Summary:
In the past few years, the People's Bank of China (PBC) has created a series of lending facility tools represented by mid-term lending facility (MLF) tools to help guide commercial banks to reduce their financing costs and promote high-quality economic development. Compared to the lending facility tools introduced by the Federal Reserve and other central banks during the crisis, the MLFs are intended as normal monetary policy tools rather than temporary rescue tools. The MLFs are designed to provide base money to commercial banks, support the proper growth of credit, and the reduction of commercial bank loan interest rates. Due to a lack of suitable causality identification strategies, it remains controversial whether lending facility tools have an effective impact on the interest rates of commercial bank loans. In particular, in China, where a variety of monetary policy tools coexist, the complex effects of different monetary policy tools affect and overlap with each other. This complexity presents difficulties for the study of the policy effects of lending facility tools. So far, empirical research on the impact of China's lending facility tools on bank loan interest rates remains rare. Based on the quasi-natural experiment created by the introduction of MLFs by the PBC, this paper uses hand-collected data from the 2009 to 2017 annual reports of 100 commercial banks to conduct an empirical study of whether China's lending facilities have an effective impact on commercial bank loan interest rates. The main conclusions of this paper are as follows. First, after the creation of the MLFs, the greater the eligible collateral held by commercial banks, the lower the interest rates of their loans. This effect increases over the studied period, showing that lending facilities can significantly affect commercial bank loan interest rates and have an increasing policy effect over time. Second, the PBC’s MLF operation expands the amount of borrowing from the PBC and the lending provided by commercial banks. This increased lending effectively reduces commercial bank loan interest rates, showing that the MLF tools work through the channel of eligible commercial bank collateral. The contributions of this paper are as follows. First, by using hand-collected eligible collateral data from commercial banks, this paper demonstrates the transmission mechanism by which MLFs affect bank loan rates. Previous empirical studies of the impacts of lending facility tools in China do not consider the eligible collateral of commercial banks or demonstrate how lending facilities exert their policy effects through such banks. Given that China's lending facilities have required that participating commercial banks provide eligible collateral, our use of hand-collected eligible collateral data provides original micro-level evidence that the MLFs work through the collateral channel. Second, by studying the policy effects of the MLF tools from the perspective of commercial bank loan interest rates, this paper verifies the effectiveness of the MLFs, thereby enriching the literature. Our results show that the PBC can effectively decrease commercial bank interest rates by using lending facilities to provide large-scale, low-cost funds to commercial banks, and that the effects are enhanced over time. The findings of this paper have implications for collateral management in China's monetary policy and its implementation of lending facilities. First, the PBC can use lending facilities to influence commercial bank loan interest rates by adjusting lending facility scales, interest rates, and eligible collateral ranges. The PBC’s lending facilities help improve the formation mechanism of the loan prime rate (LPR) formation mechanism and reduce social financing costs.Second,The MLF is a hybrid monetary policy tool that is both quantitative and price based. In practice, the PBC mainly operates the MLF by adjusting its size. In contrast, the MLF’s interest rate has undergone small changes, with an overall downward trend. As a result, the extent to which the MLF interest rate affects commercial bank loan interest rates is unclear. Therefore, to improve the effectiveness of China's lending facilities, it is important to further explore how the policy effects of the MLF’s functional mechanisms are affected by different scales of operation and lending facility interest rates.
邓伟, 宋敏, 刘敏. 借贷便利创新工具有效影响了商业银行贷款利率吗？[J]. 金融研究, 2021, 497(11): 60-78.
DENG Wei, SONG Min, LIU Min. Do Innovative Lending Facilities Affect Bank Loan Interest Rates？. Journal of Financial Research, 2021, 497(11): 60-78.
[1]邓伟、宋敏和陈雄兵,2021,《借贷便利影响了商业银行贷款期限结构吗？》,《财贸经济》第9期,第83～96页。 [2]邓伟和袁小惠,2016,《中国货币政策创新工具:产生、比较与效果分析》,《江西财经大学学报》第4期,第23～30页。 [3]郭晔和房芳,2021,《新型货币政策担保品框架的绿色效应》,《金融研究》第1期,第91～110页。 [4]郭豫媚、戴赜和彭俞超,2018,《中国货币政策利率传导效率研究:2008-2017》,《金融研究》第12期,第37～54页。 [5]侯成琪和黄彤彤,2020,《流动性、银行间市场摩擦与借贷便利类货币政策工具》,《金融研究》第9期,第78～96页。 [6]黄振和郭晔,2021,《央行担保品框架、债券信用利差与企业融资成本》,《经济研究》第1期,第105～121页。 [7]潘敏和刘姗,2018,《中央银行借贷便利货币政策工具操作与货币市场利率》,《经济学动态》第3期,第48～62页。 [8]宋敏,2018,《全球金融危机十周年反思——基于中美两国比较分析的视角》,《北京工商大学学报》(社会科学版)第3期,第11～19页。 [9]孙国峰和蔡春春,2014,《货币市场利率、流动性供求与中央银行流动性管理——对货币市场利率波动的新分析框架》,《经济研究》第12期,第33～44+59页。[10]孙国峰和段志明,2016,《中期政策利率传导机制研究——基于商业银行两部门决策模型的分析》,《经济学(季刊)》第1期,第349～370页。 [11]王永钦和吴娴,2019,《中国创新型货币政策如何发挥作用:抵押品渠道》,《经济研究》第12期,第86～101页。 [12]易纲,2021,《中国的利率体系与利率市场化改革》,《金融研究》第9期,第1～11页。 [13]余振、顾浩和吴莹,2016,《结构性货币政策工具的作用机理与实施效果——以中国央行PSL操作为例》,《世界经济研究》第3期,第36～44页。 [14]元惠萍、吴明州和刘堂勇,2018,《常备借贷便利与逆回购操作对货币市场利率的影响》,《财贸经济》第7期,第65～80页。 [15]Armantier, O., E. Ghysels, A. Sarkar and K. Shrader. 2015. “Discount Window Stigma during the 2007-2008 Financial Crisis”, Journal of Financial Economics, 118(2):317～335. [16]Armantier, O., S. Krieger and J. Mcandrews. 2008. “The Federal Reserve's Term Auction Facility”, Current Issues in Economics and Finance, 14(5):1～10. [17]Berentsen, A. and C. Monnet. 2008. “Monetary Policy in a Channel System”, Journal of Monetary Economics, 55(6): 1067～1080. [18]Christensen, J. H. E., J. A. Lopez and G. D. Rudebusch. 2014. “Do Central Bank Liquidity Facilities Affect Interbank Lending Rates？”, Journal of Business & Economic Statistics, 32(1): 136～151. [19]Fleming, M. J., W. B. Hrung and F. M. Keane. 2010. “Repo Market Effects of the Term Securities Lending Facility”, American Economic Review: Papers & Proceedings, 100(2): 591～596. [20]McAndrews, J., A. Sarkar and Z. Wang. 2017. “The Effect of the Term Auction Facility on the London Interbank Offered Rate”, Journal of Banking & Finance, 83(11): 135～152. [21]Taylor, J. B. and J. C. Williams. 2009. “A Black Swan in the Money Market”, American Economic Journal: Macroeconomics, 1(1): 58～83. [22]Wu, T. 2011. “The U.S. Money Market and the Term Auction Facility in the Financial Crisis of 2007-2009”, Review of Economics and Statistics, 93(2): 617～631.
