COVER STORY • Mid-Term Prospects for the Global Economy — Where Is It Heading in the Midst of Structural Change & Geopolitical Crisis? • 3

Structural Change &Inequality: Evidence
from Asia

By Rudra Prosad Roy & Saikat Sinha Roy

Heterogeneity in Within-country Inequality AcrossCountries: a Discussion
Through adopting Sustainable Development Goals (SDGs)
countries have targeted to reduce income inequality within andacross countries. Even though relative global inequality is found tohave remained stable, or at best declined (Miguel Nino-Zarazua,
Laurence Roope and Finn Tarp, “Global Inequality: Relatively Lower,Absolutely Higher”, Review of Income and Wealth, Aug. 15, 2016),
there is wide heterogeneity in within-country inequality across
CHART 1Author
Rudra Prosad Roycountries and regions (Stephan Klasen, Nathalie Scholl, Rahul
Lahoti, Sophie Ochmann and Sebastian Vollmer, “Inequality —Worldwide Trends and Current Debates”, Georg-August-Universität
Göttingen Discussion Paper No. 209, 2016). Reduction of income
inequality is key to long-term growth and sustenance not only byencouraging investment in human capital, but also ensuring
reduction in the concentration of economic and political power in thehands of a few, who then prevent redistribution of income andwealth. (A detailed discussion of the effects of income inequality on
economic growth can be found in Rudra Prosad Roy and Saikat

Change in average income inequality between 1990s & 2000s-40.35

54.10

Source: Authors’ own calculation on the basis of data from World Development Indicators

14 Japan SPOTLIGHT • January / February 2018

Author
Saikat Sinha RoyCOVER STORY 3

Yemen

VietnamTurkeyUzbekistan

ThailandTajikistan

Slovakia

Sri LankaPhilippines

Russian Federation

Nepal

Pakistan

Maldives

Mongolia

LaosMalaysia

Kyrgyzstan

JordanKazakhstan

Iran

Israel

India

Indonesia

China

Cambodia

Australia

Bangladesh

CHART 2Sinha Roy, “Does Inequality Dampen
Change in average income inequality between 1990s
Economic Growth? A Cross-Countr y& 2000s in Asia-Pacific countries
Analysis”, in Chandan Roy (ed.),I n t e r n a t i o n a l Tr a d e a n d I n c l u s i v e
Development: Emerging Issues andEnlarging Debates, New Delhi: New
Academic Publishers, 2017.)
Within-country income inequality is often
believed to be associated with the structuraltransformation of that economy. Classically,
structural change in an economy takes
place over time with a rise in the relative
share of the manufacturing sector followed
by a rise in the relative share of the services
sector. The idea of a nexus between
structural transformation and income
inequality follows from seminal papers by
Simon Kuznets (“Economic Growth andIncome Inequality”, American Economic
Gini 1990
Review 45, 1955, and “Quantitative Aspects
Gini 2000
of the Economic Growth of Nations: VIII.
Note: The vertical axis measures log GINI for the two decades. However, the axis is not mapped to scale; the size of theDistribution of Income by Size”, Economic
bubble indicates the extent of income inequality for each country during each period.
Development and Cultural Change 12,
Source: Authors’ own calculation on the basis of data from World Development Indicators
1963). It is often argued that structural
their resources towards more skill- and technology-based activities
transformation in the long run creates more job opportunities andincluding manufacturing and services. In the more recent period,
leads to a more equal society. Kuznets, on the other hand,most countries including emerging market economies have
hypothesized an inverted U-shaped relationship between economictransformed towards more services production. During the same
growth and income inequality.
time economies have also experienced changes in income inequality.
In this context, it is important to observe whether structural
Over the last two and a half decades, income inequality has
transformation reduces income inequality. Prior to discussing theincreased in many countries. Income inequality increased in Africa,
linkage between structural transformation and income inequality, it isfollowed by Latin American and Asian countries. Changes in average
important to understand the pattern of change of income inequality
inequality between the 1990s and 2000s across countries can beover time across countries.
seen in Chart 1. Large changes in inequality are observed in Asian
Structural Change & Income Inequality:
Emerging Market Economies (EMEs). Chart 2 shows changes inSome Cross-Country Evidence
average income inequality in Asia and Pacific countries between the1990s and 2000s. On account of lack of comparable data, the data
While most developed countries experienced structural
on Japan cannot be presented here. It can be seen that in sometransformation in the 19th and early 20th centuries, some other
Asian countries average inequality, measured in terms of averagecountries, including Japan and several developing nations,
Gini coefficient, has increased between the 1990s and 2000s; and inexperienced structural transformation in the mid and late 20thsome other countries it has fallen.
c e n t u r y. F o r i n s t a n c e , J a p a n e x p e r i e n c e d “ a n e c o n o m i c
For instance, between the 1990s and 2000s, when Chinatransformation … in the high-growth years from 1953 to 1973. Inwitnessed a quantum increase in inequality, India and Indonesia
the space of two decades a largely agricultural nation became theexperienced only a moderate increase. While China showed almost aworld’s largest exporter of steel and automobiles…” (Paul Krugman,
15% increase in inequality during the last two decades, the Gini
The Return of Depression Economics and the Crisis of 2008,
coefficient for India increased from 30.8 to 33.6. The increase/London: Penguin, 2008; p.57). Economies that were primarily
decline in income inequality is irrespective of the size of thedependent on agriculture and other primary activities have shiftedeconomy. Small countries like Jordan, Kazakhstan, Malaysia,
Japan SPOTLIGHT • January / February 201815

COVER STORY 3

CHART 3

Relationship between structural change & inequality
Low Income

Lower Middle Income

Upper Middle Income

20406080

20406080

High Income

010203040010203040

GDP Share of manufacturing sector
Graphs by groupGini

Fitted values

Source: Authors’ own calculation on the basis of data from World Development Indicators

Pakistan, and the Philippines, and large countries like the RussianFederation and Thailand, showed a decline in inequality, whereas
Bangladesh and Sri Lanka experienced an increase in inequality. The
inequality measured in terms of the Gini coefficient for Bangladesh
increased from 30.5 to 32.9.
Among ASEAN countries, in Indonesia, Laos and Vietnam, the Gini
coefficient increased from 29.37 to 34.3, from 32.7 to 34.7, and from35.6 to 36.8, respectively. Some other ASEAN countries like thePhilippines and Thailand showed a downward trend in inequality
during this period of time. In Australia as well, inequality increased
marginally. In the 1990s, the average inequality measured in terms of
the Gini coefficient was 33.7, and in the 2000s it increased to 34.1.
Most of the countries have undergone rapid structural change
towards services during this period. On the whole, inequality isfound to have increased mostly in countries that underwent
structural transformation in these two decades. Simultaneous
occurrence of structural change and income inequality tempted
researchers to study the causal relationship, if any, between the two.

16 Japan SPOTLIGHT • January / February 2018

Globalization, Structural Transformation & Income
Inequality
In our study “Structural Change, Trade, and Inequality: Some
Cross-Country Evidence”, (Asian Development Bank Institute (ADBI)
Working Paper No. 763, 2017) we empirically threw some light on
the proposition linking structural transformation and income
inequality. With a large number of both developed and developing
countries during the period 1991-2014, it has been shown that theprocess of structural transformation has increased incomeinequality. It has been found that, across countries of different
regions, structural transformation has increased income inequality.
This can also be seen graphically from Charts 3 & 4. From Chart 3 itcan be seen that for high-income and upper middle-income
countries, structural change (measured in terms of share of the
manufacturing sector) and inequality are negatively related. On theother hand, for lower middle-income and low-income countries, they
are positively related. The relationship marginally varies whenstructural change is measured in terms of share of the services
sector (Chart 4). It is found, using a regression exercise, that if theGDP share of the manufacturing sector increases by 1%, it causes a3% increase in income inequality. On the other hand, if the share ofCOVER STORY 3

CHART 4

Relationship between structural change & inequality
LowLower Middle

Upper Middle

2040608020406080

High

20406080

20406080

GDP Share of Service
Graphs by group

Gini

Fitted values

Source: Authors’ own calculation on the basis of data from World Development Indicators.

the services increases by 1%, income inequality is found to increaseby 10%.
However, this pattern is found to vary across regions. For
example, if the GDP share of the services sector in Asia increases by1%, income inequality in Asia increases by 8.53%. While structuraltransformation measured in terms of the share of manufacturing is
not found to have any significant impact on inequality in Asia, theimpact is positive and significant when structural transformation ismeasured in terms of the share of services. This result is notcounter-intuitive: as Asian countries have moved towards productionof services during the 1990s and 2000s, inequality is found to havebeen exacerbated in these countries. The wage gap between skilled
and unskilled labor could be one of the key factors explaining thisobserved increase in within-country inequality in Asia following
structural transformation towards services.
The argument runs as follows: as the economy relies more on
modern sectors, where productivity is higher, demand for highskilled labor increases and that of low-skilled labor decreases,
thereby increasing income inequality. Therefore, as resources
including labor move from less productive sectors (agriculture) tomore productive sectors (manufacturing and services), income
inequality increases. Globalization, in particular trade and FDI, andstructural transformation accelerate this process of a widening wage
gap between skilled and unskilled labor in developed and mostly indeveloping countries (Supplement to the International Labour
Organization’s Global Wage Report 2014-15: Wages in Asia and thePacific : Dynamic but Uneven Progress).
On the whole, in the short and medium term, structuraltransformation causes rising wage inequality and thus a rise inincome inequality. These findings highlight the need for the bottom
deciles of income earners in Asian countries to benefit from theprocess of structural transformation. Trade, FDI and infrastructuraldevelopment could be the possible policy targets.

Rudra Prosad Roy is a research fellow at the Department of Economics at
Jadavpur University, Kolkata. He has an M.Sc in applied economics fromPresidency College, Kolkata, and an M.Phil in economics from Jadavpur
University. He has several international publications to his credit.
Dr. Saikat Sinha Roy is professor of economics at Jadavpur University,Kolkata. His areas of academic interest include applied trade modelling, tradeand development, open economy macroeconomics, and issues relating toemerging market economies (EMEs). His work has been published in various
national and international journals and edited volumes. He recently co-edited abook titled International Trade and International Finance: Explorations ofContemporary Issues (Springer, India, 2016).

Japan SPOTLIGHT • January / February 201817