Summary:
With China's monetary policy regime shifting gradually from a quantitative-based framework to a price-based one, short-term interest rates in the inter-bank market play an increasingly critical role in monetary policy transmission. As the most sensitive measure of the inter-bank market liquidity,short-term interest rate in the inter-bank market not only reflects the monetary policy orientation of the central bank, but also measures the inter-bank financing cost of financial institutions. The transmission of short-term interest rate along the treasury yield curve is an important part of the entire interest rate transmission mechanism in the price-based monetary policy framework. At the same time, the volatility of short-term interest rates in China's inter-bank market is relatively high compared with that of most developed and developing countries. The high volatility of short-term interest rates has had an adverse impact on the operation of financial institutions and the transmission of monetary policy. In recent years, the People's Bank of China (PBoC) has focused on optimizing the liquidity provision mechanism, and gradually improved the interest rate corridor mechanism through the introduction of standing lending facilities and other arrangements, and decreased the volatility of short-term interest rates. Naturally, the question is, how does short-term interest rate volatility in the inter-bank market affect the transmission efficiency of monetary policy shocks along the yield curve and how are financial market participants involved in this process？ This is exactly what this article is concentrates on. Traditional empirical research on the transmission of monetary policy has the following difficulties. First, the use of interest rates or money growth rate as proxy variables for monetary policy has a strong endogenous problem. Second, the conventional single-equation estimation method can only explore the current impact of policy shocks, but cannot capture the complex dynamic effects. Third, China's current quantitative and price-based monetary policy tools are being used at the same time, and it is difficult for traditional methods to uniformly measure the amplitude of various different policy instruments. This paper uses high-frequency identification and instrumental variable local projection methods (LP-IV) to explore the impact of short-term interest rate volatility on the transmission efficiency of monetary policy. Based on the data of interest rate swap transactions, this paper first uses the high-frequency identification method to identify unexpected monetary policy changes, which avoids the endogeneity problems that may be caused by traditional identification methods. On this basis, this paper uses the LP_IV to estimate the dynamic transmission efficiency of short-term interest rate changes caused by monetary policy shocks to the yield of treasury bonds of various maturities, as well as the impact of short-end interest rate fluctuations on the transmission efficiency. The results show that: first, monetary policy shocks have a significant and lasting impact on the transmission of short-term interest rates to treasury bond yields; Second, the fluctuation of short-term interest rates will weaken the transmission efficiency of monetary policy. Third, there is asymmetry in the efficiency weakening caused by short-term interest rate fluctuations, which has a strong weakening effect on loose monetary policy, but a weak effect on tight monetary policy, and there is maturity heterogeneity. Although the existing studies have paid attention to the phenomenon of excessive fluctuations in short-term interest rates in China's inter-bank market, there have been no in-depth empirical studies on how excessive fluctuations affect the transmission efficiency of monetary policy shocks. At the same time, it does not consider whether there is heterogeneity in the impact of excessive volatility on policy transmission efficiency under different monetary policy stances (easing or tightening). The research in this paper fills this gap and further enriches the research on the transmission of monetary policy shocks to the financial market. The conclusions of this paper provide support for the central bank to dredge the constraints faced by the price transmission of monetary policy and further cultivate the key role of short-term interest rates in monetary policy. The environment of moderate fluctuations in short-term interest rates is conducive to improving the transmission efficiency of monetary policy under the new framework and stabilizing market participants' expectations for short-term interest rates.
范志勇, 安戈洋, 章永辉. 银行间市场短端利率波动与货币政策传导效率——基于利率互换市场高频识别与局部投影方法[J]. 金融研究, 2024, 531(9): 1-19.
FAN Zhiyong, AN Geyang, ZHANG Yonghui. Short-term Interest Rate Fluctuations and the Interest Rate Transmission Efficiency ——Based on High Frequency Identification and Local Projection. Journal of Financial Research, 2024, 531(9): 1-19.
Bauer, M. and E. T. Swanson,2022,“A Reassessment of Monetary policy Surprises and High-frequency Identification”, NBER Macroeconomics Annual, 37(1),pp.87～155.
[18]
Bauer, M. and E. T. Swanson,2023,“An Alternative Explanation for the ‘Fed Information Effect”,American Economic Review, 113 (3),pp.664～700.
[19]
Bauer, M., B. S. Bernanke and E. Milstein,2023,“Risk Appetite and the Risk-Taking Channel of Monetary Policy”,Journal of Economic Perspectives, 37 (1),pp. 77～100.
[20]
Bernanke, B. S. and K. N. Kuttner,2005,“What Explains the Stock Market's Reaction to Federal Reserve Policy？”, Journal of Finance,60 (3),pp.1221～1257.
[21]
Cheng,X. and Y. Wang,2022,“Shadow Banking and the Bank Lending Channel of Monetary Policy in China”,Journal of International Money and Finance,128(11),pp.1~23.
[22]
Das, S. and W. Song,2023,“Monetary Policy Transmission and Policy Coordination in China”,China Economic Review, 82(12),pp.1～18.
[23]
Döttling, R. and L. Ratnovski,2023,“Monetary Policy and Intangible Investment”,Journal of Monetary Economics,134(3),pp.53～72.
[24]
Freixas, X. and J. C. Rochet,2008,Microeconomics of Banking.Cambridge,MA:The MIT Press.
[25]
Gertler, M., P. Karadi,2015,“Monetary Policy Surprises, Credit Costs, and Economic Activity”,American Economic Journal: Macroeconomics, 7(1),pp.44～76.
[26]
Hanson, S. and J. C. Stein,2015,“Monetary Policy and Long-term Real rates”,Journal of Financial Economics, 115(3),pp.429～448.
[27]
Jordà, Ò.,2005, “Estimation and Inference of Impulse Responses by Local Projections”,American Economic Review, 95(1),pp.161～182.
[28]
Jordà, Ò, M. Schularick and A. M. Taylor,2015,“Betting the House”,Journal of International Economics, 96(Supplement 1) ,pp.S1～S18.
[29]
Lu, D., H. Tang and C. Zhang ,2023, “China's Monetary Policy Surprises and Corporate Real Investment”,China Economic Review, 77(2),pp.1～22.
[30]
Ma, J. ,2017, “Interest Rate Transmission in a New Monetary Policy Framework,” in W.R Lam, M. Rodlauer and A.Schipke, Modernizing China: Investing in Soft Infrastructure, International Monetary Fund, Washington DC, pp.191～213.
[31]
Mirand, A. S, and G. Ricco ,2021, “The Transmission of Monetary Policy Shocks”, American Economic Journal: Macroeconomics, 13(3),pp.74~107.
[32]
Nakamura, E. and J. Steinsson ,2018a, “Identification in Macroeconomics.”Journal of Economic Perspectives,32(3).pp.59～86.
[33]
Nakamura, E.and J. Steinsson ,2018b,“High-frequency Identification of Monetary Non-neutrality: the Information Effect ”,The Quarterly Journal of Economics, 133(3),pp.1283～1330.
[34]
Palma, N.,2022,“The Real Effects of Monetary Expansions: Evidence From a Large-scale Historical Experiment”,The Review of Economic Studies, 89(3),pp.1593～1627
[35]
Ramey, V. A.,2016,“Macroeconomic Shocks and Their Propagation”, Handbook of Macroeconomics, 2: 71～162.
[36]
Ramey, V. A. and S. Zubairy ,2018, “Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data”,Journal of Political Economics,126(2),pp.850～901.
[37]
Stock, J. H. and M. W. Watson ,2018, “Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments” ,The Economic Journal ,128(610),pp. 917～948.
[38]
Vayanos, D. and J. L. Vila.,2021,“A Preferred-habitat Model of the Term Structure of Interest Rates ”,Econometrica, 89(1),pp.77～112.
[39]
Yang, X., L. Han, W. Li, X. Yin and L. Tian,2017, “Monetary Policy, Cash Holding and Corporate Investment:Evidence from China”, China Economic Review, 46(6),pp.110～122.
