From a Quantity to an Interest Rate‐Based Framework: Multiple Monetary Policy Instruments and Their Effects in China

• Published date: 01 October 2022
• Author: Soyoung Kim,Hongyi Chen
• Date: 01 October 2022
• DOI: http://doi.org/10.1111/jmcb.12900

DOI: 10.1111/jmcb.12900

SOYOUNG KIM

HONGYI CHEN

From a Quantity to an Interest Rate-Based

Framework: Multiple Monetary Policy Instruments

and Their Effects in China

This paper investigates the effects of various monetary policy instruments

in China with the structural vector autoregression model. Empirical results

are as follows. The effects of benchmark lending rate and short-term inter-

est rate shocks are larger than those of reserve requirement ratio shocks.

Nonpolicy shocks exert substantial effects on intermediate targets under a

quantity-based policy framework. The size and effectsof short-term interest

rate shocks in recent years are large. Short-term interest rate shocks have

strong effects on property prices. These results suggest that the new interest

rate-based policy framework is more effective than the previous quantity-

based policy framework.

JEL codes: C32, E50

Keywords: interest rate-based framework, monetary policyinstruments,

China, effects of monetary policy

1. INTRODUCTION

T     on the effects of mone-

tary policy in China is growing. However, analyzing these effects can be challenging

because of the multiple monetary policy instruments and intermediate targets used by

China. These include reserve requirement ratio; benchmark lending and deposit rates;

repo or reverse repo rates; differentiated, dynamic, and target reserve requirements;

central bank bills; repo or reverse repo amount; total loan growth;M2; and total s ocial

This research was conducted while Soyoung Kim was visiting the Hong Kong Institute for Mon-

etary Research whose hospitality is gratefully acknowledged. This work was supported by the Min-

istry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-

2018S1A5A2A01031512).

Department of Economics, Seoul National University (E-mail: soyoungkim@snu.ac.kr) Hong Kong

Institute for Monetary and Financial Research (E-mail: hchen@hkma.gov.hk)

Journal of Money, Credit and Banking, Vol. 54, No. 7 (October 2022)

© 2021 The Ohio State University.

2104 :MONEY,CREDIT AND BANKING

nancing (TSF). Recently, the People’sBank of China (PBoC) lifted the deposit rate

ceiling and introduced instruments, such as short-term liquidity operations, stand-

ing lending facility (SLF), medium-term lending facility, and pledged supplementary

lending, to build an interest rate corridor system. These changes reect the intention

of the PBoC to move from a quantity-based monetary policy framework to an inter-

est rate-based policy framework. The practice of using multiple policy instruments

is strikingly different from that in main industrial countries which, until the global

nancial crisis at least, used only one instrument, such as short-term interest rate.

Therefore, directly applying a conventional approach used in previous studies on the

effects of monetary policy in main industrial countries is difcult.

The presence of multiple policy instruments and intermediate targets calls for a

new methodology, partly because these monetary policy tools and targetsare interre-

lated. For example, quantity-based measures likely affect price-based measures and

vice versa. In addition, other factors, such as demand-side factors, also likely affect

intermediate targets.1In such cases, a simple method to analyze the effects of each

policy instrument separately and/or the effects of intermediate targets may fail. The

effects of each policy instrument should be analyzed by carefully considering the

interactions with other policy instruments and other relevant variables, including in-

termediate targets.

To address the challenge of multiple policy instruments, previous studies on Chi-

nese monetary policy have developed an indicator of monetary policythat comprises

changes in various policy instruments and/or intermediate targets. He and Pauwels

(2008) develop a measure of the Chinese monetary policy stance by indicating tight-

ening and easing actions of different instruments as a series of −1 and +1. Xiong

(2012) extends this method. Shu and Ng (2010) and Sun (2015) try to measure the

monetary policy stance of China. Chen, Chow, and Tillmann (2017) develop a Qual

vector autoregression (VAR) that includes the latent policy variableconstructed based

on policy actions in reserve requirement ratio, benchmark lending, and deposit rates.

Chen, Chow,and Tillmann (2017) identify only one type of monetary policy shock. A

few studies, such as those of He, Leung, and Chong (2013) and Fernald, Spiegel, and

Swanson (2014), analyze the effects of certain policy instruments but do not explic-

itly consider the realistic interactions among these instruments. Fan, Yu, and Zhang

(2011) and Sun, Ford, and Dickinson (2010) investigate the effects of intermediate

targets, such as M2 growth, by directly treating them as policy variables.

Unlike most studies on the overall effects of monetary policy, our research empir-

ically investigates the effects of various types of monetary policy instruments sepa-

rately by modeling their interactions and relationship with other monetary variables,

such as target variables in China. The results aim to draw implications for the PBoC’s

attempt to change the monetary policy framework to an interest rate-based framework

in recent years. First, we analyze the effects of each monetary policy instrument.

What are their effects on key macrovariables? What is the relative effectiveness of

1. For example, an increase in money demand or loan demand can increase M2 or loan if the monetary

authority accommodates it.