Does Financial Structure Matter for Economic Growth? New Evidence from China

• Published date: 01 December 2024
• Author: Guangdong Xu,Binwei Gui,Shudan Xu
• Date: 01 December 2024
• DOI: http://doi.org/10.1111/1467-8462.12570

The Australian Economic Review, vol. 57, no. 4, pp. 351–383 DOI: 10.1111/1467-8462.12570

Article

Does Financial Structure Matter for Economic Growth? New

Evidence from China

Guangdong Xu , Binwei Gui and Shudan Xu

Abstract

Following the methodology of Beck et al. in

2001 and Levine in 2002, three relative

indicators are constructed to measure China's

financial structure at the provincial level and

these indicators are applied to explore the

current financial structure–economic growth

nexus in the Chinese context. The ordinary

panel regression model results indicate that

different dimensions of financial structure have

different growth implications, while the panel

threshold regression model results suggest a

nonlinear relationship between financial struc-

ture and economic growth based on the stage

of economic development, the relative impor-

tance of the state sector, and the financial

structure per se.

JEL CLASSIFICATION

E44; G00; O16

1. Introduction

Is financial structure relevant to our under-

standing of economic progress? More speci-

fically, does having a bank‐based financial

system versus a market‐based system make a

difference? If so, which system is better for

achieving economic prosperity? Economists

have debated the comparative importance of

these two systems for decades (Allen and

Gale 2000; Demirgüç‐Kunt and Levine 2001;

Fohlin 2012). However, consensus has not yet

been reached at either the theoretical or

empirical level. Allen, Gu and Kowalewski

(2018, p. 56) have therefore admitted that ‘the

question of how financial structure character-

istics affect economic development is not yet

fully understood’.

A potential r eason for this disagreeme nt may

stem from the fact that most empirical studies

are cross‐country studies, and this study type

can suffer from certain econometric problems,

such as parameter heterogeneity. As Favara

(2006, p. 23) has cautioned, ‘traditional growth

regressions t hat ignore dynamics and slope

heterogeneity (such as fixed effects and GMM

estimators) may be misspecified and tend to

overestimate the importance of financial devel-

opment as a determinant of GDP growth’.

Popov (2018, p. 67) similarly warns that

‘pooling together countries that differ vastly

in their degree of financial and economic

development makes parameter heterogeneity a

nonnegligible concern’.Moresingle‐country

studies are therefore needed, given their

*Xu, Gui and Xu: China University of Political Science

and Law ‐School of Law and Economics, No. 25, West

Tucheng Road, Haidian District, Beijing 100088, China.

Corresponding author: Guangdong Xu, email

<guangdongx@cupl.edu.cn>.

© 2024 The University of Melbourne, Melbourne Institute: Applied Economic & Social Research, Faculty of Business

and Economics.

Published by John Wiley & Sons Australia, Ltd

potential to yield less biased estimates through

the avoidance of parameter heterogeneity.

This study follows the single‐country

approach and explores the relationship be-

tween financial structure and economic

growth in China, which is now the second

largest economy in the world and has the

largest banking system in the world. China is

a valuable topic not only because of its

economic and financial magnitude but also

because of the apparent contradiction between

its actual growth experience and the conclu-

sion of the finance–growth nexus literature,

which has perplexed researchers for decades

(Allen, Qian and Qian 2005; He and

Wei 2022). A financial structure approach

may help to solve this puzzle by considering

the complex interactions between the banking

sector, the stock markets and the economy,

which have been overlooked in the current

(China‐centered) finance–growth nexus litera-

ture, which is typically focused on the size or

depth of the financial sector.

More specifically, we follow the metho-

dology of Beck et al. (2001) and Levine

(2002) and construct three relative indicators

to measure China's financial structure at the

provincial level. We then use both an ordinary

panel regression model and a panel threshold

regression model to explore the relationship

between financial structure and economic

growth. The ordinary panel regression results

indicate that the different dimensions of

financial structure have different growth

implications, while the panel threshold regres-

sion results suggest that there is a nonlinear

relationship between financial structure and

economic growth at China's provincial level,

regardless of which threshold variable is used.

This study is related to several streams of

literature. The first stream follows the tradition

of Beck et al. (2001) and Levine (2002) and

relies on certain relative indicators of financial

structure to examine the relationship between

financial structure and economic growth at the

cross‐country level (see Section 2.1 for details).

We contribute to this literature through the

provision of a single‐country case and, perhaps

more importantly, by straightforwardly addres-

sing the potential nonlinearity via a panel

threshold regression model. The second literature

stream takes nonlinearity more seriously and

confirms the existence of a nonlinear relationship

between economic growth and (i) banking

development (Deidda and Fattouh 2002;

Rioja and Valev 2004; Arcand, Berkes and

Panizza 2015), between that and (ii) stock

market development (Cave, Chaudhuri and

Kumbhakar 2020; Afonso and Reimers 2022),

and between that and (iii) both banking devel-

opment and stock market development (Shen

and Lee 2006; Shen et al. 2011; Swamy and

Dharani 2019). This line of literature, however,

does not use the relative indicators proposed by

Beck et al. (2001) and Levine (2002) and

therefore, it could be argued, deviates from the

original focus of the financial structure literature.

Finally, the third stream of literature, which

focuses on China's financial structure (Rousseau

and Xiao 2007; Hasan, Wachtel and Zhou 2009;

Fang and Jiang 2014), neither employs relative

indicators nor takes potential nonlinearity into

consideration. We address these two flaws

simultaneously in this study.

The remainder of the paper is organised as

follows: Section 2 offers a brief literature review.

Section 3 advances a discussion on the metho-

dology and data used to quantify the impacts of

financial structure on China's economic growth.

Section 4 presents the empirical results. Finally,

we conclude in Section 5.

2. Literature Review

2.1 Cross‐Country Studies

There are two strands of empirical literature

that explore the relationship between financial

structure and economic growth (Xu 2022).

The first group strand follows the tradition of

Beck et al. (2001) and Levine (2002) by using

certain indicators to measure the comparative

weight of banks and stock markets in a

financial system and then exploring whether

and to what extent this comparative weight

matters for economic growth. The second,

without referring to these relative indicators,

aims to directly estimate the contributions of

one financial sector to economic growth

versus those of the other. We follow the

352 The Australian Economic Review December 2024

© 2024 The University of Melbourne, Melbourne Institute: Applied Economic & Social Research, Faculty of Business

and Economics.

approach of Beck et al. (2001) and Levine

(2002) and therefore only review the first

strand of literature in this section. Interested

readers can refer to Xu (2022) for detailed

discussions on the second strand of literature.

Financial structure is generally defined by

the relative weight (in terms of size, activities

and efficiency) of financial markets (particu-

larly stock markets) versus financial intermedi-

aries (particularly banks) in a country's financial

system (Beck et al. 2001; Levine 2002). A

collection of four indicators

1

that can be used to

proxy for financial structure has been developed

by Beck et al. (2001) and Levine (2002). The

first indicator, namely, structure‐activity, is a

measure of the activity of stock markets relative

to that of banks and equals the logarithm of the

total value traded ratio (the value of domestic

equities traded on domestic exchanges divided

by Gross Domestic Product [GDP]) divided by

the bank credit ratio (the value of deposit

money bank credits to the private sector as a

share of GDP). The second indicator, namely,

structure‐size, is a measure of the size of stock

markets relative to that of banks and equals the

logarithm of the market capitalisation ratio (the

value of domestic equities listed on domestic

exchanges divided by GDP) divided by the

bank credit ratio. The third indicator, namely,

structure‐efficiency, is a measure of the effi-

ciency of stock markets relative to that of banks

and is equal to the logarithm of the total value

traded ratio (or turnover ratio, which equals the

value of stock transactions relative to market

capitalisation) times the overhead costs (or

interest rate margins) of the banking system

relative to banking system assets. Finally, these

authors developed a conglomerate indicator,

namely, structure‐aggregate, which is the first

principal component of the aforementioned

three indicators. These indicators (Levine

indicators hereafter) can therefore be relied

upon to measure the relative activity, size,

efficiency and aggregate development of stock

markets versus those of banks in different

countries, where larger values indicate a more

market‐based financial system.

Beck et al. (2001) and Levine (2002) found

that for 48 countries over the 1980–1995

period, when their financial structure

indicators and aggregate financial develop-

ment indicators (bank activity times stock

market activity, bank size times stock market

size, bank efficiency times stock market

efficiency, and the first principal component

of activity, size, and efficiency) are jointly

included in the regression equation, the

financial development indicators are posi-

tively and significantly related to economic

growth, whereas the financial structure in-

dicators never significantly enter the growth

regression.

The irrelevance argument, however, has

been challenged by subsequent studies. Pinno

and Serletis (2007) found that once parameter

heterogeneity is allowed, financial structure

becomes relevant; that is, economic growth is

promoted by market‐based financial systems

in developed countries (but is supported by

bank‐based financial systems in developing

countries). Luintel et al. (2008) and Arestis,

Luintel and Luintel (2010) similarly argued

that the resulting estimates may be biased

when cross‐country parameter heterogeneity

is ignored. They apply time‐series and dy-

namic heterogeneous panel methods to over-

come the problems of cross‐country hetero-

geneity and unbalanced cross‐country growth

paths and find that financial structure deter-

mines output levels (not growth rates) in the

majority of their sample countries.

The conclusion of Pinno and Serletis (2007)

implies that the financial structure–economic

growth nexus is dependent on an economy's

income level, which is a finding that is

supported by other studies. For example,

Luintel et al. (2016) reported that the relation-

ship between financial structure and output

level changes with the stage of economic

development. In addition to the development

stage, the institutional environment has also

been shown to be relevant. Ergungor (2008)

reported that whether and to what extent

financial structure influences economic growth

depends on the features of the judicial system;

countries that have inflexible judicial systems

grow faster under bank‐oriented financial

systems. Yeh, Huang and Lin (2013) found

that the interactions between financial structure

indicators and income level, as well as those

353Financial Structure on China's Growth

© 2024 The University of Melbourne, Melbourne Institute: Applied Economic & Social Research, Faculty of Business

and Economics.