Development of Internet finance and bank lending channel transmission of monetary policy

ZHAN Minghua1 ZHANG Chengrui2 SHEN Juan3

(1.School of Finance, Guangdong University of Foreign Studies 510016)
(2.Shenzhen Branch, Bank of China 518004)
(3.School of Economics and Management, Zhejiang Sci-Tech University 310018)

【Abstract】Financial structure is the medium of monetary policy transmission, so monetary policy transmission changes with variations in financial structure. Recently, Internet finance has grown rapidly in China. The scale and growth speed of Internet finance in China is the largest and fastest in the world. According to iResearch (2017) , there are 500 million users of Chinese Internet banking and 200 million users of the lending network. Undoubtedly, Internet finance is a large shock to China’s financial structure that will significantly influence monetary policy transmission. This paper asked how Internet finance influences the bank lending channel of China’s monetary policy transmission. There are two reasons to care about this question. First, unlike in developed countries, China’s financial sector is still in the process of full liberalization. Until 2016, bank loans accounted for 69.86% of total social financing, so the bank lending channel plays an important role in China’s monetary policy transmission. Second, the relationship between Internet finance and the bank lending channel is ambiguous. Internet finance may reduce financial frictions, weakening the transmission effects. However, Internet finance would not affect bank credit transmission if there were no substitution between Internet finance assets and bank credit. Therefore, further research into the relationship between Internet finance and the bank lending channel is needed. In this paper, we built a general equilibrium model that includes representative economic agents and put forward four hypotheses about how Internet finance can influence the bank lending channel. We then empirically tested these four hypotheses. The main empirical technology of this paper is the generalized method of moments /dynamic panel data (GMM/DPD). This method allows us to resolve the problem of endogeneity and improves the validity of the estimates. Our data include variables on bank loans, monetary policy, Internet finance, financial frictions, shadow banking and bank size. Most of the macro and micro variables are available from Wind. The data on Internet finance mainly come from open network resources like iResearch and ERI. Missing values are completed with the moving average method. Our analysis leads to the following conclusions. First, the empirical results prove that Internet finance weakens the bank lending channel of monetary policy transmission by reducing frictions in the financial market. Second, through the optimal finance decision strategies of households, enterprises and commercial banks, Internet finance influences the monetary policy lending channel. There are four effects in this process: a bank debt structure effect, a liquidity effect in securities markets, an effect resulting from the mismatch of financial resources and a corporate finance structure optimization effect. Third, the empirical results support there being significant effects of bank debt structure on the bank lending channel. Initial findings of no significance are due to the limited scale of securities markets in China and the effect resulting from the mismatch of financial resources offsetting the financing structure optimization effect. The policy implications of this research are that the implementation of monetary policy should be sensitive to the structure of financial markets and that more attention should be paid to the “catfish effects” to traditional financial institutions caused by Internet finance.

【Keywords】 Internet finance; monetary policy; bank lending channel; catfish effect;

【DOI】

【Funds】 The National Social Science Fund of China (16AZD015)

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(Translated by LIANG Xue)

    Footnote

    [1]. ① As f1, f2, f3 and f4 are the complex functions of IFt, the proving process is simplified here. [^Back]

    [2]. ① Robustness tests such as the dynamic panel GMM are performed to some extent in each equation. Due to the limits of the paper, they are not listed here. [^Back]

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This Article

ISSN:0577-9154

CN: 11-1081/F

Vol 53, No. 04, Pages 63-76

April 2018

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Article Outline

Abstract

  • 1 Literature review and this paper’s contribution
  • 2 Framework of theoretical analysis
  • 3 Overall effect of Internet finance on bank lending channel
  • 4 Empirical evidence for the micro-mechanism of the influence of Internet finance on the bank lending channel
  • 5 Conclusions and policy implications
  • Footnote

    References