table 1.

**Figure 3.** The characteristic of volatility on related variables (Month).

**Table 1.** The results of ADF test (Month).


The numbers in brackets are *p* value. \*, \*\* and \*\*\* indicate the 10%, 5% and 1% significance level, respectively.

#### 5.1.2. Impulse Response Analysis

To figure out the relationship between variables clearly, we document four 2-dimensional VAR models, which are Agri-Loan to M2, Agri-Loan to Inter-Lend, Enter-Loan to M2 and Enter-Loan to Inter-Lend. The optimal lag order of four VAR models is determined by Akaike information criterion and its values are shown in Table 2.


Figure 4 depicts the impulse response of four VAR models (Here, because we only consider the response of financial inclusion factors to monetary policy in this paper, we give the one-way impulse response.). The four graphs of Figure 4 all show that monetary policy has a short-term positive impact on financial inclusion factors and after a period of fluctuation, they all gradually fade away. The shapes of Figure 4a,c are similar, which shows the price tools of monetary policy are not flexible to the use of fund. Compared with Figure 4b,d, the responses of financial inclusion factors are different faced to shock of the Inter-Lend, and it shows the use of money of financial inclusion are more sensitive to quantity tools of monetary policy. It can be found that either price or quantity tools of monetary policy have a positive effect on financial inclusion. The positive incentives of quantity tools of monetary policy are more capable of promoting the development of financial inclusion compared with price tools.

To sum up, monetary policies produce positive influence on financial inclusion although the effect is limited and differs between quantity and price tools. The policymakers should pay more attention to the effectiveness and sustainability when implementing tools for financial inclusion. Combining quantity tools with price tools could be a more effective and applicable solution under the

background of financial structural adjustment, which provides a sustainable circumstance for financial inclusion growth.

**Figure 4.** Impulse response graph.
