Financial Factors, Openness and the Natural Interest Rate in China

• DOI: http://doi.org/10.1111/cwe.12327
• Author: Hongjin Li,Naifang Su
• Published date: 01 July 2020
• Date: 01 July 2020

©2020 Institute of World Economics and Politics, Chinese Academy of Social Sciences

China & World Economy / 76–100, Vol. 28, No. 4, 2020

76

*Hongjin Li (corresponding author), Associate Professor, Research Bureau, People’s Bank of China, China.

Email: lhongjin@pbc.gov.cn; Naifang Su, Associate Professor, Research Bureau, People’s Bank of China,

China. Email: sunf013@126.com. Thanks for anonymous reviewers’ helpful suggestions. The view of the

article only represents personal opinions, not related to the People’s Bank of China.

Financial Factors, Openness and the Natural

Interest Rate in China

Hongjin Li, Naifang Su*

Abstract

China’s nancial market has undergone signicant changes since nancial deleveraging

commenced and regulatory supervision was tightened in 2017. Intensifying China–

US trade tensions have further increased the uncertainties of external environments. In

this article, we use a Bayesian approach instead of the standard maximum likelihood

estimation in the Laubach−Williams model to estimate the natural interest rate by

considering financial factors and open conditions, and analyze the relationships

among the natural interest rate, economic activities and monetary policies. We nd that

technological and demographic factors are the main drivers of natural interest rates,

while financial factors and open conditions also play important roles. In particular,

shocks in the nancial markets and the external economic environment in recent years

are important reasons for the decline of China’s natural interest rate. Therefore, it

is necessary to strengthen research on the estimation of the natural interest rate to

ensure China’s transformation into more price-based monetary policy and high-quality

development.

Key words: Bayesian estimation, nancial factors, natural interest rate, open conditions,

state-space model

JEL codes: E43, E47, E52

I. Introduction

The natural interest rate as the equilibrium real interest rate or the neutral real interest

rate (Wicksell, 1898) is the short-term real interest rate that is consistent with potential

output and stable inflation (Kiley, 2015; Yellen, 2015). It is also a key concept in

monetary economics and is of critical importance to the implementation of monetary

policy. Since the 1980s, the monetary quantity targeting system has been gradually

©2020 Institute of World Economics and Politics, Chinese Academy of Social Sciences

Financial Factors, Openness and the Natural Interest Rate 77

abandoned, and a price-based monetary policy with an interest rate target has been

widely used. Most central banks in the world explicitly or implicitly follow Taylor’s rule

(Taylor, 1993) for interest rate decision-making, and such price-based monetary policy

decision-making with an interest rate target has since achieved great success.

The theory of the natural interest rate has developed with the evolution of

monetary theory. From the perspective of monetary policy rules, the K-percent

rule based on the monetary exogenous theory (Friedman, 1960, 1968) does not

take into account potential variables, such as the natural interest rate and the

natural unemployment rate (also known as the non-accelerating inflation rate of

unemployment, NAIRU), which are considered as goals instead of endogenous inputs

for monetary policy decision-making. On the other hand, the monetary endogenous

theory has gradually developed over time (Moore, 1988). Changes in the amount of

money (such as M2) depend on economic performance, and the monetary policy rule

is a feedback control process. Therefore, the natural interest rate and NAIRU have

become endogenous variables of monetary policy rules (Clarida, 2019; FED, 2019).

After Woodford (2003) proposed a neo-Wicksellian framework based on the New

Keynesian model, economists started to pay more attention to the estimation of natural

interest rates, especially after the global nancial crisis (GFC), in the process of anti-

crisis policy evaluation, monetary policy normalization and the interest rate liftoff. As

such the accurate estimation of natural interest rates plays an increasingly important

role in monetary decision-making.

There are many methods for estimating natural interest rates (Giammarioli and

Valla, 2004; Cuaresma and Gnan, 2007). Two popular approaches are: (i) the Laubach−

Williams (LW) method, which is a state-space model based on the New Keynesian

model (Laubach and Williams, 2003); and (ii) the dynamic stochastic general

equilibrium (DSGE) model based on the New Wicksellian theory proposed by Neiss

and Nelson (2003). Although the LW and DSGE methods offer great advantages, both

in theory and practice compared with other methods (Yellen, 2015; Li and Su, 2016a;

Wieland, 2018), their estimates are rather volatile because of model setting, parameter

choices and initial values (Pescatori and Turunen, 2016; Beyer and Wieland, 2019). In

particular, Cukierman (2016) and Taylor and Wieland (2016) argued that the omission of

certain factors may result in misspecication of the natural interest rate and thereby may

distort conclusions. For example, the LW method is based on IS and Phillips curves,

which consider the relationships among output, inflation and interest rates. Variables

such as demography, nance and openness are omitted. These problems also exist in the

DSGE method.

Extensive literature has shown that apart from technological progress, factors