Structural Transformation around the World: - Am MIT spezialisierte KI-Forschung

Structural Transformation around the World:
Patterns and Drivers
Kunal Sen∗

The conventional view of structural transformation is informed by three stylized
facts of economic development: (ich) all economies exhibit declining employment
in agriculture, (ii) all economies exhibit a hump-shaped share of employment
in industry, Und (iii) all economies exhibit an increasing share of employment
this presumed path of structural
in services. In diesem Papier, I show that
transformation may no longer be the route to economic development
In
low-income economies. Classifying economies as either structurally developed,
structurally developing, or structurally underdeveloped, I observe a different
path of structural transformation in structurally underdeveloped economies in
which workers are moving directly from agriculture to nonbusiness services,
which as a sector does not have the same productivity gains as manufacturing.
I also show that the mainstream approach is unable to explain the patterns
of structural transformation observed in low-income developing economies.
This suggests the need to rethink the theoretical premises behind much of
the mainstream approach to structural transformation and to identify alternate
causal mechanisms to explain the different types of structural transformation
underway in the developing world.

deindustrialization,

Schlüsselwörter:
transformation
JEL-Codes: O11, O14, O47

employment,

productivity,

strukturell

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ICH. Einführung

Economists have long searched for patterns that relate successful economic
development to structure and policy (Syrquin and Chenery 1989). This comparative
approach in development economics was initiated by Simon Kuznets and predicated
on “the existence of common, transnational factors and a mechanism of interactions
among nations that will produce some systematic order in the way modern
economic growth can be expected to spread around the world” (Kuznets 1959,
170). One of the most striking ﬁndings of this comparative approach to economic
development was the “universal inverse association of income and the share
of agriculture in income and employment” (Syrquin and Chenery 1989, 172).

∗Kunal Sen: Director, United Nations University World Institute for Development Economics Research
(UNU-WIDER). Email: sen@wider.unu.edu. The author would like to thank the managing editor and the journal
referees for helpful comments and suggestions. The usual ADB disclaimer applies.

Asiatischer Entwicklungsbericht, Bd. 36, NEIN. 2, S. 1–31
https://doi.org/10.1162/adev_a_00130

© 2019 Asian Development Bank and
Asian Development Bank Institute.
Veröffentlicht unter Creative Commons
Namensnennung 3.0 International (CC BY 3.0) Lizenz.

2 Asiatischer Entwicklungsbericht

As Kuznets argued, one of the key features of modern economic growth
was the movement of workers from agriculture to manufacturing and services
(Kuznets 1966). The comparative approach identiﬁed the manufacturing sector
as the engine of economic growth for most economies and the rate at which
industrialization occurred differentiated successful economies from unsuccessful
ones (McMillan, Rodrik, and Verduzco-Gallo 2014; Haraguchi, Cheng, and Smeets
2017). Jedoch, at a certain stage of economic development, as productivity growth
in manufacturing exceeds productivity growth in agriculture and services, Und
as demand for services expands, the service sector becomes the major provider
of employment, and the manufacturing sector lessens in importance in terms of
providing employment, though not in terms of output growth (Chenery and Syrquin
1975, Syrquin 1988, Syrquin and Chenery 1989).

The movement of workers from agriculture to manufacturing to services
has been the path of structural transformation in all economies that comprise the
high-income club as well as the pattern of successful growth in East Asia. Das
path of structural transformation has received a great deal of attention among
economists and underpins most of the theoretical understanding of structural
transformation—all the way from scholars in classical economics such as Kuznets,
Lewis, Chenery, and Syrquin to more modern approaches that are rooted in the
neoclassical tradition (sehen, Zum Beispiel, Duarte and Restuccia 2010; Dabla-Norris
et al. 2013; Herrendorf, Rogerson, and Valentinyi 2014; McMillan, Rodrik, Und
Verduzco-Gallo 2014; Diao, McMillan, and Rodrik 2017). Jedoch, as will be
documented, this path of structural transformation may no longer be the route
to economic development among low-income economies. Stattdessen, I observe a
different path of structural transformation where workers are moving directly from
agriculture to nonbusiness services, which as a sector does not have the same
productivity gains observed in manufacturing. If this is the path of structural
transformation that we are likely to see in the developing world, especially among
the poorest economies, what implications does this have for our conventional view
of structural transformation? What are the implications of the direct movement of
workers from agriculture to nonbusiness services for economic growth? What are
the drivers of such an alternate path of structural transformation? How well does the
mainstream approach to structural transformation explain recent patterns, especially
in low-income economies?

In diesem Papier, I ﬁrst review the recent theoretical approach to structural
transformation in the mainstream literature. I then document the patterns of
structural transformation observed in developing and developed economies. ICH
then examine the implications of different paths of structural transformation
for economic growth. I next examine the drivers of the alternate paths of
structural transformation. Endlich, I take a prototype mainstream model of structural
transformation—Duarte and Restuccia (2010)—and examine how well the model
does in explaining patterns of structural transformation.

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Structural Transformation around the World 3

II. Theoretical Perspectives on Structural Transformation

In the 1950s, led by economists like Hollis Chenery, Moses Syrquin, Und
Simon Kuznets, a program of research was developed to understand the features
and preconditions of modern economic growth (Lewis 1954, Chenery and Syrquin
1975, Syrquin 1988). Core to this research was the interest in understanding “the
interrelated processes of structural change that accompany economic development
. . . jointly referred to as structural transformation” (Syrquin 1988, 206). One of
the most robust ﬁndings from this program of research was that “in the economies
where per capita income grew signiﬁcantly, the proportion of the labour force
engaged in agriculture declined and that engaged in nonagriculture increased”
(Kuznets 1965, 24). Kuznets also noted that, in more advanced economies, “the
shares of mining and manufacturing in the total labour force grew signiﬁcantly, Aber
the increases have ceased or slowed down in recent decades . . . the shares of trade
and other services have grown steadily in recent decades” (Kuznets 1965, 25).

A more recent analysis of the pattern of structural transformation is provided
by Duarte and Restuccia (2010), who use sectoral employment data for 29 hoch-
and middle-income economies that are obtained from the EU KLEMS data and
the International Labour Organization’s LABORSTA database (ILOSTAT). Duarte
and Restuccia (2010) ﬁnd that “all economies in the sample follow a common
process of structural transformation. Erste, all economies exhibit declining shares of
hours in agriculture, even the most advanced economies in this process, such as the
United Kingdom and the United States (US). Zweite, economies at an early stage
of the process of structural transformation exhibit a hump-shaped share of hours
in industry, whereas this share is decreasing for economies at a more advanced
stage. Endlich, all economies exhibit an increasing share of hours in services”
(Duarte and Restuccia 2010, 135). They go on to state: “The processes of structural
transformation observed in our sample suggest two additional observations. Erste,
the lag in the structural transformation observed across economies is systematically
related to the level of development: poor economies have the largest shares of
hours in agriculture, while rich economies have the smallest shares. Zweite, unser
data suggest the basic tendency for economies that start the process of structural
transformation later to accomplish a given amount of labor reallocation faster than
those economies that initiated this process earlier” (Duarte and Restuccia 2010,
135).

The Neoclassical (Mainstream) Approach to Structural Transformation

The workhorse model of economic growth is the Solow–Swan model,
which by its very nature, abstracts from sectoral allocation issues in the process
of economic development, focusing on the role of capital accumulation and
technological change in the aggregate. As Herrendorf, Rogerson, and Valentinyi

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4 Asiatischer Entwicklungsbericht

(2014) Notiz: “The one-sector growth model has become the workhorse of modern
macroeconomics. The popularity of the one-sector growth model is at least partly
due to the fact that it captures in a minimalist fashion the essence of modern
economic growth, which Kuznets (1973) in his Nobel prize lecture described as
the sustained increase in productivity and living standards. By virtue of being a
minimalist structure, the one-sector growth model necessarily abstracts from several
features of the process of economic growth. One of these is the process of structural
transformation, das ist, the reallocation of economic activity across the broad sectors
agriculture, manufacturing and services” (Herrendorf, Rogerson, and Valentinyi
2014, 855).

For a long time, there was limited interest in the question of structural
transformation in the neoclassical school of economics. This changed in the 2000s,
with a series of path-breaking papers that developed multisector versions of the
one-sector growth model that were consistent with the stylized facts of structural
transformation, such as Rogerson (2007); Ngai and Pissarides (2007); Duarte and
Restuccia (2010); and Herrendorf, Rogerson, and Valentinyi (2014). Two classes of
models were developed: (ich) one where the causal explanation was technological
in nature and which attributed structural transformation to different rates of
sectoral total factor productivity growth, Und (ii) a utility-based explanation that
required different income elasticities for different goods and could yield structural
transformation even with equal total factor productivity growth across all sectors.

Hier, we describe a model of structural transformation that combines both

of these explanations. The model is drawn from Duarte and Restuccia (2010).

A Model of Structural Transformation

In the Duarte and Restuccia (2010) Modell,

there are three sectors—
agriculture (A), manufacturing (M), and services (S)—which are produced using
constant returns-to-scale production functions. Sector-speciﬁc technology is given
by Ai, where i is agriculture, manufacturing, and services.

The model assumes a continuum of homogenous ﬁrms in each sector that
are competitive in goods and factor markets. The representative household is
endowed with L units of labor, which is supplied inelastically to the market.
The representative household consumes agricultural goods (ca) and a composite
nonagricultural good comprising manufacturing (cm) and services goods (cs). Der
model assumes a closed economy and abstracts from intertemporal optimization
(somit, the model is static and the problem of the household is effectively a
sequence of static problems).

The per period utility is given by

u(ca,T, ct ) = a log(ca,t − ¯a) + (1 − a) log(ct ),

a ∈ [0, 1]

(1)

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Structural Transformation around the World 5

The subsistence level of agricultural goods below which the household
cannot survive is given by ¯a > 0. The composite nonagricultural good (ct ) is given
von

ρ
ct = [v. Chr
M,T

+ (1 − b)(cs,T + ¯s)ρ]1/ρ

(2)

where ¯s > 0, b is between 0 Und 1, and ρ < 1. For ¯s > 0, these preferences imply
that the income elasticity of services is greater than 1. daher, ¯s works as a
negative subsistence consumption level: when the income of the household is low,
fewer resources are allocated to the production of services, and when the income of
the household rises, resources are reallocated to services.

Both product and labor markets clear, so that La + Lm + Ls = L and ca = Ya,
cm = Ym, and cs = Ys. The ﬁrst-order conditions for consumption imply that the
optimal labor input in agriculture (Der) is given by
(cid:2)
L + ¯s
Als

La = (1 − a)

¯a
Aa

+ A

(3)

(cid:3)

When a = 0, the household consumes ¯a of agricultural goods each period, and labor
allocation in agriculture depends on the level of labor productivity in that sector. Als
labor productivity in agriculture increases, labor moves away from the agriculture
sector.

The ﬁrst-order conditions for consumption of manufacturing and service

goods imply that

Lm = (L − La) + ¯s/As

1 + X

Wo
(cid:2)

x ≡

B
1 − b

(cid:3)

1/(ρ−1)

(cid:2)

(cid:3)ρ/(ρ−1)

Bin
Als

(4)

This equation reﬂects the two forces that drive labor reallocation between
manufacturing and services in the model. The technological explanation will stress
the role of differential productivity growth in explaining structural transformation.
This is evident if we assume homothetic preferences (das ist, ¯s = 0). In diesem
Fall, Lm/Ls = 1/x and differential productivity growth in manufacturing relative
to services is the only source of labor reallocation between these sectors as long
as ρ is not equal to 0. Insbesondere, when ¯s = 0, the model can be consistent
with the observed reallocation of labor from manufacturing to services as labor
productivity grows in manufacturing relative to services and as long as the elasticity
of substitution between manufacturing and services is low. The second explanation
is the utility-based explanation, which is evident if ¯s > 0 (das ist, preferences are
nonhomothetic) and labor productivity grows at the same rate in manufacturing and

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6 Asiatischer Entwicklungsbericht

services, or ρ = 0, so that x is constant. Hier, for a given La there is a reallocation
of labor from manufacturing to services as the latter is more income elastic than the
ehemalig, per the so-called Engel effects (sehen, Zum Beispiel, Clark 1940).

III. Paths of Structural Transformation

Data

The data on structural transformation come from the Groningen Growth and
Development Centre (GGDC) database of the University of Groningen (Timmer, von
Vries, and de Vries 2015). The GGDC data are widely used in the recent literature
on structural transformation (sehen, Zum Beispiel, Diao, McMillan, and Rodrik 2017;
Comin, Lashkari, and Mestieri 2018). Es gibt 41 economies in the database,
which includes annual disaggregated data on real value added and employment by
sector from 1960 Zu 2012. For the purpose of this paper, the GGDC data provide
information on manufacturing and nonmanufacturing industries (construction,
mining, and utilities) separately, as well as disaggregated data on services by type
of sector (business services, government services, trade, and hotels and restaurants,
unter anderen). Table A1 in the Appendix provides details on the 10 sectors in the
GGDC data. Employment is deﬁned as “all persons employed,” including all paid
employees, as well as self-employed and family workers.

The GGDC dataset includes 12 African economies (including North Africa),
9 Latin American economies, 11 Asian economies (including Japan), and the US,
with the rest coming from Europe. A key strength of the employment data is
that the source for each economy is the population census, which ensures full
coverage of the working population as well as a precise sectoral breakdown. Der
population census, which tends to be quinquennial or decennial in most economies,
is supplemented by the labor force surveys and the business surveys to derive annual
trends. The use of the population census also ensures that informal employment,
which is important in many low- and middle-income economies, is captured in
the GGDC data. Another feature of the data is the careful attention paid to
intertemporal, International, and internal consistency (Timmer and de Vries 2009;
Diao, McMillan, and Rodrik 2017). This differentiates the quality of the data from
other sources of employment data, such as ILOSTAT, which compiles data directly
obtained from economy sources without the consistency checks undertaken by
GGDC.1 The GGDC data has two limitations: (ich) limited coverage of low-income
economies; Und (ii) Egypt and Morocco do not report disaggregated employment

1An alternate source of employment data are the labor force surveys (z.B., ILOSTAT). Though labor force
surveys are conducted more frequently than the population census, the data are often not representative in many
developing economies and are sometimes restricted to particular areas, such as urban areas. See Baymul and Sen
(2019) for a discussion of the limitations of ILOSTAT.

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Structural Transformation around the World 7

data for community, sozial, and personal services. I exclude these two economies
from the sample, leaving 39 economies.2

I categorize economies by the different stage of structural transformation
that they are in. The ﬁrst set of economies are those where agriculture is still
the largest sector in terms of the share of employment in the most recent period
verfügbar. In our sample, these economies are Ethiopia, Indien, Kenya, Malawi,
Nigeria, Senegal, Tanzania, and Zambia. These economies are almost all in sub-
Saharan Africa, with India the only exception. These economies are considered
structurally underdeveloped. The next set of economies are those where more
people are employed in the service sector than in agriculture, with agriculture being
the second-largest sector. These economies—Bolivia, Botswana, Brasilien, Kolumbien,
Costa Rica, Ghana, Indonesien, Volksrepublik China, Peru, die Phillipinen,
Südafrika, and Thailand—are called structurally developing economies. Diese
economies span Africa, Asien, and Latin America. The ﬁnal set of economies are
those with more people employed in the manufacturing sector than in agriculture.
The economies in the sample from Africa, Ostasien, and Latin America include
Argentina; Chile; Hongkong, China; Malaysia; Mauritius; Mexiko; the Republic
von Korea; Singapur; Taipeh,China; and Venezuela. This set also includes advanced
market economies from Europe—Denmark, Frankreich, Italien, Japan, die Niederlande,
Spanien, Schweden, and the United Kingdom—as well as the US. These economies are
known as structurally developed. Tisch 1 provides a list of economies by stage of
structural transformation.3

Paths of Structural Transformation

Figur 1 plots the share of employment in each major sector—agriculture,
manufacturing, nonmanufacturing industry, business services, and nonbusiness
services—in total employment over time for all 39 economies. Wie erwartet,
in agriculture falls steadily over time. The share
the share of employment
of manufacturing employment exhibits an inverted U-shaped behavior, wieder
as expected. The share of employment
in nonbusiness services shows a
steady increase. There is virtually no change in the share of employment in
nonmanufacturing industry. The share of employment in business services shows a
sharp increase after the 1990s.

2An additional limitation of the dataset is that it does not differentiate between informal and formal

employment in the manufacturing and service sectors.

3I experimented with an alternate approach to classifying economies by stages of structural transformation
by using the share of employment in agriculture in the last period available as the sorting criteria. Using this
Kriterien, economies are classiﬁed as structurally developed if their share of employment in agriculture is below
10%, structurally developing if their share of employment in agriculture is between 10% Und 50%, and structurally
underdeveloped if their share of employment in agriculture is above 50%. I did not ﬁnd any difference in the ﬁndings
using this criteria of classifying economies in different stages of structural transformation. Note that using the share of
employment in manufacturing instead of agriculture as a way to classify economies is misleading, as manufacturing
employment shares had peaked in many economies by the beginning of the review period.

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8 Asiatischer Entwicklungsbericht

Tisch 1. Stages of Structural Transformation—Economy Classiﬁcation

Structurally Underdeveloped
(8)

Structurally Developing
(12)

Structurally Developed
(19)

Ethiopia
Indien
Kenya
Malawi
Nigeria
Senegal
Tanzania
Zambia

Bolivia
Botswana
Brasilien
Kolumbien
Costa Rica
Ghana
Indonesien
Volksrepublik China
Peru
Philippinen
Südafrika
Thailand

Argentina
Chile
Denmark
Frankreich
Hongkong, China
Italien
Japan
Malaysia
Mauritius
Mexiko
Niederlande
Republik Korea
Singapur
Spanien
Schweden
Taipeh,China
Großbritannien
Vereinigte Staaten
Venezuela

Quelle: Author’s compilation.

Figur 1. Share of Employment by Major Sector, All Economies

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Notiz: Share of employment by sector in total employment.
Quelle: Author’s calculations based on GGDC data.

Structural Transformation around the World 9

Figur 2. Share of Employment by Major Sector, Structurally Developed Economies

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Notiz: Share of employment by sector in total employment.
Quelle: Author’s calculations based on GGDC data.

Figur 2 shows the pattern of structural transformation for structurally
developed economies. The share of employment in agriculture was low to start with
at the beginning of the review period and falls below 10% by the end of the period.
The share of employment in nonbusiness services increases from around 40% Zu
around 60% of total employment. The manufacturing employment share, which had
already peaked for most of these economies prior to 1960, shows a steady decline.
Auffallend, the share of employment in business services rises steadily to the point
where it has almost reached the level of the share of manufacturing employment
by the end of the review period. The share of employment in nonmanufacturing
industry shows no clear trend in the period under consideration.

Figur 3 shows the pattern of structural transformation for structurally
developing economies. There is a remarkable fall in the share of employment in
agriculture from around 60% In 1960 to around 30% In 2010. This is matched by a
corresponding increase in employment in nonbusiness services from just over 20%
to over 40% of total employment. The manufacturing employment share shows
a gradual increase, and the share of employment in business services increases
beginning in the 1990s. There is no perceptible change in the share of employment
in nonmanufacturing industry.

Endlich, Figur 4 shows the pattern of structural

transformation for
structurally underdeveloped economies. A remarkable feature of structural
transformation in these economies is the very slow movement of workers out of

10 Asiatischer Entwicklungsbericht

Figur 3. Share of Employment by Major Sector, Structurally Developing Economies

D
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Notiz: Share of employment by sector in total employment.
Quelle: Author’s calculations based on GGDC data.

Figur 4. Share of Employment by Major Sector, Structurally Underdeveloped Economies

e
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Notiz: Share of employment by sector in total employment.
Quelle: Author’s calculations based on GGDC data.

Structural Transformation around the World 11

Tisch 2. Patterns of Structural Transformation: Employment Shares by Sector (%)

Nicht-

Economy Group

Period

Landwirtschaft

Underdeveloped

Developing

Developed

1960–1979
1980–1999
2000–2012
1960–1979
1980–1999
2000–2012
1960–1979
1980–1999
2000–2012

78.2
73.3
66.4
56.3
42.0
31.1
20.1
10.4
5.9

Manufacturing manufacturing Business business
Services Services

Industry

4.4
4.5
6.2
10.3
11.9
12.0
22.8
20.9
15.8

2.3
2.2
3.2
6.0
7.3
7.5
9.4
8.9
9.0

0.4
0.6
1.0
2.3
3.4
5.3
4.2
7.8
12.1

14.6
19.3
23.1
25.1
35.5
44.1
43.4
52.1
57.2

Notiz: Unweighted averages as percentages of total employment.
Quelle: Author’s calculations based on GGDC data.

agriculture. These workers mostly go to the nonbusiness service sector and not to
manufacturing, which shows no clear increase in employment share. The share of
employment in business services is very low as well. The share of employment in
nonmanufacturing industry shows no clear trend in the period under consideration.
Tisch 2 summarizes the information provided in Figures 1–4. It shows the
very slow movement of workers away from the agriculture sector in structurally
underdeveloped economies: von einem 78% employment share in 1960–1979 to 66%
in 2000–2012. These economies also saw a very slow increase in the share
of employment in manufacturing from 4% in 1960–1979 to 6% in 2000–2012.
In the case of structurally developing economies, the average share of employment
in services overtakes employment in agriculture only in the period 2000–2012.
Trotzdem,
these economies experience a rapid decline in the share of
employment in agriculture from 56% in 1960–1979 to 31% in 2000–2012, sowie
an increase in the share of employment in manufacturing from 10% in 1970–1979 to
12% in 2000–2012. For structurally developed economies, the share of employment
in agriculture was low to start with at 20% in 1960–1979. By the period 2000–2012,
more workers are employed in nonmanufacturing industry in these economies than
in agriculture, while services provide the largest employment share by far at 69%.
Hier, we observe a fall in the share of employment in manufacturing over time.

The share of employment in the ﬁve subsectors that make up the service
sector—business, Transport, trade, government, and personal—also differ between
economy groups as well over time. All services except business services are
classiﬁed as nonbusiness services.4 There are three reasons to make a distinction
between business and nonbusiness services. zuerst, as we will show later in
the paper, the productivity of the business service sector far exceeds that of
the nonbusiness service sector, and is comparable to the productivity of the

4More disaggregated data are available in Baymul and Sen (2019).

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12 Asiatischer Entwicklungsbericht

manufacturing sector. Zweitens, the business service sector includes the more
tradable parts of the service sector (z.B., information technology), während die
nonbusiness sector broadly corresponds to the nontradable service sector. Thirdly,
most of the activity that occurs in the business service sector is in enterprises
that are in the formal sector (z.B., information technology ﬁrms and banks), while
a large part of the activity in the nonbusiness service sector is in the informal
sector—including self-employed or household enterprises in trade, hotels and
restaurants, and personal services (z.B., fruit and vegetable street vendors).5 Für
structurally underdeveloped economies, most of the growth of employment in the
service sector occurs in nonbusiness services rather than business services. Das ist
very different from what is experienced in structurally developing and developed
economies, where the most rapid increase in employment for any particular sector
is observed in the business service sector; for structurally developing economies,
it rises from 2% of total employment in 1960–1979 to 5% in 2000–2012, und für
developed economies, it rises from 4% Zu 12% during the same period (Tisch 2). In
Kontrast, the business service subsector remains a paltry 1% of total employment in
structurally underdeveloped economies during 2000–2012.

To ascertain whether or not the shares of employment in manufacturing,
business services, and nonbusiness services follow a clear trend, I regress the
share of employment in manufacturing on a time trend, averaging the data over
5-year periods. I also add the square of the time trend to account for the fact that
the manufacturing employment share peaks at some point along a country’s path
of economic development. I do the same for business services and nonbusiness
services, except that here I do not add a time trend as there is no clear turning point
in these shares in the data. I ﬁrst run the regressions for all economies and then
by structural economy groups. I estimate these equations using random effects and
report the results in Table 3.

For all economies, manufacturing employment exhibits an inverse U-shaped
behavior with time—the coefﬁcient on the time trend is positive and signiﬁcant,
while the coefﬁcient on the square of the time trend is negative and signiﬁcant,
both at the 1% Ebene. Both business services and nonbusiness services’ shares of
total employment show a clear increase over time for all economies. Jedoch,
the trend analysis by structural economy group shows clear differences in the rate
of change of the shares of employment in manufacturing, business services, Und
nonbusiness services over time across the three economy groups (columns 1, 2, Und
3). Wie erwartet, manufacturing employment’s share of structurally underdeveloped
economies does not exhibit an inverted U-shaped behavior over time—when both
the time trend and its square are included in the regression, both are insigniﬁcant
(column 10). When only the time trend is included, it is positive and statistically

5The only exception here is the government sector where workers are usually in permanent jobs that are

reasonably well paying.

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Structural Transformation around the World 13

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14 Asiatischer Entwicklungsbericht

signiﬁcant, suggesting that there is movement into manufacturing for structurally
underdeveloped economies over time (column 11). Jedoch, as indicated by the
magnitude of the coefﬁcients on the time trend variable, the movement into
manufacturing is the weakest among all three economy groups, conﬁrming what had
been observed in Figures 1–4 (columns 4, 7, Und 11). I also obtain a similar ﬁnding
for the shares of employment of business services and nonbusiness services, Wo
the rate of increase for structurally developing economies is far lower than that for
structurally developed and underdeveloped economies (columns 5, 6, 8, 9, 12, Und
13). Weiter, for structurally underdeveloped economies, the rates of increase of
the manufacturing employment and business employment shares are signiﬁcantly
lower than that for the nonbusiness services employment share (columns 11, 12,
Und 13). Im Gegensatz, for structurally developing economies, the rate of increase in
the manufacturing employment share is higher than that for the business services
employment share.6

To sum up, different paths of structural transformation are observed in the
historical employment data for 39 high-, middle-, and low-income economies. Der
hoch- and middle-income economies—which comprise the structurally developed
and structurally developing set of economies, respectively—have mostly followed
the conventional path of structural transformation in which workers move from
agriculture to manufacturing and services ﬁrst, and then out of manufacturing and
into services. Im Gegensatz, the low-income economies, which are the structurally
underdeveloped economies, exhibit
the slow movement of workers out of
agriculture; where this movement has occurred, it has mostly been to nonbusiness
services rather than to manufacturing. I also observe a clear difference across the
economy groups in terms of within-sector movement into services. While there
has been a distinct movement of workers in structurally developed economies
into business services along with nonbusiness services (und zwar in geringerem Maße
in structurally developing economies), there is very little movement of workers
into business services for structurally underdeveloped economies, with most of
the movement to nonbusiness services. I will show later why this difference in
the movement of workers into business versus nonbusiness services is important
for understanding the long-term drivers of structural transformation and economic
Entwicklung.

IV. Drivers of Structural Transformation

The discussion of the theoretical perspectives on structural transformation
indicated that one of the key drivers of structural
transformation has been
differential productivity growth across sectors. To what extent can we attribute

6The ﬁndings on the different paths of structural transformation in the developing world have also been

observed in other studies such as ADB (2013).

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Structural Transformation around the World 15

Figur 5. Aggregate Productivity

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Quelle: Author’s calculations based on GGDC data.

the patterns of structural transformation observed in section III to differential
productivity growth across sectors? To address this question, I ﬁrst
anschauen
the behavior of sectoral productivity for all economies and then by economy
Gruppe. Beginning with a plot of aggregate labor productivity for the three
economy groups in Figure 5, it is not surprising to see that the aggregate labor
productivity of structurally developed economies is much higher than that for
structurally developing economies, which itself is higher than that for structurally
underdeveloped economies. Außerdem, while aggregate labor productivity
increased steadily for structurally developed economies from the beginning of the
review period until the dip in 2008 due to the global ﬁnancial crisis (and also, to a
lesser extent, for structurally developing economies), there is no sign of an increase
in aggregate productivity for structurally underdeveloped economies.

Figures 6–9 examine the behavior of sectoral productivity ﬁrst for all
economies and then by economy group. For all economies, sectoral productivity
is the highest
in nonmanufacturing industry, manufacturing industry, Und
business services. This is followed by nonbusiness services and then agriculture.
Interessant, real labor productivity in manufacturing industry shows a distinct
behavior of catch-up with nonmanufacturing industry and business services
(Figur 6).

For structurally developed economies, there is a similar pattern with respect
to sectoral productivity, except that the productivity of nonbusiness services is not
very different from that of nonmanufacturing industry, manufacturing industry, Und

16 Asiatischer Entwicklungsbericht

Figur 6. Sectoral Productivity, All Economies

Notiz: Productivity calculated as real value added per worker (unweighted averages).
Quelle: Author’s calculations based on GGDC data.

Figur 7. Sectoral Productivity, Structurally Developed

Notiz: Productivity calculated as real value added per worker (unweighted averages).
Quelle: Author’s calculations based on GGDC data.

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Structural Transformation around the World 17

Figur 8. Sectoral Productivity, Structurally Developing

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Notiz: Productivity calculated as real value added per worker (unweighted averages).
Quelle: Author’s calculations based on GGDC data.

Figur 9. Sectoral Productivity, Structurally Underdeveloped

Notiz: Productivity calculated as real value added per worker (unweighted averages).
Quelle: Author’s calculations based on GGDC data.

18 Asiatischer Entwicklungsbericht

business services (Figur 7). For structurally developing economies, there is not a
similar pattern of behavior with nonbusiness services, which is a less productive
sector than nonmanufacturing industry, manufacturing industry, and business
services among this economy group (Figur 8). For structurally underdeveloped
economies, quite remarkably, we see that manufacturing industry productivity is
not very different than agricultural productivity and, in fact, seems to be converging
to the latter over time. We also see that the levels of productivity in manufacturing
industry and nonbusiness services are almost identical, a surprising ﬁnding given
that a large proportion of nonbusiness services are neither tradable nor produced in
competitive markets as in the case of manufacturing industry (Figur 9).

What do these ﬁndings on sectoral productivity imply for the Duarte and
Restuccia model of structural transformation that was discussed in section II?
Examining the implications of the ﬁndings for the theoretical modeling of structural
transformation, while differential productivity growth across sectors provides
an adequate explanation of structural transformation in structurally developed
and developing economies, it does not do so for structurally underdeveloped
economies. For structurally developed and developing economies, the higher rate of
productivity growth in manufacturing industry compared with nonbusiness services
can explain why there has been a reallocation of workers from manufacturing to
services over time. Jedoch, for structurally underdeveloped economies, we have
already observed that the rate of productivity growth in manufacturing industry is
not very different from that of nonbusiness services, or for that matter, agriculture.
This suggests that the mainstream approaches to structural transformation that are
prevalent in the literature are not particularly useful in understanding contemporary
structural transformation. This point was also made by Rodrik (2016), who shows
via a simple open economy, two-sector model of structural transformation that
differential total factor productivity growth in manufacturing cannot be the culprit
for the “premature deindustrialization” that Rodrik observes for many low-income
economies. In Rodrik’s formulation, the causal factor for the deindustrialization in
developing economies is globalization, whereby developing economies “imported”
deindustrialization from developed economies. The evidence for this claim is not
weak. As Sen (2019) zeigt an, globalization has had both a positive and negative
effect on employment in manufacturing—the ﬁrst by the scale effect and the second
by the labor intensity effect.7

What about the utility-based explanation of structural transformation? Für
structurally developed and developing economies, which have seen very high
rates of economic growth, the high income elasticity of services, and business
services in particular, can explain why employment in these sectors increased with

7Sen (2019) uses disaggregated industry data for 92 developing and transition economies for the period
1970–2010 to show that the impact of globalization on manufacturing employment is positive through the scale and
composition effects, and it is negative through the labor intensity effect.

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Structural Transformation around the World 19

economic growth. Jedoch, for structurally underdeveloped economies, welche haben
not seen sustained economic growth and are mostly low-income economies, Es
is difﬁcult to argue that Engel effects can explain why there has been so much
movement of workers into nonbusiness services right from the start of the process
of economic development. What this suggests is that there needs to be a rethinking
of the theoretical premises behind much of the mainstream approach to structural
transformation and the identiﬁcation of alternate causal mechanisms that can
explain the varieties of structural transformation observed in the developing world.

V. How Well Does the Mainstream Approach Explain Structural Transformation?

I now evaluate the explanatory power of the mainstream approach to
structural transformation by taking a prototype mainstream model—the Duarte and
Restuccia model—to the data. Recall that the model has the following parameters:
A, ¯a, ¯s, B, and ρ. Zusätzlich, to generate the values for labor allocation in
agriculture, manufacturing, and services requires the actual productivity levels from
1960 Zu 2010 in agriculture, manufacturing, and services.

Duarte and Restuccia (2010) ﬁrst calibrate their model to US data for the
period 1956–2004. Their calibration strategy involves selecting parameter values
so that the equilibrium of the model matches the salient features of structural
transformation for the US economy from 1956 Zu 2004. The parameter a is the
share of employment in agriculture in the initial year, the parameter ¯a is the
share of employment in agriculture in the terminal year, the parameter ¯s is the
share of employment in manufacturing in the terminal year, and b is the average
share of employment in manufacturing for the period under consideration; alle
of these parameters are for the US. Duarte and Restuccia (2010) then use this
parameter model to simulate shares of employment in agriculture, manufacturing,
and services for individual economies using actual sectoral productivity data for
these economies. They ﬁnd that their model “reproduces the salient features of
structural transformation and aggregate productivity across economies” (Duarte
and Restuccia 2010, 150). The model replicates basic trends in the agricultural
employment share for all economies,
though it underpredicts the share of
employment in services and overpredicts the share of employment in manufacturing
in less developed economies.

A limitation of Duarte and Restuccia’s (2010) analysis is that their sample
does not include any low-income economies, with the economies in their sample
being either high- or middle- income economies. Darüber hinaus, they do not differentiate
between business and nonbusiness services, Wann, as has been argued in this paper,
these two subsectors have very different proﬁles of productivity.

I now simulate the Duarte and Restuccia model with the sample of 39
economies for the period 1960–2010. I do it by economy group to see how

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20 Asiatischer Entwicklungsbericht

Scenario

Tisch 4. Simulation Scenarios

Parameters Baseline as in
Duarte and
Restuccia (2010);
services =
business services
+ nonbusiness
services

Baseline as in
Duarte and
Restuccia (2010);
services =
nonbusiness
services;
manufacturing +
business services
as one sector

0.01

0.11

0.89

0.01

0.11

0.89

0.04

¯a

¯s

Using actual data
for initial year
and ﬁnal year;
services =
business services
+ nonbusiness
services

Share of agricultural
employment in
2010

Share of agricultural
employment in
1960
Share of

nonbusiness and
business services
employment in
1960
Share of

manufacturing
employment
during the period
1960–2010

Using actual data
for initial year;
services =
nonbusiness
services;
manufacturing +
business services
added together

Share of agricultural
employment in
2010

Share of agricultural
employment in
1960
Share of

nonbusiness
services
employment in
1960
Share of

manufacturing +
business services
employment
during the period
1960–2010
−1.5

−1.5

Quelle: Modiﬁed from Duarte, Margarida, and Diego Restuccia. 2010. “The Role of Structural Transformation in
Aggregate Productivity.” The Quarterly Journal of Economics 125 (1): 129–73.

well the Duarte and Restuccia model does in explaining the paths of structural
transformation that were observed in section III. Tisch 4 shows four simulations
for each economy group. In the ﬁrst scenario, I use the same parameter values as
in the Duarte and Restuccia (2010) calibration exercise and include business and
nonbusiness services in one all-inclusive service sector. In the second scenario,
I group business services with manufacturing as one sector; as has been noted,
the business service sector has a similar productivity proﬁle as the manufacturing
sector, and parts of business services also have similar properties as manufacturing
in terms of externalities and tradability, unter anderen (sehen, Zum Beispiel, Amirapu
and Subramanian 2015). The third and fourth scenarios relax the stringent
assumption in Duarte and Restuccia (2010) of the US being the benchmark
economy for the calibrations. This is important as several economies are quite far
from the US in terms of their structural features. Our third and fourth scenarios
use parameter values that correspond to the average in a particular economy group
for the initial and terminal years. The difference between the two scenarios is
that Scenario 3 groups business and nonbusiness services as one service sector,

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Structural Transformation around the World 21

Figur 10. Scenario 1, Structurally Developed Economies

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La = agricultural employment share, simulation results; Lm = manufacturing employment share, simulation results;
Ls = services employment share, simulation results; (mean) man_agr_share = actual agricultural employment share;
(mean) man_emp_share = actual manufacturing employment share; (mean) serv_emp_share = actual services
employment share.
Quelle: Author’s calculations based on GGDC data.

while Scenario 4 groups manufacturing and business services as one sector and
nonbusiness services as another sector.8

Figuren 10, 11, Und 12 provide the simulations and actual shares of
agriculture, manufacturing, and services for structurally developed, Entwicklung,
and underdeveloped economies for Scenario 1, jeweils. Figuren 13, 14, Und
15 provide the simulations and actual shares of agriculture, manufacturing, Und
services for structurally developed, Entwicklung, and underdeveloped economies
for Scenario 2, jeweils. Figuren 16, 17, Und 18 provide the simulations and
actual shares of agriculture, manufacturing, and services for structurally developed,
Entwicklung, and underdeveloped economies for Scenario 3, jeweils. Figuren 19,
20, Und 21 provide the simulations and actual shares of agriculture, manufacturing,
and services for structurally developed, Entwicklung, and underdeveloped economies
for Scenario 4, jeweils.

Across all four scenarios, the Duarte and Restuccia model predicts actual
employment shares in agriculture, manufacturing, and services in structurally

8While Duarte and Restuccia (2010) include nonmanufacturing industry with manufacturing as one sector, ICH
take the level of employment in nonmanufacturing industry as exogenously given in my simulations. This is done for
two reasons: (ich) the share of employment in mining, which is one important subsector in nonmanufacturing industry,
is not a function of productivity or income elasticities, and depends on whether the economy has mining resources;
Und (ii) both utilities and construction, the other subsectors in nonmanufacturing industry, are very different in their
properties from the manufacturing sector.

22 Asiatischer Entwicklungsbericht

Figur 11. Scenario 1, Structurally Developing Economies

Figur 12. Scenario 1, Structurally Underdeveloped Economies

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Structural Transformation around the World 23

Figur 13. Scenario 2, Structurally Developed Economies

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Figur 14. Scenario 2, Structurally Developing Economies

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24 Asiatischer Entwicklungsbericht

Figur 15. Scenario 2, Structurally Underdeveloped Economies

Figur 16. Scenario 3, Structurally Developed Economies

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Structural Transformation around the World 25

Figur 17. Scenario 3, Structurally Developing Economies

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Figur 18. Scenario 3, Structurally Underdeveloped Economies

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26 Asiatischer Entwicklungsbericht

Figur 19. Scenario 4, Structurally Developed Economies

Figur 20. Scenario 4, Structurally Developing Economies

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Structural Transformation around the World 27

Figur 21. Scenario 4, Structurally Underdeveloped Economies

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developed economies well, as may be expected. Jedoch, there are systematic
errors in prediction across all four scenarios for structurally developing and
underdeveloped economies. The Duarte and Restuccia model overpredicts the
share of employment in services and underpredicts the share of employment in
agriculture, particularly for structurally underdeveloped economies. Zum Beispiel,
the percentage difference between the actual employment share in services and
its predicted share is 76% for structurally developing economies and 286% für
structurally underdeveloped economies. Im Gegensatz, the difference is a paltry 5%
for structurally developed economies.

Across all four scenarios, there are clear differences in how the model does
in explaining actual employment shares, especially for structurally developing and
underdeveloped economies. For structurally underdeveloped economies, the model
overpredicts the services employment share by 286% Und 295% for Scenarios 1
Und 2, jeweils. For Scenarios 3 Und 4, the model underpredicts the services
employment share by 139% Und 136%, jeweils, and generates a negative
employment share for services. This suggests that the Duarte and Restuccia model
can provide a realistic explanation of structural transformation for rich economies
but not for poor economies. While more realistic versions of the model may be
able to generate simulations that are closer to the actual employment shares, ein
important reason behind the model’s inability to capture structural transformation in

28 Asiatischer Entwicklungsbericht

low-income economies is that relative productivity changes are not as key
a determinant of labor reallocation in poor economies as they are for rich
economies. daher, it is necessary to rethink mainstream approaches to structural
transformation that put a great deal of weight on sectoral productivity growth and
income effects.9

VI. Conclusions and Policy Implications

The conventional view of structural transformation is informed by three
stylized facts of economic development: (ich) all economies exhibit declining
employment in agriculture; (ii) economies at an early stage of the process of
structural transformation exhibit a hump-shaped share of employment in industry,
whereas this share is decreasing for economies at a more advanced stage; Und (iii)
all economies exhibit an increasing share of employment in services. In diesem Papier, ICH
show that this presumed path of structural transformation may no longer be the route
to economic development for low-income economies. Classifying economies as
either structurally developed, Entwicklung, or underdeveloped, I observe a different
path of structural transformation in structurally underdeveloped economies, Wo
workers are moving directly from agriculture to nonbusiness services, which as a
sector does not have the same productivity gains as manufacturing. I also ﬁnd that a
prototype mainstream model does a poor job of replicating the patterns of structural
transformation observed in low-income economies. This suggests that there needs
to be a rethinking of the theoretical premises behind much of the mainstream
approach to structural transformation and the identiﬁcation of alternate causal
mechanisms to explain the different types of structural transformation observed in
the developing world.

What implications do these results have for policy? Clearly, for many of the
middle-income economies in the sample, several of which are in Asia, productivity
growth in manufacturing relative to nonbusiness services remains the key driver
for the reallocation of workers from manufacturing to services. Weiter, for these
economies, the Engel effects become important as per capita income increases,
leading to an increase in the employment share of the highly productive business
service sector over time. Im Gegensatz, for structurally underdeveloped economies, Die

9An alternate mainstream approach that emphasizes income effects instead of relative productivity
differentials as the key explanatory variable for structural transformation is provided by Comin, Lashkari, Und
Mestieri (2018). This approach assumes nonhomothetic preferences and shows that income effects account for
75% of the observed patterns of structural change. Jedoch, a limitation of this approach is that it essentially sees
structural transformation as a consequence of economic development rather than a cause. While income effects have
a role to play in explaining the hump-shaped nature of the manufacturing employment share, and the rapid growth
in the services employment share in middle- and high-income economies, it cannot in itself explain why low-income
economies have not been able to follow the path of structural transformation observed in middle- and high-income
economies, where the movement of workers into manufacturing was the primary driver of growth at the early and
middle stages of economic development.

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Structural Transformation around the World 29

low productivity of the manufacturing sector provides a more challenging setting
for both economic growth and structural transformation. For these low-income
economies, whatever limited possibilities that may exist for manufacturing-driven
strukturell
transformation must be focused on policies that can increase the
productivity of the manufacturing sector, as well as on exploring options for growth
that are based on the nonbusiness service sector, which remains the major sector of
employment outside agriculture for structurally underdeveloped economies.

Verweise

Amirapu, Amit, and Arvind Subramanian. 2015. “Manufacturing or Services? The Indian
Illustration of a Development Dilemma.” Centre for Global Development Working Paper
NEIN. 409.

Asiatische Entwicklungsbank (ADB). 2013. “Asia’s Economic Transformation.” Key Indicators
for Asia and the Paciﬁc 2013. https://www.adb.org/sites/default/ﬁles/publication/30358
/ki2013-special-chapter.pdf.

Baymul, Cinar, and Kunal Sen. 2019. “What Do We Know about the Relationship between

Structural Transformation and Inequality?” Asian Development Review 36 (1): 136–67.

Chenery, Hollis, and Moshe Syrquin. 1975. Patterns of Development, 1950–1970. Delhi: Oxford

Universitätsverlag.

Clark, Colin. 1940. Conditions of Economic Progress. London: Macmillan.
Comin, Diego, Danial Lashkari, and Marti Mestieri. 2018. “Structural Change with Long Run

Income and Price Effects.” Mimeo.

Dabla-Norris, Era, Alun Thomas, Rodrigo Al Garcia-Verdu, and Yingyuan Chen. 2013.
“Benchmarking Structural Transformation across the World.” IMF Working Paper No.
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Appendix

The Groningen Growth and Development Centre’s database provides annual
employment data for 10 different sectors in 41 economies. The time spans for
available data vary between economies; Jedoch, most economies in the database
have observations from 1960 Zu 2012. Table A1 lists the 10 sectors with their
respective ISIC Revision 3.1 codes and deﬁnitions.

ISIC 3.1 Code
A+B
C
D
E
F
G+H

Table A1. Description of Sectors

Sector Name

Description

Landwirtschaft
Mining
Manufacturing
Utilities
Construction
Trade services

Landwirtschaft, hunting and forestry, and ﬁshing
Mining and quarrying
Manufacturing
Electricity, Gas, and water supply
Construction
Wholesale and retail trade; repair of motor vehicles,

motorcycles, and personal and household goods; hotels
and restaurants

ICH
J+K

Transport services
Business services

Transport, storage, and communications
Financial intermediation, renting, and business activities

(excluding owner-occupied rents)

L, M, N

Government services

Public administration and defense, Ausbildung, Gesundheit, Und

social work

Ö, P

Personal services

Other community, social and personal service activities,

and activities of private households

ISIC = International Standard Industrial Classiﬁcation of All Economic Activities.
Quelle: Timmer, Marcel, Gaaitzen de Vries, and Klaas de Vries. 2015. “Patterns of Structural Change in Developing
Countries.” In Routledge Handbook of Industry and Development, edited by John Weiss and Michael Tribe, 65–83.
London: Routledge.

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Structural Transformation around the World 31

Agriculture is the primary sector. The secondary industry sector can be
divided into two groups—manufacturing industry and nonmanufacturing industry;
the latter comprises mining, utilities, and construction. The tertiary service sector
consists of trade, Transport, business, government, and personal services. The ISIC
classiﬁcation of manufacturing includes primary processed products. Employment
in each category is deﬁned as all persons engaged in labor, and hence encompasses
self-employed and family workers both in the formal and informal sectors.

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