The Role of Structural Change in the Economic - 麻省理工学院人工智能研究专业

The Role of Structural Change in the Economic
Development of Asian Economies
∗
NEIL FOSTER–MCGREGOR AND BART VERSPAGEN

在本文中, we combine data on gross domestic product (GDP) per capita and
sectoral employment shares to undertake a decomposition of GDP per capita
growth for a sample of 43 Asian and non-Asian economies. We decompose
income changes into three components: (我) changes in labor productivity
within sectors, (二) employment shifts across sectors (structural change), 和
(三、) changes in the intensity of employment participation. We then compare the
decomposition results for the Asian economies that moved between different
income levels of interest with those from a representative typical economy and
other comparison economies. The results suggest that in most Asian economies
labor productivity growth was the dominant source of gains in GDP per capita,
with the observed gains in labor productivity often driven by changing labor
productivity within sectors rather than by shifts in employment across sectors.
This is not to diminish the role of structural change, which at lower income
levels can explain a signiﬁcant proportion of overall labor productivity growth.

关键词: labor productivity, structural change, structural decomposition
JEL codes: O14, O47

我. 介绍

Rich economies produce, consume, and invest in entirely different goods and
services than poor economies. 那些 (很少) developing economies that managed to
make the transition from low-income to high-income status did so by undergoing a
process of deep structural transformation in which the productive structure of their
economy was changed completely. One aspect of this transformation involves the
movement of capital and labor out of primary goods and into manufacturing, 和
ultimately into services as economies further mature. This process has been followed
in most advanced economies, with differences in the speed and extent of structural
change being offered as an explanation for diverging growth rates (看, 例如,
Denison 1967 and Maddison 1987). Less is known about developing economies,
though a number of recent examples of deep structural change—often related to

∗Neil Foster–McGregor
(corresponding author): Research Fellow, UNU-MERIT, Boschstraat, 马斯特里赫特,
荷兰. 电子邮件: foster@merit.unu.edu; Bart Verspagen: Director, UNU-MERIT, Boschstraat, 马斯特里赫特,
荷兰. 电子邮件: verspagen@merit.unu.edu. The authors would like to thank the participants at the Asian
Development Outlook–Asian Development Review Conference held in Seoul in November 2015, the managing
编辑, and an anonymous referee for helpful comments. The usual disclaimer applies.

Asian Development Review, 卷. 33, 不. 2, PP. 74–93

C(西德:3) 2016 Asian Development Bank
and Asian Development Bank Institute

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 75

improved economic performance—exist, most notably in Asia. The so-called Asian
Tigers (香港, 中国; the Republic of Korea; 新加坡; and Taipei,中国)
were the ﬁrst generation of postwar economies that managed to make the transition
from developing to developed status. Other Asian economies, including the People’s
Republic of China (PRC), have since embarked on this path of high gross domestic
产品 (GDP) growth and rapid structural change.

最近, a small number of papers have examined the extent and impact
of structural change in developing economies. Timmer, de Vries, and de Vries
(2014) show that the expansion of manufacturing activities led to growth-enhancing
structural change in economies in Asia, 非洲, and Latin America. (然而, 这
process stalled in Africa and Latin America during the mid-1970s and 1980s and
was followed by a movement into market services, which have lower possibilities
for growth than manufacturing.) Using structural decomposition methods similar
to those adopted in this paper, Timmer, de Vries, and de Vries (2014) ﬁnd that
while structural change in Africa and Latin America involved a reallocation toward
sectors with above-average productivity, these sectors experienced below-average
productivity growth. The resultant dynamic losses found in Africa and Latin
America do not tend to be found in Asia. McMillan, Rodrik, and Verduzco–Gallo
(2014) undertake a similar exercise and ﬁnd that the structural change that has
occurred in Africa and Latin America since 1990 has tended to reduce economic
生长. 尤其, McMillan, Rodrik, and Verduzco–Gallo (2014) 显示
the contribution of structural change to productivity growth in Africa and Latin
America has been negative, with very small negative effects found in high-income
经济体. 同时, positive effects were found in Asian economies. 作者
argue that much of the difference in overall labor productivity growth among the
three developing regions is due to different patterns of structural change.

Not only has deep structural change occurred in a number of Asian economies
in recent decades, but economies in Asia have also been able to transition between
different income levels relatively quickly. This has important policy implications.
As stated by McMillan, Rodrik, and Verduzco–Gallo (2014), the speed with which
structural transformation takes place is the key factor that differentiates successful
economies from unsuccessful ones. Considering data from the Maddison Project
Database on 133 economies for which data is available over the period 1950–2010,
we observe that the average duration for Asian economies to move between an
income level of $1,500 和 $5,000 是 25 年, while for economies from other
regions it took an average of 31 years.1 Results for movements between other
income levels are broadly similar, with average transition periods of 11 和 22 年,
分别, for Asian and non-Asian economies to move from an income level of
$5,000 到 $10,000; 9 和 16 年, 分别, for Asian and non-Asian economies

1The Maddison Project Database reports data on GDP per capita for a large number of economies. Data are

在 1990 美元.

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

76 ASIAN DEVELOPMENT REVIEW

to move from an income level of $10,000 到 $15,000; 和 7 和 14 年, 分别,
for Asian and non-Asian economies to move from an income level of $15,000 到 $20,000. In moving from an income level of $20,000 到 $25,000, the duration is
10 和 9 年, 分别, for Asian and non-Asian economies, though the Asia
subsample for this transition comprises only two economies (香港, China and
新加坡).

In the context of Asian economic performance, much of the literature
attempting to explain the rapid growth of income per capita in recent decades
can be split into two camps. In the one camp are those studies arguing that
fundamentals—namely inputs, and capital accumulation in particular—can explain
the rapid growth of a number of Asian economies, with little or no credit given to
productivity improvements. Examples from the literature include Young (1992) 和
Krugman (1994). As pointed out by Felipe (1997), accepting this point of view also
leads to the conclusion that growth in these rapidly growing Asian economies may
not be sustainable because input-driven growth is not sustainable in neoclassical
growth models since there are limits to input mobilization and incremental growth
in inputs is subject to diminishing returns (看, 例如, Solow 1956). In steady
状态, growth in per capita output will equal the sum of labor force and labor
productivity growth.

In the other camp are those who believe that economic performance in Asia
has been driven by total factor productivity growth through, 例如, adopting
and assimilating foreign technology (看, 例如, Romer 1993), or through
rapid structural changes such as changes in ﬁrm size and sectors of specialization
(Nelson and Pack 1999).

在本文中, we combine data on GDP per capita and sectoral employment
shares to undertake a decomposition of growth in GDP per capita for a sample of 43
Asian and non-Asian economies. Considering transitions between different levels
of GDP per capita, we decompose these income changes into three components:
(我) changes in labor productivity within sectors, (二) employment shifts across sectors
(structural change), 和 (三、) changes in the intensity of employment participation.
We undertake this decomposition for Asian economies that moved between income
级别, comparing the decomposition results for these economies with those from
other economies and a representative typical economy that we construct based on
all available data. The paper adds to the existing literature on the performance
of Asian economies by distinguishing between the roles of productivity and labor
participation intensity in driving overall growth in per capita output. By considering
the aggregate level effects of reallocation, this paper also adds to the existing
literature on the misallocation of resources and is therefore a complement to recent
studies that consider within-sector misallocation using ﬁrm-level data (看, 为了
例子, Pavcnik 2002 and Hsieh and Klenow 2009).

The results suggest that in most Asian economies labor productivity growth
has been the dominant source of gains in GDP per capita, especially for movements

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 77

between higher income levels. The observed gains in labor productivity were
usually driven by changing labor productivity within sectors rather than by shifts in
employment across sectors (再次, especially for movements between higher income
级别). This is not to diminish the role of structural change, which at lower income
levels can explain a signiﬁcant proportion of overall labor productivity growth.

The remainder of the paper is set out as follows. Section II describes the
methodology used to undertake our decomposition analysis and constructs the
decomposition for our representative typical economy. Section III describes the data
used in our analysis. Section IV presents our results. Section V concludes.

二. 方法

GDP per capita (Y/N ) can be expressed as the product of labor productivity

(Y/L) and employment participation (L/N ):

是
氮

= Y
L

L
氮

where Y is GDP (value added), L represents employment, and N represents
人口. The growth rate of GDP per capita can then be expressed as the sum of
the growth rates of labor productivity and employment participation growth:

(西德:2)

˙Y − ˙N

(西德:2)

(西德:3)

˙Y − ˙L

(西德:3)

(西德:2)

˙L − ˙N

(西德:3)

(1)

where a dot over a variable indicates a growth rate. Using standard structural
decompositions (看,
例如, Fabricant 1942; McMillan, Rodrik, 和
Verduzco–Gallo 2014; and Timmer, de Vries, and de Vries 2014), we can decompose
labor productivity growth into a within effect and two structural change terms:
(西德:3)
(西德:2)
s1
我

− y0
我

− s0
我

(西德:4)

y1
我

s1
我

(西德:3) (西德:2)

(西德:3)

(西德:2)

(西德:3)

− y0
我
y0

s0
我

我

− s0
我
y0

y0
我

我

˙Y − ˙L ≡ ˙y =

(2)

where the subscript i denotes a sector, y is labor productivity, ˙y denotes labor
productivity growth, and si denotes the share of sector i in aggregate employment.
The superscripts refer to time periods.

The effects on the right-hand side are (我) the within effect (the contribution
of labor productivity growth rates within each sector), (二) the static shift effect
(the productivity effect from reallocating labor that results from differences in
productivity levels between sectors at the start of the period), 和 (三、) the dynamic
shift effect (the productivity effect of reallocating labor that results from differences
in productivity growth rates between sectors over the period). The sum of (二) 和
(三、) equals the total effect of employment reallocation. The within effect will be

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

78 ASIAN DEVELOPMENT REVIEW

积极的 (negative) when the weighted growth in labor productivity in a sector is
积极的 (negative), while the static effect will be positive (negative) when labor
moves from less (更多的) to more (较少的) productive sectors. The dynamic effect
captures the joint effect of changes in employment shares and sectoral productivity;
it will be positive (negative) if workers are moving to sectors that are experiencing
积极的 (negative) productivity growth. The static effect captures whether workers
move to sectors with above-average productivity, while the dynamic effect captures
whether productivity growth is higher in sectors that expand in terms of employment
shares (Timmer, de Vries, and de Vries 2014).

Combining equations (1) 和 (2), as well as combining the two employment
reallocation terms, results in a decomposition of GDP per capita growth containing
three terms:

(西德:2)

˙Y − ˙N

(西德:4)

(西德:3)

我

(西德:2)

(西德:3)

y1
我

− y0
我
y0

s0
我

(西德:4)

我

(西德:2)

(西德:3)

s1
我

− s0
我
y0

(西德:2)

y1
我

(西德:3)

˙L − ˙N

(3)

The three terms represent (我) the within effect from productivity growth within
部门, (二) the shift or reallocation effect from shifting labor across sectors, 和
(三、) an effect due to the growth of employment participation.

This is the starting point for our empirical analysis. In contrast to the
approaches adopted in the studies of Timmer, de Vries, and de Vries (2014)
and McMillan, Rodrik, and Verduzco–Gallo (2014), we do not consider the
decomposition of growth rates of GDP per capita over time. 反而, we undertake
this decomposition for a movement between different levels of GDP per capita,
which proxy for various stages of development. This approach allows us to address
the issue of whether productivity growth or employment participation dominate the
movement between different levels of development, as well as the role of structural
改变. 例如, we consider the decomposition for economies that move from
an income level of $1,500 to an income level of $5,000—a growth rate in GDP
per capita of 233.3% over an unspeciﬁed time period—ﬁnding the years in which
economies reached these income levels; taking the values of y and s in these years,
and the growth rate of employment participation between these years; and calculating
the decomposition. We do this for all economies in our data set that managed to
traverse the different income levels—$1,500 to $5,000, $5,000 到 $10,000, $10,000 到 $15,000, $15,000 到 $20,000, 和 $20,000 to $25,000—within the period of
分析, 1950–2010.2 We also report on the speed of transition, considering whether
a certain pattern of the decomposition is associated with a quicker transition.

While this approach allows us to undertake the decomposition for particular
economies—in our case, Asian economies—and allows for a comparison across
经济体, we also consider what the decomposition would look like for a

2In a small number of cases, we update the data set to 2013 using data from the Penn World Tables if it allows

us to consider an additional transition to a higher income level (Feenstra, Inklaar, and Timmer 2015).

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 79

representative typical economy as it made the transition between different income
levels.3 We then assess whether the pattern of the typical economy is replicated by
any of the Asian economies in our sample.

y si , and upon y1

To create the decompositions for the typical economy, we need information
on the employment shares, si , and the relative labor productivity, yi /y, for a
typical economy. We employ a locally weighted scatterplot smoothing (LOWESS)
regression on the employment shares, 做
y0 . LOWESS is a nonparametric
method that is used to create a smooth line through a scatter plot to identify a
relationship between two variables. The basic idea of this method is straightforward
and involves ﬁtting simple (例如, polynomial) regression models to localized subsets
of data using weighted least squares, thus allowing one to build up a function that
explains the deterministic part of the variation in the data. We conduct the LOWESS
analysis on si and yi
y si for each of our nine sectors and on the ratio of aggregate
labor productivity y1
y0 , with GDP per capita as the independent variable. This gives us
(西德:5)y1
(西德:6)做
估计 (西德:5)si ,
y0 . Taking these estimated values at particular income levels
y si , 和
and combining them with equation (3) allows us to undertake the decomposition
analysis for our typical economy, which is an economy with the estimated values of
si and yi
y si at a particular income level.4 Equation (3) is thus rewritten as

(西德:2)

˙Y − ˙N

(西德:3)

(西德:7)

(西德:4)

我

y1
我
y0

− y0
我
y0

(西德:8)

s0
我

(西德:4)

(西德:2)

我

s1
我

− s0
我

(西德:2)

(西德:3) y1
我
y0

(西德:3)

˙L − ˙N

Given the fact that we can write y1
我
y0

= y1
我
y1

y1
y0 , we can further write

(西德:2)

˙Y − ˙N

(西德:3)

(西德:7)

(西德:4)

我

y1
我
y1

y1
y0

− y0
我
y0

(西德:8)

s0
我

(西德:4)

我

(西德:2)
s1
我

− s0
我

(西德:3) y1
我
y1

y1
y0

(西德:2)

(西德:3)

˙L − ˙N

Using our LOWESS estimates, 我们有

(西德:2)

˙Y − ˙N

(西德:4)

(西德:3)

我

⎛

⎜
⎝

我

(西德:6)y1
y1 s1
我
(西德:5)
s1
我

(西德:12)
y1
y0

我

(西德:6)y0
y0 s0
我
(西德:5)
s0
我

⎞

⎟
⎠ s0
我

(西德:4)

(西德:16)
(西德:5)
s1
我

- (西德:5)
s0
我

我

(西德:17) (西德:6)y1
y1 s1
(西德:5)
s1
我

我

(西德:2)

(西德:12)
y1
y0

(西德:3)

˙L − ˙N

3While for the purpose of presentation we refer to this construct as a typical economy, the typical economy
is based on a weighted average of all economies in the data set and therefore may not represent any single economy
or its evolution of structural change and GDP per capita.

4一般来说, we will not obtain a prediction for one of our income levels (例如, $1,500 或者 $5,000). 反而,
we use the predicted values for two economies with income levels that are closest to these values (on either side of
the income level we are interested in) and take the weighted average of these to obtain a prediction for a particular
income level.

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

80 ASIAN DEVELOPMENT REVIEW

where all variables with a hat above them are obtained from the ﬁtted values of
the LOWESS models. This gives us a decomposition for the representative typical
economy in our sample.

三、. Data and Descriptive Statistics

Data on GDP per capita are taken from the Maddison Project Database, 哪个
reports data on GDP per capita in 1990 international Geary–Khamis dollars for a
large number of economies. In our analysis, we use data on all economies for which
data are recorded over the period 1950–2010, which gives us data on 133 发达
and developing economies.5

Data for sectoral employment shares are taken from the GGDC 10-sector
数据库 (Timmer, de Vries, and de Vries 2014), which reports data on an annual
basis from 1950 on value added, output deﬂators, and persons employed for
10 broad sectors. We use the data on persons employed to construct sectoral
employment shares. The database has data for 43 economies in Africa, 亚洲,
欧洲, 拉美, and North America. 这 10 sectors included in the database
是 (我) 农业, hunting, forestry, and ﬁshing (农业); (二) mining and
quarrying (矿业); (三、) manufacturing; (四号) 电, 气体, and water supply
(utilities); (v) 建造; (六) wholesale and retail trade, repair of motor vehicles
and motorcycles, personal and household goods, and hotels and restaurants
(贸易); (七) 运输, 贮存, and communications (运输); (viii) ﬁnancial
intermediation, renting, and business services (FIRBS); (ix) public administration
和防御, 教育, 健康, and social work (government services); 和
(X) personal services (个人的). In our analysis, we combine the ﬁnal two sectors
into a single sector (public sector), leaving us with nine sectors.

When combining these two data sets, it is clear that the sectoral data is the
limiting factor, meaning that the main analysis can only be conducted on the 43
economies for which we have sectoral data. 此外, our measure for labor
参与 (L/N) results from the combination of these two data sets; 那是, 这
participation effect is the difference between the growth rates of labor productivity
and GDP per capita. 然而, in some of the descriptive analysis of GDP per capita
that follows, we refer to a larger data set of 133 economies from the Maddison
Project Database. 桌子 1 reports from this larger sample the number of transitions
between different income levels for the Asian and non-Asian economy subsamples,
along with the average speed of transition between income levels for the different
subsamples. Given the much smaller number of observations available for the Asian
sample (21 相对 112 经济体), 桌子 1 indicates that there is generally a higher

5For a small number of economies, data are missing for one or two time periods. We include additional
data from the Penn World Tables for the period 2011–2013 for a small number of economies if doing so will add a
transition episode from one income level to another (Feenstra, Inklaar, and Timmer 2015).

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 81

桌子 1. Descriptive Statistics on the Frequency and Speed of Transitions
between Income Levels

$1,500– $5,000

$5,000– $10,000

$10,000– $15,000

$15,000– $20,000

$20,000– $25,000

Number of transitions

亚洲
Non-Asia

Speed of transition (年)

亚洲
Non-Asia

6
9

25.2
31.0

7
19

11.4
21.9

5
26

9.0
15.7

5
17

7.4
13.7

2
12

10.0
9.0

Notes: This table reports the number of transitions between each income level made by Asian and
non-Asian economies in the 133-economy sample, along with the average speed of transition for those
经济体, also split into an Asian and non-Asian subsample. The Asian subsample comprises 21
economies for which we have data over the period 1950–2010. It excludes Australia and New Zealand.
来源: Authors’ calculations based on the Maddison Project Database. http://www.ggdc.net/maddison
/maddison-project/home.htm

probability for Asian economies than non-Asian economies to have moved between
the different income levels during the period 1950–2010.6 Table 1 also shows that
except for the movement from $20,000 到 $25,000, Asian economies were able to
move between income levels faster than non-Asian economies by an average of
之间 5 和 11 years for each transition.

IV. 结果

We begin our discussion of the results by reporting results from the LOWESS
regression of sectoral employment shares on GDP per capita, which give an
indication of how structural change occurs as economies move between different
收入水平. The results from this method are akin to the early work of Chenery
(1960), 除其他外, who attempted to detect the typical pattern of structural
change along the path of so-called modern economic growth (Kuznets 1971). 这
results are displayed in Figure 1.

The most visible aspect of structural transformation in Figure 1 is the declining
share of employment in agriculture as income (GDP per capita) progresses. At a
level of GDP per capita below $5,000, which roughly corresponds to the cutoff between low- and middle-income economies, agriculture is the dominant sector in the economy. In low-income economies, agriculture is typically responsible for 80% or more of total employment. As income progresses, 然而, the share of employment in the agriculture sector declines rapidly to less than 10% at GDP per capita of $15,000 and only about 1% as the income level approaches $25,000. When the employment share of agriculture falls, the corresponding shares of all other sectors tend to increase. These other sectors can be roughly divided into three 6For some economies, it was not possible to move between these income levels either because they had already done so or they had already crossed the lower bound prior to 1950. l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 82 ASIAN DEVELOPMENT REVIEW Figure 1. LOWESS Regression of the Relationship between Employment Shares and Income per Capita FIRBS = ﬁnancial intermediation, renting, and business services; GDP = gross domestic product; PPP = purchasing power parity; TransCom = transport and communications. 来源: 作者的计算. groups based on the shares of total employment that they attain in the transition from a low-income to a middle-income economy. In the ﬁrst group are manufacturing; 贸易 (wholesale and retail, including restaurants and hotels); and the public sector. The employment shares of these sectors grow rapidly when the share of agriculture decreases, and they each quickly exceed 10% of total employment. The second group consists of construction, transport and communications, and FIRBS. These sectors’ employment shares generally do not exceed 10% by the time the economy reaches middle-income status. The ﬁnal group consists of mining and public utilities, which do see rising shares as the employment share of agriculture declines; typically these sectors remain very small, 然而, with an employment share of only about 1% each. With the transition from middle-income to high-income status, another major structural change takes place. After reaching a peak employment share of around 30% when income per capita reaches $12,000, the employment share of the
manufacturing sector begins to decline as an economy further develops. 同时,
the employment shares of trade, the public sector, and FIRBS continue to grow.
The employment share of the FIRBS sector surpasses that of manufacturing at an
income level of around $25,000. Largely consistent with expectations, we may conclude from Figure 1 that the transition from a low-income economy to a high-income economy is a process in which an economy broadly shifts from being agricultural based to service based. l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 83 数字 2. Structural Decomposition for a Typical Economy l D o w n o a d e d f r o m h t t p : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 来源: 作者的计算. The manufacturing sector plays a transitory role, with its importance reaching a peak at the middle-income stage. It is this process of structural transformation that we now examine further, focusing on growth and transformation in Asian economies and comparing their performance with that of a typical economy. Prior to discussing the performance of individual Asian economies, we undertake the decomposition analysis described in section II for a typical economy in our sample. 要做到这一点, we use the results of the LOWESS regression of employment shares described in Figure 1, along with results from a similar LOWESS regression of a sector’s contribution to overall labor productivity, ( yi y si ). Using the ﬁtted values from these LOWESS regressions, we obtain relative productivities and employment shares for different income levels, which we then feed into equation (3) to obtain the structural decomposition for a typical economy that moves between two income levels. 数字 2 reports the results of this decomposition for a typical economy as it moves from an income level of $1,500 到 $5,000 (an increase of 233%), 从 $5,000
到 $10,000 (an increase of 100%), 从 $10,000 到 $15,000 (an increase of 50%), 从 $15,000 到 $20,000 (an increase of 33%), 和来自 $20,000 到 $25,000 (an increase of 25%).7 数字 2 also includes the duration of the movement of a typical economy from one income level to another. The results in Figure 2 suggest a number of interesting patterns for our typical economy. 第一的, we see that the contributions of the different decomposition terms 7Movements between these income levels can be achieved at different speeds, with higher average annual growth rates in economies that are able to traverse the different income levels more quickly. 84 ASIAN DEVELOPMENT REVIEW are roughly equal as income moves from $1,500 到 $5,000, with the shift term (30.5%) being slightly lower than the other two terms. This implies that the typical economy requires a transformation across three dimensions—increased productivity within sectors, structural change, and increased employment participation—to move from low- to middle-income status. As we shift between higher income levels, we observe a steadily declining contribution of the shift term, which becomes (轻微地) negative as income moves from $20,000 到 $25,000. This likely reﬂects the fact that at higher income levels, the amount of structural change that takes place is quite small—with the exception of the agriculture and mining sectors, which have very low employment shares at higher income levels (数字 1). While accounting for less than 50% of the required change in income at lower income levels, the within effect comes to dominate at higher income levels, accounting for more than 75% of the income change when moving from $10,000 到 $15,000, 从 $15,000 到 $20,000, 和来自 $20,000 到 $25,000. The growth in employment participation is found to be relatively more important for changes at lower income levels, explaining more than 30% of the change in income from $1,500 到 $5,000 和来自 $5,000 到 $10,000. Its contribution then drops to 20% or below before becoming relatively more important again for the income change from $20,000 到 25,000 (25%). The ﬁnal thing to note from this ﬁgure is the time it
takes to traverse between two income levels. Here we observe something like linear
decay, with it taking 29 years for the typical economy to move between income
levels of $1,500 和 $5,000, and just 10 years to move between income levels
的 $20,000 和 $25,000. While useful for the comparison of the typical economy
with Asian economies, these numbers do not tell us that (annual) GDP per capita
growth is on average higher as economies move between higher income levels,
since the percentage change in income is smaller for the movements between higher
收入水平. 实际上, the fastest annual growth rate for GDP per capita is observed
in the movement from $1,500 到 $5,000 (an increase in GDP per capita of 233% 超过
29 年), and the slowest is observed in the movement from $20,000 到 $25,000
(an increase in GDP per capita of 25% 超过 10 年).

The results in Figure 2 suggest that structural change—captured by the shift
term—is an important factor for a typical economy moving between lower levels
of income and is less relevant at higher levels, while changing productivity within
sectors is relevant at all income levels, most notably higher income levels. 这
role of increased employment participation is varied, but tends to be stronger at
lower income levels. The results for the structural change term are consistent with
expectations and with existing studies. McMillan, Rodrik, and Verduzco–Gallo
(2014) point out that intersectoral productivity gaps tend to diminish during the
course of development. 所以, even if the movement between higher income
levels involves signiﬁcant structural change, such as the observed shift from
manufacturing to services, the overall impact on productivity growth will be small.

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 85

数字 3. Structural Decomposition of a Move in Income per Capita from $1,500 到 $5,000

来源: 作者的计算.

We now compare this typical pattern with the decomposition results for the
set of Asian economies that traversed each of these income levels during the period
for which we have data. We also include non-Asian economies for comparison.

数字 3 reports the results for the set of Asian economies that moved between
the income levels of $1,500 和 $5,000 over the period 1950–2010, along with results
for the typical economy and for Botswana for purposes of comparison.8 There is a
wide variety of experiences in moving between these two income levels, 包括
differences in the contributions of the three decomposition terms relative to the
typical economy in most cases. Some Asian economies—most notably the Republic
of Korea (17 年); Taipei,中国 (17 年); the PRC (19 年); 和, to a lesser
extent, Thailand (24 年)—were able to move quickly from an income level of
$1,500 到 $5,000, with average annual GDP per capita growth rates of between 9.7%
和 13.7%. 同时, the relative contributions of the three decomposition
terms differed signiﬁcantly among these four economies.

In the Republic of Korea, the vast majority of income growth (大约 60%
of the total) was due to increased employment participation, with a relatively small
contribution from within-sector productivity growth (25% of the total) and only a
minor role for structural change (15% of the total). 所以, the role of productivity
growth in this case is minor relative to increased labor effort. Structural change
made a similarly small contribution to income growth in Taipei,中国, 但是

8Botswana and Indonesia reached the $5,000 income per capita level in 2011 和 2012, 分别. For the full sample of 133 economies for which we have GDP per capita data, 15 economies completed this transition during the period 1950–2010. l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 86 ASIAN DEVELOPMENT REVIEW relative importance of the within and employment participation effects were reversed relative to the case of the Republic of Korea. The importance of the within effect was even stronger in the PRC, accounting for around 92% of the change in income. 有趣的是, the contribution of employment participation was actually negative, indicating a declining share of the population employed in the PRC. As with the cases of Taipei,China and the Republic of Korea, the relative importance of structural change to income growth was muted, contributing around 15% of the total change in income per capita. Thailand, which also took a relatively short period of time to move between the income levels of $1,500 和 $5,000, showed a pattern more similar to that for the typical economy, with a fairly even split between the three different composition terms. Structural change played the most prominent role by a slight margin, accounting for around 39% of the overall change in income per capita. In terms of the remaining economies in Figure 3, the results for Indonesia are quite similar to those for both the typical economy and Thailand, with a fairly even split between the three decomposition terms and a relatively more important role for the structural change term, which accounts for 38% of the total change in income per capita. The major difference when compared with Thailand is the relatively long period of time it took to move from an income level of $1,500 到 $5,000 (39 年), implying an average annual growth rate of GDP per capita of around 6%. The comparison economy, 博茨瓦纳, is quite different from most other economies and is most similar to the PRC with respect to the decomposition terms. In Botswana’s case, we see a minor role for employment participation growth in GDP per capita growth, with a relatively large role (67% of the total) for within-sector productivity growth and a moderate role for structural change (31% of the total). 数字 4 repeats the above exercise for a transition between income levels of $5,000 和 $10,000, with results reported for seven Asian economies; the baseline typical economy; and ﬁve other comparison economies (阿根廷, 智利, 意大利, Mauritius, and Spain) that achieved the transition during the review period and for which we have sectoral employment data.9 The Asian economies that moved between these two income levels did so relatively quickly, with the transition lasting between 8 和 11 years in all cases except Malaysia, which took 20 年. The average duration of Asian economies’ transition was shorter than that of the typical economy (19 年) and of the other comparison economies, of which Argentina stands out with a duration of 59 年. With respect to the contributions of the different terms, we again see a great deal of heterogeneity, with none of the Asian economies following the path of the typical economy. There are other similarities with Figure 3 还有. 尤其, we again ﬁnd that for the Republic of Korea—as well as Singapore and, to a lesser 9In the sample of 133 经济体, 26 economies achieved this transition during the period 1950–2010. The PRC completed the transition in 2013. l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 87 数字 4. Structural Decomposition of a Move in Income per Capita from $5,000 到 $10,000 来源: 作者的计算. extent, Taipei,China—the growth of employment participation accounted for much of the change in income level: 大约 50% in the Republic of Korea and Singapore, 和 32% in Taipei,中国. In other Asian economies, the contribution of employment participation growth was much smaller, accounting for less than 20% in Japan and Malaysia, and making a negative contribution in the PRC (as was also the case with Figure 3). For the PRC, the negative contribution is relatively large, indicating a fairly large decline in employment participation growth. Productivity growth within sectors is an important factor for all economies in Figure 4, with the contribution of the within effect ranging from 34% in the Republic of Korea to 115% in the PRC. The shift term capturing structural change is relatively unimportant, accounting for around 21% of the change in income per capita in the typical economy and even smaller contributions in all Asian economies except the PRC, where structural change accounts for 41% of the overall change in income per capita. The average contribution of the shift term across the economies reported in Figure 4 is just 10%, which is considerably smaller than the average contribution of 27% reported in Figure 3. An interesting comparison exists between the case of the PRC and that of Argentina. Both of these economies saw relatively large contributions of the within effect to the change in income per capita, but while the PRC also had a positive contribution from the shift term and a negative contribution from the growth of employment participation, Argentina saw a negative contribution from the shift term and a positive contribution from the growth of employment participation. These two economies were also at opposite extremes with regard to the speed of transition. 的确, there exists a strong positive correlation between the speed of transition and l D o w n o a d e d f r o m h t t p : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 88 ASIAN DEVELOPMENT REVIEW Figure 5. Structural Decomposition of a Move in Income per Capita from $10,000 到 $15,000 l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 来源: 作者的计算. the contribution of the shift term (0.57) for the observations reported in Figure 4, with similar positive correlations also found for the shift in income per capita from $10,000 到 $15,000 (数字 5) 和来自 $15,000 到 $20,000 (数字 6). 数字 5 repeats the decomposition exercise for the transition in income per capita from $10,000 到 $15,000. The ﬁgure reports results for ﬁve Asian economies; the benchmark typical economy; 和 10 other comparison economies (智利, 丹麦, 法国, 意大利, Mauritius, 荷兰人, 西班牙, 瑞典, 英国, 和美国) that achieved the transition during the period 1950–2010.10 As with the previous ﬁgure, we observe that Asian economies were able to shift between these two income levels relatively quickly, with the transition taking 9 years or less in all Asian economies except Japan, where the transition took 14 年, which was slightly more than for the typical economy. The duration of the transition was longer than that of the typical economy in most other comparison economies, with only Chile, Mauritius, and Spain experiencing a transition in less than the 12 years it took the typical economy. 数字 5 highlights the continued decline in the importance of the shift term to the change in income. 平均而言, the contribution of the shift term is just 5% for the observations included in Figure 5, compared with 10% in the case of the movement in income from $5,000 到 $10,000, 和 27% for the movement from $1,500 到 $5,000. For the Asian economies in the sample, only in the cases of Hong 10Out of the 133 economies in the broader sample for which we have GDP per capita data, 31 made the transition from an income level of $10,000 到 $15,000 during the period 1950–2010. THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 89 孔, 中国 (37%) 和, to a lesser extent, 日本 (16%) does the shift term make a signiﬁcant contribution to the income change; its contribution accounts for less than 10% in Singapore and Taipei,中国, and is negative in the Republic of Korea. Despite the relatively small contribution of the shift term in Asian economies, we obtain a positive correlation (0.32) between the share of the income change accounted for by the shift term and the speed of the transition. 相似地, we also see a declining role for employment participation growth. While this term accounts for between 20% 和 25% of the income change in Figures 3 和 4, it only accounts for an average of 12% for the economies in Figure 5. 有趣的是, employment participation growth makes a large contribution to the change in income in Spain (64%) 和, to a lesser extent, 智利 (46%). It also remains important in the Republic of Korea (31%), which is consistent with the other income changes shown in Figures 3 和 4. In Hong Kong, 中国, 然而, the contribution of employment participation growth is negative, indicating a decline in employment participation as the economy moved between income levels of $10,000
和 $15,000. The above results imply an increasing role for the within effect and for productivity growth within sectors. This term accounts for 83% of the income change on average for the observations included in Figure 5, though only 40% in the case of Spain. For the Asian economies, the contribution of the within effect to income growth ranged from 73% in the Republic of Korea to more than 97% for Hong Kong, 中国; 日本; and Taipei,中国. 最后, 数字 6 presents the decomposition results for economies that observed a change in income per capita from $15,000 到 $20,000 during the review period. This includes the decomposition results for ﬁve Asian economies; the typical economy; and six other comparison economies (丹麦, 法国, 荷兰人, 瑞典, 英国, 和美国).11 再次, we observe that the Asian economies were able to move between the two income levels relatively quickly. The duration of the transition was 8 years or less for all Asian economies except Japan, which at 11 years still had a duration less than that for the typical economy and the other comparison economies. We again see a declining role for the shift term, which captures structural change, 图中 6. 平均而言, the contribution of the shift term to the change in income is basically zero (–0.9%), though this hides differences across economies. While for some economies (法国, 荷兰人, 新加坡, 瑞典, and the United Kingdom) the contribution of the shift term is negative, in most Asian economies the contribution is positive. In the case of Hong Kong, 中国, it is relatively important, accounting for 45% of the overall change in income. The fact 11Of the 133 economies in the sample, 22 moved between income levels of $15,000 和 $20,000 during the period 1950–2010. We also conducted the decomposition for a transition between income levels of $20,000 和
$25,000. Given that only two Asian economies (香港, China and Singapore) and a limited number of other economies (12) in the overall sample achieved this transition, we choose not to report the results. l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 90 ASIAN DEVELOPMENT REVIEW Figure 6. Structural Decomposition of a Move in Income per Capita from $15,000
到 $20,000 l 从http下载 : / / 直接的 . 米特 . / e d u a d e v / 文章 – p d l f / / / / / 3 3 2 7 4 1 6 4 2 6 8 2 a d e v _ a _ 0 0 0 7 3 压力 . 来宾来访 0 8 九月 2 0 2 3 来源: 作者的计算. that structural change again becomes important for some economies around these income levels is consistent with the results reported in Figure 1, suggesting a second period of structural change—this time from manufacturing to services—at incomes above $12,000.

The within effect accounts for a similar share of the overall income change
(81%) as was the case with the movement in income per capita from $10,000 到 $15,000. It accounts for a particularly large share in Japan (96%) and Singapore
(114%), as well as in France, 瑞典, and the United Kingdom, where it accounts
for more than 100% of the income change. While reaching 57% in the Republic
of Korea, the within effect is relatively less important in other Asian economies,
contributing between 35% 和 40% of the overall income change in Taipei,中国
and Hong Kong, 中国.

The importance of employment participation growth is also mixed for the
Asian economies. Its contribution is small but negative in Japan and Singapore.
同时, this term continues to play an important role in the Republic of
韩国 (41%) as it has for all previous movements in income levels. It also plays a
particularly important role in Taipei,中国 (55%), but is somewhat less important
in Hong Kong, 中国 (19%).

V. Summary and Conclusion

在本文中, we combine a standard decomposition of labor productivity
growth with data on the growth of employment participation to decompose GDP per

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 91

capita growth into an effect due to productivity growth within sectors, an effect due
to structural change, and an effect due to changing labor force participation growth.
Using this decomposition, we examine the importance of the relative contributions of
these three effects as economies move between different income levels, concentrating
on a set of Asian economies and comparing results for these economies with those
for a typical economy and other comparison economies.

A number of interesting results emerge. 第一的, we observe that the importance
of structural change (the shift term) varies by income level. Structural change tends
to be relatively important as economies move from low- to middle-income status,
but its role diminishes during the transition between middle-income levels. 给定
the relatively large percentage change in GDP per capita as economies move from
an income level of $1,500 to an income level of $5,000, structural change will
contribute a great deal to GDP per capita growth at low-income levels. 这
contribution of 30% for the typical economy implies that structural change accounts
for more than 70 的 233 percentage point increase in GDP per capita, 哪个, 和
an average transition period of 29 年, implies that structural change adds around
2.7 percentage points annually to GDP per capita growth in low-income economies.
As economies move toward higher levels of income per capita, structural change
again becomes important for some economies, likely reﬂecting the second structural
change from manufacturing to services observed in many economies. 的效果
structural change tends to be more muted at higher income levels, probably due to
the fact that intersectoral productivity differences tend to diminish as economies
发展.

第二, the effect due to productivity growth within sectors is relatively
small for changes from low- to middle-income status, but dominates the change
from middle- to high-income status. 第三, the Asian economies in our sample are
relatively successful in moving quickly between income levels. 一般来说, Asian
economies traverse the different income levels signiﬁcantly faster than economies
from other regions. 第四, Asian economies do not tend to follow the path of the
typical economy as they move toward higher income levels, with the decompositions
for Asian economies tending to look quite different from those of the typical
economy and other comparison economies. There is also no common path for
Asian economies, with the decompositions for each Asian economy differing from
另一个.

第五, despite the different development experiences of individual Asian
经济体, there are certain patterns that can be observed for particular economies as
they move between different income levels. In the case of the Republic of Korea, 为了
例子, we observe that employment participation growth has been an important
factor in the economy’s movements across different income levels, 特别
during the movement from low- to middle-income status. Structural change also
played a role in the Republic of Korea’s movement from low- to middle-income
地位, but has had a small role at higher income levels. 反过来, the within

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

92 ASIAN DEVELOPMENT REVIEW

effect plays a relatively minor role at lower income levels, but comes to dominate
at higher income levels in the Republic of Korea. In the PRC, which experienced
movements between income levels of $1,500 和 $5,000 和之间 $5,000 和 $10,000 during the review period, we observe that the within effect is relatively large,
while there is a negative contribution from employment participation growth. 这
role of structural change, while much smaller than that of the within effect, is found
to be positive and important, particularly for the move from $5,000 到 $10,000.
In Taipei,中国, the role of structural change is generally small, making its largest
contribution (16% of the total) in the movement from an income level of $1,500 到 $5,000; its contribution is as low as 4% for the transition between income levels
的 $5,000 和 $10,000. The within effect is the dominant factor for Taipei,中国
as it moves between most income levels, accounting for 100% of the move from
an income level of $10,000 到 $15,000. The exception to this is Taipei,China’s
move from an income level of $15,000 到 $20,000, where employment participation
accounts for 55% of the change in income per capita. The within effect is also the
dominant factor in the case of Japan, making its smallest contribution (68%) 在里面
move between income levels of $5,000 和 $10,000, and its largest contribution
(98%) in the move between $10,000 和 $15,000. The role of structural change is
fairly similar across the different income groups, accounting for between 10% 和
15% of the change. In contrast with some Asian economies such as the Republic of
韩国, the role of employment participation is fairly muted in Japan, contributing a
maximum of 20% in the move from an income level of $5,000 到 $10,000. 最后, 在
the case of Singapore we see a dominant role for the within effect at all levels except
for the move from an income level of $5,000 到 $10,000; 在这种情况下, 就业
participation growth contributes nearly half of the increase in income. Apart from
this movement, neither employment participation nor the shift term contributes more
比 10% to the change in income levels in Singapore.

全面的, the results suggest that for most Asian economies labor productivity
growth was the dominant source of gains in GDP per capita growth—the major
exception being the Republic of Korea. This observation holds at movements
between higher income levels. While these gains could be due to either capital
deepening (例如, an increase in the capital–labor ratio) or to total factor productivity
gains, we can say that in most cases much of the growth of labor productivity is due
to within-sector changes in labor productivity growth rather than the result of labor
shifting across sectors, particularly at transitions between higher income levels. 这
result is consistent with other recent studies, including Timmer, de Vries, 和的
Vries (2014), who ﬁnd that the within effect is the dominant factor in explaining
labor productivity growth in Asia.

Structural change remains an important factor in driving GDP per capita
growth at lower income levels. Such a conclusion implies that while policies aimed
at encouraging structural change are likely to be rewarded at relatively low income
级别, the focus as economies develop should be aimed at increasing productivity

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3

THE ROLE OF STRUCTURAL CHANGE IN ASIA’S ECONOMIC DEVELOPMENT 93

growth rates in general and in services in particular as production tends to become
more concentrated in this sector at higher income levels.

While policies encouraging structural change at lower income levels should
be focused on shifting resources from agriculture to manufacturing, it is not easy
to identify the exact set of policies needed to encourage structural change at lower
income levels since such change takes place under widely divergent conditions across
different economies. Industrial policies should therefore be tailored to an economy’s
speciﬁc circumstances, including the presence of manufacturing industries, stage of
发展, resource endowment, and economy size.

References∗

Chenery, H. 乙. 1960. Patterns of Industrial Growth. The American Economic Review 50 (4):

624–54.

Denison, 乙. F. 1967. Why Growth Rates Differ. 华盛顿, 直流: Brookings.
Fabricant, S. 1942. Employment in Manufacturing, 1899–1939. 纽约: 国家统计局

经济研究.

Feenstra, 右. C。, 右. Inklaar, 和M. 磷. Timmer. 2015. The Next Generation of the Penn World

桌子. American Economic Review 105 (10): 3150–82.

Felipe, J. 1997. Total Factor Productivity Growth in East Asia: A Critical Survey. EDRC Report

Series No. 5. Manila: Asian Development Bank.

Hsieh, C.-T., 和P. J. Klenow. 2009. Misallocation and Manufacturing TFP in China and India.

Quarterly Journal of Economics 124 (4): 1403–48.

Krugman, 磷. 1994. The Myth of Asia’s Miracle. 外交事务 73 (6): 62–78.
Kuznets, S. 1971. Economic Growth of Nations: Total Output and Production Structure.

剑桥, 嘛: Belknap Press of Harvard University Press.

Maddison, A. 1987. Growth and Slowdown in Advanced Capitalist Economies: Techniques of

Quantitative Assessment. Journal of Economic Literature 25 (92): 649–98.
Maddison Project Database. http://www.ggdc.net/maddison/maddison-project/home.htm
McMillan, M。, D. Rodrik, 和我. Verduzco–Gallo. 2014. Globalization, Structural Change, 和
Productivity Change, with an Update on Africa. World Development 63 (2014): 11–32.
纳尔逊, 右. R。, 和H. Pack. 1999. The Asian Miracle and Modern Growth Theory. 经济的

杂志 109 (457): 416–36.

Pavcnik, 氮. 2002. Trade Liberalization, 出口, and Productivity Improvements: 证据来自

Chilean Plants. Review of Economic Studies 69 (1): 245–76.

Romer, 磷. 1993. Idea Gaps and Object Gaps in Economic Development. Journal of Monetary

经济学 32 (3): 543–73.

Solow, 右. 1956. A Contribution to the Theory of Economic Growth. Quarterly Journal of

经济学 70 (1): 65–94.

Timmer, 中号. P。, G. J. de Vries, and K. de Vries. 2014. Patterns of Structural Change in Developing
Economies. GGDC Research Memorandum No. 149. Groningen: Groningen Growth and
Development Centre.

Young, A. 1992. A Tale of Two Cities: Factor Accumulation and Technical Change in Hong Kong

and Singapore. 剑桥, 嘛: 国家经济研究局.

∗ADB recognizes “China” as the People’s Republic of China and “Hong Kong” as Hong Kong, 中国.

我

D
哦
w
n
哦
A
d
e
d

F
r
哦
米
H

t
t

:
/
/

d
我
r
e
C
t
.

米

我
t
.

e
d
你
A
d
e
v
/
A
r
t
我
C
e
–
p
d

我

F
/

3
3
2
7
4
1
6
4
2
6
8
2
A
d
e
v
_
A
_
0
0
0
7
3
p
d

乙
y
G
你
e
s
t

哦
n
0
8
S
e
p
e
米
乙
e
r
2
0
2
3
下载pdf