Shadow Banking, Monetary Policy, and Confidence Effects in China: Empirical Research Using a Structural Vector Autoregressive Model

By using monthly data regarding the scale of shadow banking, interest rates, loan balances, and the market confidence index in China from 2013 to 2017, this study constructed a structural vector autoregressive model to investigate the impacts of monetary policies and confidence in the economy with a special parallel financial intermediary. The regression results indicated that the tightening of monetary policy had compressive effects on commercial banks and shadow banking in China; however, the characteristics of Chinese shadow banking increased overall economic volatility, making the financial system more vulnerable. In addition, this study determined that the influence of confidence in the market in China, as demonstrated through responses of monetary policy authorities, had a considerable effect on shadow banking. We further determined the channel through which confidence affected the credit scale.

Ashcraft, and Boesky [3], the typical shadow banking products available in developed economies are asset-backed commercial securities, money market funds, and other innovative financial tools. Chinese banks conducting shadow banking mostly use entrusted loans and trust loans as their investment instruments. As argued by Wang et al., two features distinguish shadow banking in China from that in the West: 1) shadow banking in China is dominated by traditional commercial banks, and 2) shadow banking is implicitly endorsed by the Chinese government [4]. In addition, more than half of the business flow of shadow banking in China is essentially that of "bank loans in disguise" [5].
The aforementioned differences between shadow banking in China versus that in the West can be explained in terms of economic transition in China. Market reform in China has led to a dual-track economic system of state-owned enterprises (SOEs) and non-SOEs. A lack of credit support for non-SOEs has stimulated the demand for shadow banking. As argued by Elliott

Measurement of the Scale of China's Shadow Banking and Market Confidence
China's shadow banking system is different from that of the United States, where use of asset securitization products is most prominent of any country worldwide.
The shadow banking in China is closely related to commercial banks; it could even be said that China's shadow banks are institutions that both depend on commercial banks and help such banks to circumvent regulations.
Because of the diversity of banking business models, complexity of the accounting subjects involved, and variety of participating institutions, direct calculation of the scale of shadow banking in China is difficult. This study used the method of Sun and Jia [13], which entails starting from the basic accounting principle of "credit equals debt" and then deducting all "nonshadow assets"-such as loans, foreign exchange, corporate bonds, and other traditional assets-from the total liabilities to obtain the scale of shadow banking. This method can be represented as follows: where NSB is "nonshadow assets," SB is "shadow assets," L is loans, FE is funds outstanding for foreign exchange, EB is corporate bonds, and D is deposits.
where DR is deposits of residents, DC is deposits of nonfinancial corporations, C is currency in circulation, DG is governmental deposits, DNB is interbank deposits of nonbank financial institutions, and K is the net assets of all banking financial institutions.
DG also comprises various sources and can be expressed as follows: where DGB is deposits of the government in commercial banks, DGC is deposits of the government in the central bank, TBB is treasury bonds held by commercial banks, and TBC is treasury bonds held by the central bank.
An additional equation can be derived from Equation (1) and Equation (2) to account for the effect of off-balance-sheet wealth management products: where M2 is money and quasimoney and FM is off-balance-sheet wealth management products.
By using these equations, the scale of China's shadow banking from 2013 to 2017was obtained and is graphically represented in Figure 1. In our model, market confidence was measured using the Purchasing Managers' Index (PMI), which is an appropriate proxy for confidence level. Collins showed that the PMI reported by the National Association of Purchasing Managers in the United States can explain movements in economic activity and stock market performance [14]. Koenig used the PMI to assess the strength of the US   Giannone, Agrippino, and Modugno used the CFLP-PMI to forecast the real gross domestic product of China [16]. Gui and Li used the PMI and Producer price index to analyze how confidence affects price level [17]. The PMI data for China are plotted in Figure 2.

Data Description
The key data selected for analysis were the scale of the shadow banking system, total loans of financial institutions, Shanghai Interbank Offered Rate (1-month-weighted mean), and PMI. Descriptions of each data type are presented in Table 1 and the summary statistics of the main variables are detailed in Table 2 1 .
The data were adjusted using the X-11 seasonal adjustment method and the first order difference was obtained by calculating the logarithm. The categories of data were renamed dlnsb_sa, dlnloan_sa, dlnrate_sa, and dlnpmi_sa.
After adjustment, all data passed the augmented Dickey-Fuller test as stationery time-series data. The results of the test are displayed in Table 3.

Model Specification
The SVAR model evaluates relationships between variables on the basis of vector autoregression, and thus has high power for explaining actual economic phenomena. The number of estimated parameters of the model is reduced by addition  to analyze the interrelationships between shadow banking, commercial bank loans, interest rates, and market confidence. According to the Akaike information criterion, a lag of 2 was used in the model, represented as follows: The vector t y is ln rate_sa The general "AB-Model" form was used and the Cholesky decomposition method was employed, where matrix A is a lower triangular matrix and matrix B is a diagonal matrix; that is,

Results and Analysis
The effects of rising interest rates on the lending scale of commercial banks and scale of shadow banking are illustrated in Figure 3. The left-hand plot depicts the change with respect to commercial banks' loan issuances, whereas the right-hand plot depicts the change with respect to loans issued through shadow banking.
As indicated by the model results, the scale of shadow banking was immediately narrowed by a higher interest rate; this indicated that monetary policy tightening had a considerable effect on shadow banking and compressed it. This was because the funds employed in shadow banking mainly originated from commercial banks; thus, increasing interest rates for commercial banks led to a rising cost of funds in the shadow banking system. However, approximately six periods after the tightening of monetary policy, the trend in the scale of shadow banking had reversed, with shadow banking becoming more prevalent. This was   China's economy had had a tendency to overheat in the preceding few decades and indicated that preventing inflation and overheating was the top priority of monetary policies [18]. Consequently, China's monetary policy has been particularly sensitive to over optimism in the market.
As a result of the intervention of monetary authorities, the PMI increased, leading to higher interest rates that outweighed the credit demand induced by rising confidence. Therefore, after the PMI had increased, the scales of commercial banks and shadow banking were restricted; however, shadow banking was more sensitive to market shocks, and thus volatility was further increased.

Conclusions
On the basis of measurement of China's shadow banking system, this study estimated the effects of monetary policy and a confidence shock on the commercial and shadow lending sectors. We discovered the following key findings.
1) China's shadow banking has had strong links to commercial banks; however, compared with commercial banks, shadow banks were more strongly affected by monetary policy. When policies are tightened, the scale of shadow banking tends to decrease, whereas commercial banks have a substitution effect on shadow banking. This phenomenon led to major uncontrollability in the market that exacerbated the vulnerability of the financial system.
2) The effect of market confidence on the economy was achieved through the transmission of monetary policy. When market sentiment was favorable, monetary authorities tended to stop easing policies. This led to a widespread decrease in the scale of shadow banking that prevented economic overheating but exacerbated market volatility because of a certain degree of overreaction of the shadow banking system to monetary policy. This phenomenon occurred because of China's policy logic and the state of the Chinese economy.
The emergence of shadow banking has altered the traditional economic and financial structures, resulting in ineffective application of traditional theories and policies. Therefore, economic analysis and policy formulation are necessary.
The policy implications are that strengthening oversight to move the shadow banking system to within the ambit of regulation is a worthwhile objective, and

Conflicts of Interest
The author declares no conflicts of interest regarding the publication of this paper.