Summary:
Since the 2007-08 financial crisis, central banks and regulatory authorities have focused on establishing macro-prudential regulatory frameworks to ensure financial stability and prevent systematic risks. Macro-prudential policy and monetary policy tools are in general complementary, but how best to coordinate between the two remains an important research question. Although several studies have examined the problem from a capital regulation and countercyclical buffer perspective, little attention has been paid to liquidity regulation in a macro-prudential regulatory framework. In 2012, the China Banking and Insurance Regulatory Commission (CBIRC) introduced the Basel III liquidity regulatory framework and set up a five-year plan for implementation. How did commercial banks respond to these liquidity regulations during the transition period？ Did their liquidity adjustment affect the transmission effectiveness of monetary policy？ By answering these questions, we obtain a better understanding of the interactions between macro-prudential and monetary policy. From both theoretical and empirical perspectives, our paper explores the impact and mechanism of bank liquidity adjustment behavior in response to the liquidity regulation of bank lending and monetary policy transmission. Theoretically, we extend a simple bank asset and liability management model to capture banks' asset adjustment behavior. We model a bank's profit maximization problem with three constraints: (1) a balance sheet constraint, (2) a capital adequacy ratio constraint, and (3) a liquidity constraint under the Basel III liquidity regulation (i.e., net stable funding ratio (NSFR)). Our model predicts that the bank lending channel still exists even after the introduction of the NSFR requirement. Our model also shows that different asset adjustments, namely loan versus non-loan asset adjustments, have different impacts on the effectiveness of monetary policy transmission. Using a quarterly sample of 50 major commercial banks in China from 2012Q1 to 2018Q2 (which is the transition period for Basel III implementation in China), we test our theoretical predictions regarding the effectiveness of monetary policy transmission. We construct a panel data set and use a first-order system GMM to estimate the models. Our empirical results show that the effectiveness of monetary policy transmission improves when banks increase their long-term liquidity level by adjusting their loan structure. However, the adjustment of non-loan assets may negatively affect the transmission efficiency of monetary policy, which is consistent with our theoretical predictions. We also find that joint-stock commercial banks and city commercial banks with lower levels of NSFR tend to adjust non-loan assets to improve their liquidity, which may adversely affect the effectiveness of monetary policy transmission. Our results have several policy implications. First, the regulatory authorities should closely monitor the asset adjustment behavior of commercial banks under macro-prudential regulation, which may impose positive or negative effects on the effectiveness of monetary policy transmission. In addition, commercial banks should improve their liquidity to meet the NSFR requirement by adjusting their asset and liability structure (such as by optimizing loan structure and expanding stable financing channels). This paper contributes to the literature in three ways. First, it provides both a theoretical framework and empirical evidence for the interactions between bank liquidity management and monetary policy transmission. Second, it constructs a novel measure of NSFR to capture banks' liquidity management. Our identification strategy will help future researchers understand the potential impact of liquidity regulation and macro-prudential policy in general. Finally, this paper expands the literature on the credit channel of monetary policy transmission, which plays an important role in China's monetary policy practice. However, our paper is subject to some limitations in terms of data availability and data quality, especially in the construction of different liquidity measures. In general, how banks respond to different macro-prudential policies and the unintended consequences of their behavior are important questions that need further exploration. In future research in this area, we will study the mechanism through which macro-prudential policy can affect commercial banks' behavior and open the “black box” of the credit channel of monetary policy transmission.
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