Convergence clustering in the Chinese provinces: New evidence from several macroeconomic indicators

• Author: Chi Keung Marco Lau,Zhou Lu,Giray Gozgor
• DOI: http://doi.org/10.1111/rode.12590
• Published date: 01 August 2019
• Date: 01 August 2019

Rev Dev Econ. 2019;23:1331–1346. wileyonlinelibrary.com/journal/rode

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1331

© 2019 John Wiley & Sons Ltd

DOI: 10.1111/rode.12590

REGULAR ARTICLE

Convergence clustering in the Chinese provinces:

New evidence from several macroeconomic

indicators

GirayGozgor1

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Chi Keung MarcoLau2

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ZhouLu3

1Istanbul Medeniyet University, Istanbul,

Turkey

2University of Huddersfield, Huddersfield,

United Kingdom

3Tianjin University of Commerce, Beichen

District, Tianjin, China

Correspondence

Zhou Lu, Tianjin University of Commerce,

Beichen District, Tianjin, China.

Email: luzhou59@tjcu.edu.cn

Funding information

Natural Science Foundation of Zhejiang

Province, China, Grant/Award Number:

LY18G030040

Abstract

In this paper, the convergence clustering in 31 Chinese

provinces regarding several important economic indicators

over the period 1952 to 2016 was empirically investigated.

Several provincial clusters were identified in the per capita

(real) gross domestic product (GDP), consumption–income

ratio, retail price, and consumer price inflation rates, using a

club convergence and clustering procedure. The empirical

findings are as follows. First, it was found that all series of

the original data contain a significant nonlinear component.

Second, it was observed that there are five significant clus-

ters for the per capita income in China. Third, it was found

that there are four significant clusters for the consumption–

income ratio. Fourth, it was observed that there are four sig-

nificant clusters for the retail inflation rates and two

significant clusters for the consumer inflation rates in China.

These results will enable local and central planners to im-

plement economic growth, savings and price adjustment

policies for different groups of provinces.

JEL CLASSIFICATION

R11, R12, C23

KEYWORDS

Chinese economy, convergence clustering, nonlinearity, regional

economic activity, regional inflation, spatial distributions

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GOZGOR etal.

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INTRODUCTION

Convergence clustering in 31 Chinese provinces regarding several important economic indicators over

the period 1952 to 2016 was empirically investigated in this paper. Several provincial clusters were

identified in the per capita (real) gross domestic product (GDP), the consumption–income ratio (C/Y),

retail price, and consumer price inflation rates, using the club convergence and clustering procedure

of Phillips and Sul (2007). The main advantage of the method of Phillips and Sul (2007) is that it takes

heterogeneity into account across the Chinese regions within a nonlinear time- varying framework.

Indeed, it is important to investigate the convergence clustering of the Chinese provinces with

regards to economic indicators. One of the stylized facts in the literature is that the income inequality

in the Chinese provinces has increased (divergence across provinces) since 1979 owing to the signif-

icant institutional reform in 1979 (Cheong & Wu, 2013, 2014; Ho & Li, 2010; Knight, 2014; Lau,

2010; Lyhagen & Rickne, 2014). For instance, Ho and Li (2010) investigated the stochastic properties

of output per capita across the Chinese provinces for the period 1984 to 2003 and observed significant

evidence of output divergence across the provinces. Similar evidence was obtained by Lyhagen and

Rickne (2014) for half of the Chinese cities by using the nonlinear trend functions in the vector error

correction model (VECM) over the period 1952 to 2007.

However, there are also many papers in the literature that show evidence of the convergence of

per capita income (output) across the Chinese provinces (Herrerias & Ordonez, 2012; Herrerias &

Ordonez Monfort, 2015; Herrerias, Orts, & Tortosa‐Ausina, 2011; Sakamoto & Islam, 2008). For in-

stance, Herrerias et al. (2011) obtained evidence of convergence for the per capita GDP across 28

Chinese provinces for the period 1952 to 2005. Using the method of Phillips and Sul (2007), Herrerias

and Ordonez (2012) investigated the stochastic properties of club convergence in terms of per capita

income, labor productivity and capital intensity for the period 1952 to 2008. They found a statistically

significant club convergence in the Chinese regions over the period under study. Her rerias and Ordonez

Monfort (2015) also investigated the stochastic properties of convergence across 28 Chinese provinces

for the period 1952 to 2008, using the test technique of Phillips and Sul (2007). They observed a signif-

icant degree of convergence in capital intensity, labor productivity and total factor productivity (TFP) in

the Chinese provinces. Shortly, there are two empirical results with regard to the stochastic properties of

the per capita income across Chinese provinces. First, scholars found a significant divergence across the

Chinese provinces. Second, scholars observed a nonlinear club convergence across the Chinese prov-

inces. The findings of the present study are in line with one of these two results (the latter in our case).

In addition, the empirical results of the consumption–income (C/Y) ratio can be used in macro-

econometric modeling and policy implications for the understanding of the consumption function

(therefore savings behavior) as well as global imbalances, as a result of the significant and increasing

share of the Chinese economy in the world economy. For instance, Chow (1985, 2010, 2011, 2016)

obtained evidence in favor of the permanent income hypothesis (PIH) of Friedman (1957) and Hall

(1978) in China. Using annual time- series, Chow (1985) obtained empirical evidence in favor of the

PIH for the period 1952 to 1982. Chow (2010) then updated the data for the period 1978 to 2006 and

reached the same conclusion with Chow (1985). Using the data for the period 1978 to 2009, that is,

adding the period of the Great Global Recession of 2008 to 2009 in the data set of Chow (2010), Chow

(2011) found a weak but supporting evidence for the PIH in China. Chow (2016) considered the data

set for 1952 to 2013 and again obtained evidence in favor of the PIH. Therefore, the author extended

his empirical findings of 1985, 2010, and 2011 by covering longer periods. All these findings suggest

that the consumption–income ratio is a mean- reverting process in the Chinese economy, and there-

fore, its change is predictable. Mean reversion in the consumption–income ratio means that policy

shocks temporarily affect the consumption and saving behaviors of Chinese households. However,