How fast can China grow? The Middle Kingdom's prospects to 2030

• Author: Mark Kruger,Jeannine Bailliu,Wheaton Welbourn,Argyn Toktamyssov
• DOI: http://doi.org/10.1111/1468-0106.12240
• Date: 01 May 2019
• Published date: 01 May 2019

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ORIGINAL MANUSCRIPT

How fast can China grow? The Middle

Kingdom's prospects to 2030

Jeannine Bailliu | Mark Kruger | Argyn Toktamyssov |

Wheaton Welbourn

Bank of Canada, Ottawa, Canada

Correspondence

Jeannine Bailliu, Bank of Canada, 234

Wellington Street, Ottawa, ON K1A 0H9,

Canada.

Email: jbailliu@bankofcanada.ca

Abstract

Given its size and importance for global commodity

markets, the question of how fast China can grow over

the medium term is an important one. Using a Cobb–

Douglas production function, we decompose the growth

of trend GDP into those of the capital stock, labour,

human capital and total factor productivity (TFP) and

then forecast trend output growth out to 2030 using a

bottom‐up approach based on forecasts that we build

for each one of these factors. Our paper distinguishes

itself from existing work in that we construct a forecast

of Chinese TFP growth based on the aggregation of fore-

casts of its key determinants. In addition, our analysis is

based on a carefully constructed estimate of the Chinese

productive capital stock and a measure of human capital

(based on Chinese wage survey data) that better reflects

the returns to education in China. Our results suggest

that Chinese GDP growth will slow from around 7% cur-

rently to approximately 5% by 2030, consistent with a

gradual rebalancing of the Chinese economy character-

ized by a decline in the investment rate. Moreover, our

findings underscore the growing importance of TFP

growth as a driver of Chinese growth.

1|INTRODUCTION

There is considerable uncertainty regarding the pace at which the Chinese economy can grow

over the medium term. Studies such as those by the World Bank (2015) and the OECD (2014)

are fairly bullish on China's prospects. They project growth to 2030 averaging 5

–

6%. While this

Received: 29 August 2016 Revised: 23 June 2017 Accepted: 3 July 2017

DOI: 10.1111/1468-0106.12240

Pac Econ Rev. 2017;1

–

27. © 2017 John Wiley & Sons Australia, Ltdwileyonlinelibrary.com/journal/paer 1

Pac Econ Rev. 2019;24:373–399. wileyonlinelibrary.com/journal/paer © 2017 John Wiley & Sons Australia, Ltd 373

would represent a significant slowdown in growth experienced since the beginning of reforms in

the late 1970s, it is still quite robust, especially for a country as large as China.

In contrast, a number of papers have been written that warn that China faces the risk of an

abrupt slowdown in the near future. These bearish analyses fall into two broad groups: those

that draw on the growth experience of a wide variety of countries and those that emphasize

China‐specific factors.

In the first group, Eichengreen, Park, and Shin (2012) examine a sample of cases of fast‐

growing countries, whose growth slowed significantly. These slowdowns typically come about

through a sharp fall in total factor productivity (TFP) growth as a point is reached in the

growth process where it is no longer possible to boost productivity growth by shifting

additional workers from agriculture to industry and where the gains from importing foreign

technology diminish. Drawing on this analysis, Eichengreen et al. (2012) project that China's

growth will slow significantly in the 2015–2017 period. In a similar vein, Pritchett and

Summers (2014) note that developing country growth rates are strongly episodic and large

(4‐percentage point) shifts in medium‐term growth rates are common. They believe that,

based on the experience of other countries'growth rates regressing to the mean, continued

rapid growth in China is unlikely.

In the second group, there are those such as Dollar and Wei (2014) and Lee, Syed, and

Xueyan (2013) who show that China's investment‐led growth model has been wasteful and that

investment has been excessive. Guo and N'Diaye (2014) take exception to the sustainability of

the export orientation of China's growth. Their research shows that maintaining the export‐

oriented growth model would require significant gains in China's market share. However, their

reading of the experience of other Asian economies that had similar export‐oriented growth

suggests there are limits to the global market share that a country can occupy. Wang (2012)

describes the sharp demographic transition through which China will go and how the cost of

labour will rise, savings will fall and government revenue will decline.

Given the size of the Chinese economy and its importance for global commodity markets, the

question of how fast China can grow over the medium term is an important one. This paper

addresses this question by looking at the evolution of the supply side of the Chinese economy over

history and projecting how it will evolve over the next 15 years. Using a Cobb

–

Douglas production

function, we decompose the growth of trend GDP into those of the capital stock, labour, human

capital and total factor productivity (TFP) and then forecast trend output growth out to 2030 using

a bottom

‐

up approach based on forecasts that we construct for each one of these factors.

More specifically, we proceed as follows. First, we model human capital using the Barro

–

Lee

educational attainment data set and drawing on studies of returns to schooling in China. Second,

we construct several measures of the capital stock and conduct some sensitivity analysis by

examining alternative measures that include/exclude residential housing and account for/ignore

‘

overinvestment

’

. Third, we derive an estimate of TFP growth over history and show that a

decomposition into known determinants is reasonable. We can, thus, be confident that this

framework is suitable to use for forecasting Chinese trend output growth. Finally, we use this

framework to build our forecasts of trend GDP growth using a bottom

‐

up approach based on

forecasts that we construct for each one of the components of trend GDP growth (i.e. capital

stock growth, labour growth, human capital stock growth and TFP growth).

In contrast to the literature that examines China's rapid growth over history, our paper

focuses on how fast it is likely to grow going forward.

1

It distinguishes itself from existing

1

For examples of the former, see Cheremukhin, Golosov, Guriev, and Tsyvinski (2015) and references therein.

2BAILLIU ET AL.

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empirical work on forecasting Chinese growth along three main dimensions. First, we draw on

the literature on the determinants of TFP growth to construct a forecast of Chinese TFP growth

based on the aggregation of forecasts of its key factors. As China slows, TFP growth will become

an increasingly important determinant of trend GDP growth. Therefore, understanding the

drivers of its TFP growth is key to assessing how, and how fast, China will grow.

Second, our analysis uses a measure of human capital, based on Chinese wage survey data,

that better reflects the past and anticipated returns to education in China.

2

Finally, our analysis

is based on a carefully constructed estimate of the Chinese productive capital stock that excludes

housing. Housing should not be included in a measure of the capital stock when capital is

defined as an input used to produce goods and services, as it is in this context. However, in

contrast to our paper, Chinese growth studies based on a Cobb–Douglas production function

framework tend to use capital stock measures that include housing.

Our results suggest that Chinese growth will slow from around 7% currently to approxi-

mately 5% by 2030, and are consistent with a gradual rebalancing of the Chinese economy

characterized by a decline in the investment rate. The rest of this paper is organized as follows.

In Subsection 2, we review the framework that we use to estimate trend output growth and its

key drivers. We also present our estimates of each one of the components of trend output growth

over history and compare them to those of other studies. In Subsection 3, we present our

forecasts of Chinese trend output growth and its components out to 2030 and compare our

estimates to those in the literature. Subsection 4 provides some concluding remarks.

2|KEY DRIVERS OF CHINESE TREND OUTPUT GROWTH

OVER HISTORY

We derive estimates of Chinese trend output growth over history using a production function

approach that assumes that the supply side of output can be described by a simple Cobb–Douglas

production function:

Yt¼AtKα

tLtht

ðÞ

1−αðÞ

;(1)

where Yis output, Kis the capital stock, Lis labour, his human capital per worker and αis the

share of capital income in output.

By log‐linearization, Equation 1 can be expressed as follows:

ln Yt

ð Þ¼αln Kt

ð Þþ 1−αðÞln Lt

ð Þþ 1−αðÞln ht

ð Þþ ln TFPt

ðÞ:(2)

Taking the first difference of Equation 2 will yield an equation in growth rates (where the

growth rate of variable Xis denoted by b

X):

c

Yt¼αc

Ktþ1−αðÞ

b

Ltþ1−αðÞ

b

htþd

TFPt:(3)

To abstract from the business cycle, each factor input must be assessed at its trend level

(where c

X�denotes the trend growth rate of variable X):

2

While the literature on Chinese growth typically assumes declining marginal returns to education based on cross‐coun-

try data, evidence from Chinese wage survey data suggests that the returns to education in China increase with the degree

of educational attainment.

BAILLIU ET AL.3

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374 BAILLIU et al.