Download A survey of recent trends in trade, growth and employment

Increased Economic Openness and the interface between trade, technology and
employment: Some issues vis-a-vis size and level of development in case of India and China
Shipra Nigam
The impact of increased integration through trade on income and employment within the
developing world has been the subject of widespread debate during the past few decades.
While problems that arose in case of the differing growth trajectories of Latin American
and African countries have been widely acknowledged and affected subsequent policy
debates as well as initiatives, there seems to be an emerging consensus that growth rates
have actually risen in case of most Asian countries that have witnessed trade and
economic liberalisation, with China and India being now widely posited as the new
‘success stories’ of contemporary globalisation.
High and sustained rates of growth of aggregate and per capita national income, the
phenomenal growth in trade and investment flows and the absence of major financial
crises are all invoked in characterizing this success. These in turn are often viewed as the
consequences of “far-sighted”, cautious yet comprehensive programmes of global
economic integration and domestic deregulation, as well as sound macroeconomic
management in case of both these countries ( especially in case of China). However,
where the contentious issue of the impact of these changes on nature and level of
employment in these countries is concerned, the consensus is far from clear.
The impact of this rapid growth and trade integration on the growth and structure of
employment becomes crucial for these labour abundant developing countries facing
major challenges in the area of employment. This paper intends to map the interface
between rising trade, growth and employment in an era of increased economic
integration1 while focusing on its impact on the labour markets of these Asian giants.
There are broader issues of alternative macroeconomic adjustment policies, the
movement of finance capital, exchange rate managements etc which would have
implications for global and domestic growth and employment. However the focus here is
on rising global trade integration and changes in policy regimes leading to trade and
1
It is important to clarify over here that the basic emphasis of the proposed study is on the impact of trade
rather than that of trade liberalization on employment through its impact on technological dynamism. This
is a broader question which focuses on changes in a country’s integration with the global economy rather
than just on its trade policy, although of course trade policy is a key factor in determining the impact of
trade on employment.
investment liberalization alongwith correlated changes in technological dynamism which
could have a significant impact on the output and employment growth patterns of these
large developing countries.
Accordingly this paper is divided into three major sections. The first section explores
the theoretical issues involved where the interface between rising trade integration,
growth and employment is concerned in an era of increased economic openness. The
second section carries out a survey of empirical trends in trade integration and changing
patterns of output and employment in the post liberalization era in case of India and
China focusing specifically on the last one and a half decades. The analysis is carried out
at various levels of aggregation (macroeconomic, sectoral and 3 digit Industrial
classifications) and also involves estimation of point elasticities. The concluding section
summarises the trends in context of the theoretical discussion carried out in the first
section. While marshalling available evidence on trade, growth and employment, the
paper a establishes that the "comparative advantage" notion of greater trade absorbing
labour or raising wages does not work .Further, it suggests the existence of structural
processes emerging in the context of contemporary global economic integration, which as
a result of mutually reinforcing influences (export orientation and international
technological diffusion) keep pushing large labour abundant developing economies in a
direction which involve potential underutilization of their labour reserves. It concludes
with possible ways on proceeding with further analysis to explore the possibilities of this
hypothesis.
India and China – Large developing countries and the interface between trade,
technology and employment
The debate on the effects of increased economic openness and trade liberalisation on
employment, leading either to a virtuous process of growth or forms of “jobless growth’
in the developing world is an old one which has acquired new dimensions in
contemporary literature on growth and development. Given the importance of overall
employment as a crucial indicator of economic welfare, especially where a large part of
the developing world characterised by the absence of any kind of social security
measures is concerned, the debate has spanned several important issues. In particular, the
impact of trade liberalization on the growth of output and employment and hence its
impact on poverty, wage and income distribution and the nature of employment within
the developing world has been widely contested in the literature.
The complex dynamics arising out of the interface between increased trade
integration, technology and employment for developing economies, I would argue,
devolve crucially on the questions of size and level of development of the economy
concerned and hence becomes especially important in the context of developing countries
like India and China with their large domestic product and labour markets and potential
for unleashing the process of technological dynamism on a large scale. Given that both
these countries have experienced rapid economic integration and growth in output but
with important differences in the degree and extent of structural transformation, they also
provide excellent grounds for a study from a comparative perspective.
The tenets of the standard theory based on the principle of comparative advantage
predict several positive outcomes of trade liberalization for developing countries typically
found to be abundant in unskilled labour. These include increased efficiency of resource
allocation, higher growth alongwith an increase in employment opportunities and wages
for unskilled labour, and a reduction in wage and income inequalities. The common a
priori assumption is that in developing countries, given their labour endowments, the
unskilled labour intensity of export oriented industries is higher than that of importcompeting sectors so that ultimately trade liberalization should bring about an increase in
overall labour demand2, especially for unskilled labour.
The assumptions3 which go behind establishing these propositions have been widely
criticised for their unrealistic nature in a world characterised by uncertainty, increasing
returns to scale and market imperfections. Subsequent models4 within mainstream theory
have attempted to drop most of these assumptions with differing implications for patterns
of and gains from trade. At the same time, a rich literature has also developed within
2
Here overall demand is used in the production function sense of a lower demand for K/L rather than in the
Keynesian sense.
3
These include constant returns to scale, perfect competition, strong factor intensity.
4
These include those developed by Findlay (1978), Parentte and Prescott(1998), Prescott (2000), Krugman
(1995).
economic heterodoxy,5 again with varying implications in terms of predicted outcomes
on output and employment within the developing world. Besides its theoretical critique of
the logical consistency of the premises and real world relevance of the assumptions
employed in standard models which have their roots in HO and SS theory, it has also
been pointed out in this literature that available empirical evidence fails to conclusively
establish the basic propositions of mainstream theory.
During the last 20 years, a generalized reduction in the aggregate demand for labour
paralleled the developments in international trade (See ILO (1995, 1998-1999, 2005, for
an overview). The unemployment rate has been growing on average across countries
alongwith a falling share of wage income in total income and rising wage and income
inequalities.6 To the extent this phenomenon has became increasingly evident in case of
labour abundant developing economies as well as the developed world, it necessitates a
search for alternative explanations. In this context, the role of technological diffusion
accompanying increased economic integration in determining the level and nature of
employment conditions has served as an important point of departure in explaining
divergence in observed patterns of growth and employment accompanying increased
trade integration from those expected on the basis of a conventional understanding of the
principle of comparative advantage. Given the importance of capital and skill biased
transfers of technologies developed in advanced capitalist countries in case of developing
nations, its implications for conditions prevailing in their labour markets have again been
widely discussed in existing literature. Once one gets into the realm of the possible
interfaces between trade and technology and its consequent implications for
employment , the issue can be approached from two alternative perspectives which are
however not mutually exclusive.
The age old debate on appropriateness of technology transfers developed in the
advanced capitalist nations and dictated by the need for saving labour has been an
important factor in influencing theoretical and policy analysis on the apposite trade and
investment policies to be pursued by developing nations. The debate has also devolved on
the questions of feasibility/possibilities of utilising existing repository of scientific
5
See Patnaik (2006),Wood (1994), Feenstra and Hanson (1995), Rodrik (1997)amongst others.
6
Revenga, 1992, 1995; Wood, 1997; Robbins, 1996; UNCTAD, 1997, Cornia (2006)
knowledge perse7 which could be adapted to develop suitable non mechanised methods
of production which are modern and technically efficient in case of developing countries
as opposed to transfers of capital intensive techniques developed in advanced capitalist
countries. Where some of the earlier discussions8 are concerned,
Salter’s (1966)
contention in favour of the former was critiqued by Rosenberg (1976) and Findlay (1978)
on grounds of non feasibility in terms of escalating transfer costs and skill requirements
involved in such adaptive transfers suited to factor endowments of concerned countries
vis-à-vis merely transfers of available capital intensive techniques where international
technological diffusion arising out of increased trade and FDI flows are concerned.
However, significantly, Findlay here goes on to analyse the possibility of development of
alternative growth trajectories based on generation of “intermediate technologies” for
large developing nations like India and China as compared to smaller ones with similar
relative factor endowments due to potential for higher gains that accrue with larger
volumes of demand.
Recently, it’s been pointed out that arguments based on non feasibility of transfers of
technological knowledge -that is increasingly disembodied, codified, and global and
could unleash a technological dynamism of its own- loose their significance given that
virtually costless transfers
have been made possible with the development of
sophisticated software and IT related services. However, empirical analysis has shown
that non-codified knowledge continues to be important for understanding patterns in the
creation and diffusion of knowledge (von Hippel 1994, Teece 1977) and to that extent
role of international economic activity in determining overall technological diffusion
continues to be important.
What is more important to note in this regard is that while these arguments devolve on
merely the feasibility of differing kinds of technological transfers, a host of other factors
are important in determining the actual nature and extent of diffusion accompanying
increased economic openness, such as the pattern of trade and production that a country
finds itself embarking upon consequent to its integration with the global economy. As
7
8
Referred to as “book of blueprints” by Joan Robinson in her discussions on production functions.
Salter (1966), Rosenberg (1976), Findlay (1978).
such the structural implications for changes in the labour market conditions of these
countries need to be more fully explored.
The new growth theorists9 for instance emphasise the effects of trade on diffusion of
technical innovations, changing the technological level of the less advanced country. The
consequent reallocation is biased in favour of skilled labour, since the technology being
used was developed in the country where this factor is abundant as a result of which the
structure of labour demand tends to move in favour of skilled labour. This leads to an
increase in the returns to human capital manifested in increased inequality and
employment effects due to skill shortages. Given that the mean elasticity of substitution
of skilled labour for unskilled labour is larger in developed than in developing countries
given the larger supply of skilled labour in the former10, the effects are more intensely felt
in case of the latter countries.
However, it can be pointed out over here in view of the above discussion that
technology transfer to developing nations essentially involves a process of ‘productive
implementation’ as distinguished from ‘innovation’ which do not guarantee dynamic
change in the technological level of production in developing nations. To that extent, any
skill shortages that occur are bound to be transitional as labour markets adjust to changes
in the structure of labour demand, but with the period of transition varying according to
characteristic features of the existing labour market conditions.
Rising trade integration greatly facilitated by technological change has segmented
production processes and allowed for the locational breakup of segments of individual
processes with differing types of skill requirement alongwith associated geographical
separation of different parts of the production process and increase in intra-industry trade
(Feenstra 1998).
9
Available evidence11 also suggests that the relative importance of
Grossman and Helpman (1991), Parente and Prescott (1994) and Romer (1990) etc
10
This is meant in the sense of existence of a larger pool of labour with basic skills suited to technological
developments existing in case of the developed south besides a larger resource base and greater facility of
converting unskilled to skilled labour, e.g. education and training facilities etc.
11
See Coe, Helpman, and Hoffmaister (1997),Connolly (1998), and Mayer (2001) Keller (2001). However
primarily due to the much greater difficulty in obtaining comparable and high-quality data for less
developed countries, there is a relative scarcity of results in this regard.
foreign sources for productivity growth is increasing in both
size and level of
development and some estimates put the relative importance of foreign technology for
developing countries at almost 90% and even higher. At the same time, there is no
indication that international learning is inevitable or automatic, merely a function of what
Gerschenkron (1962) has called economic backwardness. Instead, differential learning
effects seem to be in part explained by the extent and the way in which firms of different
countries engage in international economic activities.
The questions of the size of the country involved become important not only in terms of
the scope and level of technological dynamism that can be unleashed and the possibilities
of embarking on alternative growth trajectories but also in terms of the stakes involved
given the existence of large labour reserves in such economies. This could be seen in
light of the hypothesis recently advanced by Prabhat Patnaik (2006) on the technologyemployment-growth interface that occurs in developing countries as a result of increased
trade openness in an era of globalised finance accompanied by increased restrictions on
the capacity of the state to intervene. According to him, the “opening up” of an
underdeveloped economy to trade and capital flows implies that the pace of technological
and structural change within the economy gets linked to what prevails in the advanced
capitalist world. This implies an increase in the rate of growth of labour productivity
compared to what prevailed under dirigisme. At the same time the rate of GDP growth
becomes dependent upon the rate of growth of exports, which, unless the underdeveloped
countries erode each other’s market share, gets linked to the rate of growth of world
trade, which is essentially outside the country’s control. If the rate of growth of labour
demand, which is the result of these two phenomena, falls short of the rate of growth of
the work force, then the ratio of labour force to work-force increases, which means a
constancy of the wage rate of workers at the subsistence level and increase in absolute
poverty for a larger section of the work force. This then is put forward as an explanation
of the “peculiar trap” in which developing countries find themselves where rising
unemployment occurs without commensurate rise in subsistence wage levels as would be
expected on lines of conventional wisdom.
A proposition which clearly emerges from the above discussion is that in
contemporary globalization, there are important issues regarding the patterns of revealed
as well as consequential comparative advantage in trade and its implications for the
nature and level of technological dynamism in developing nations caught at specific ends
of the global value added chains which would determine their particular growth and
employment trajectory. These become especially crucial in case of China and India given
the sheer size, development potential as well as the vast labour reserves of these
economies. In what follows, a survey of the recent trends post economic liberalisation in
both these countries is undertaken to map the interface between trade, growth and
employment.
A survey of recent trends in trade, growth and employment
As far as China is concerned, severe limitations on data availability and comparability
during pre and post reform periods exist, as a result of which several studies scrutinized
available statistical data12to arrive at more acceptable estimates of output and
employment which can be used. The basic data sources include China’s statistical
yearbooks, National Accounting Statistics and household surveys. In case of India too,
there exist severe various data limitations where informal and rural employment are
concerned. This study is going to employ a combination of international data sources
such as those provided by the World Bank and the UN for comparative purposes as well
as available studies based on national estimates in case of both the countries. In what
follows, descriptive statistics on trade and production followed by calculation of
employment elasticities following standard methodology used by ILO/ UNDP are
presented.
Rising trade integration, interdependence and growing trade in goods and services
12
See, for example, Knight and Xue (2004) and Giles, Park and Zhang (2005). The few studies with a
broader focus include Fang (2004), Rawski (2002) and Brooks and Tao (2003).
Overall indicators of the extent of trade integration in terms of both the domestic
economy as measured by the share of exports and imports in GDP as well as the global
economy as measured by the share of a country’s exports and imports in global exports
and imports show that although both countries have become increasingly integrated with
the World Economy, China has gone much farther, including the fact that China started
the process of integration at least a decade earlier. Thus with twice as much or more
share of exports and imports in GDP, more than seven times (five times) the share in
World merchandise exports (imports), the share of international trade (exports and
imports of good and services) in its GDP at 66% is very high for an economy of China’s
continental size and level of per capita income13.
Table 1
Measures of Integration with the World Economy
Percent of Total
1983
1994
2004
Share in GDP of Exports of Goods
China
n.a.
18 1
34 2
and Services
India
n.a.
71
14 2
Share in GDP of Imports of Goods
China
n.a.
14 1
32 2
and Services
India
n.a.
91
16 2
Country Share in World Exports of
China
1.2
2.8
6.7
Merchandise
India
0.5
0.6
0.8
Country Share in World Imports of
China
1.1
2.6
6.1
Merchandise
India
0.7
0.6
1.1
Country Share in World Exports of
China
n.a.
1.6
2.9
13
There could be some overestimation over due to problems with national income accounting and revised
estimates being carried out might lower this figure.
Commercial Services
India
n.a.
0.6
1.9
Country Share in World Imports of
China
n.a.
1.5
3.4
Commercial Services
India
n.a.
0.8
2.0
1
Shares are for 1990
2
Shares are for 2003. With newly revised GDP data for China showing higher levels of GDP, the
shares would be somewhat lower.
Sources: T.N.Srinivasan (2006), China,
India and the World Economy.
During the period 1990-2003 while the share of exports and imports in India’s GDP
almost doubled, the increase in share in its World merchandise exports, proportionately,
was far less. However given its success in the IT service sector, India’s share in World
exports of commercial services tripled during the same period. It would seem that in
India’s case, with the possible exception of services the effect of greater integration is
largely one-way and domestic, in the sense of its influencing the rate of GDP growth and
the share of trade in domestic GDP, rather than India’s more rapid GDP growth
influencing global GDP growth significantly (table 1). Both countries have witnessed a
significant rise in the average annual growth rates of exports and imports during the 90’s
which rose further during 2000-2006 (table 3) with the growth rates again being higher
for China. While China has had a continuous trade surplus, India experienced a
continuous albeit declining trade deficit until very recently.
Table 2
Share in
Share in GDP of
Growth Rate of
Share in Growth
Share in Growth
Global GDP
Low and Middle
GDP (%)
of World GDP
Rate of Low and
(%)
Income Countries
(%)
Middle Income
(%)
Countries (%)
1990
2003
1990
2003
1980-90
1990-03
1980-90
1990-03
1980-90
1980-03
CHINA
1.6
3.89
8.87
19. 9
10.3
9.6
5.1
13.3
30.5
51.6
INDIA
1.5
1.64
7.92
8.4
5.7
5.9
2.5
3.5
15.0
13.4
CHINA AND
3.1
5.53
16.79
28.3
7.6
16.8
45.5
INDIA
SOURCE: T.N.Srinivasan (2006), ‘China,
India and the World Economy.’
Table 3
Exports of
goods and
services
(Average annual
% growth)
China
19801990
1991142000
20002006
India
Imports of
goods and
services
(Average
annual %
growth)
China
India
Growth rate of
GDP
China
India
6.01
5.93
8.14
6.55
9.21
5.89
14.46
13.03
16.92
14.80
10.45
6.03
24.84
16.94
20.24
12.32
9.35
6.49
Source: World Development Indicators 2006.
The change in structure of growth in trade has occurred at three levels, first within
overall exports/imports between goods and services, second, within merchandise exports
between primary products and manufactures and, third, within manufacturing between
products of industries with varying labour intensity and levels of technology.
Between goods and services, the biggest change has taken place in Indian exports.
While both India and China have experienced higher service export growth rates, the
emergence particularly of “outsourced” IT services from India has led to a structural shift
with an increased the share of service exports in total exports from 20% in 1990 to 27.4%
by 2003. In case of China, the share of goods exports has been rising with the share of
14
65.0
services exports in total exports falling steadily from 12% in 1982 to 7.66% in 1990 to
4.67% in 2003 (Table 4 and 5).
Table 4
India
80’s
Merchandise
exports growth
rate
8.1
Service exports
growth rate
Merchandise
imports growth
growth rate
Service imports
growth growth
rate
5.1
China
90’s
80’s
90’s
9.3
13.4
15.4
11.7
18.6
15.9
5.0
8.7
12
16.1
9.6
17.8
11.8
28.2
Source: World Development Indicators 2006.
Table 5
1982
CHINA
Goods
exports
as as
%age of
Total
Exports
of
goods
and
services
85.43
Services
exports
as
%age of
Total
Exports
of
goods
and
services
11.86
INDIA
Goods
exports
as
%age of
Total
Exports
of
goods
and
services
72.27
Services
exports
as
%age of
Total
Exports
of
goods
and
services
22.97
1990
2000
2003
85.31
85.29
87.46
7.66
5.71
4.67
78.32
69.25
68.59
19.81
26.71
27.04
Source: World Development Indicators 2006.
Where the structure of service exports is concerned, India’s experienced a significant
shift towards computer, communications and other services with their share in total
commercial service exports more than doubling from 30% in 1980 to 70 % in 2003 while
the share of travel and transport services fell steadily during this period. In case of China,
the shift has been less dramatic with the share of computer, communications and other
services in total commercial service exports rising from 22% in 1990 to 45% in 2003 and
falling to 39% in 2005. The corresponding share of transport services has been falling
while the share of travel services has risen during the same period (appendix table 6 and
7). As far as imports are concerned, while the share of Insurance and financial services
has risen for both India and China over this period , it fell from 11% to 6.5% of total
commercial service exports between 2000-2003 for the former while it rose almost four
times for China during 1990-2003. The share of Computer, communications and other
services as well as travel services in total imports has also been rising while that of
transport services has been falling for both countries ( See appendix tables 8 and 9).
Within merchandise exports, major structural changes are taking place vis-à-vis a shift
towards manufactures from primary products with the share of primary products in total
exports falling for both India and China, the decline being more pronounced for china.
The evolving structure has meant large and growing trade surplus in manufactured
goods but a small and declining surplus in agricultural commodities (Table 10). China
was a net agricultural exporter of $2 billion in 1990. By 2003, this had been transformed
into net imports of $14 billion. The food surplus remained almost constant at around $ 3
billion for India during this period (UNDP 2006).
Where share in global markets is concerned, China has emerged as a major exporter of
manufacturers since 1990 with a global share of 8.3% in 2004. India is not yet a major
exporter to the world. Within manufacturing, China has a significant share of world
markets for iron and steel, office machines and telecommunications equipment and in
textiles and clothing. Except for textiles and clothing, where India’s share has grown
modestly to 4.0% and 2.9% of global exports and less so to 1.6% in iron and steel
exports, India’s shares are very small and not growing. The share of low technology,
labour-intensive and resource based products, representing largely the traditional exports
remained more or less unchanged (Srinivasan 2006).
As far as the shifts in factor contents of country specific commodity structure are
concerned, both the nations experienced a distinct fall in the share of primary
commodities in total exports towards manufactures. In case of manufactures, China
experienced a substantial shift towards the exports of High and medium skill and
technology products especially electronics and communications equipment, parts and
components over the period 1987-2003. Although, India too experienced a rise in the
share of low, medium and high skill and technology intensive manufactures, especially
non electrical machinery, Industrial chemicals, iron and steel and parts and components,
the share of labour and resource intensive manufactures remains substantial - it rose from
27.8% of total exports in 1975 to 48.5% in 1995 while declining to 40.3% in 2003.
Interestingly, the share of textiles in total exports has been falling for both the countries
( Appendix Table 10).
Where imports are concerned, not surprisingly there has been a rise in primary
commodity imports. For both India and China though the share of medium skill and
technology intensive manufactures has fallen ( from 27.7% in 1987 to 20.1% in 2003 for
China and from 17% in 1985 to 10.4% in 1990 for India), the share of high skill and
technology intensives manufactures has risen slightly for China while its fallen for India
during this period. In case of labour and resource intensive manufactures imports China
has witnessed a substantial decline (from 12.9% to 6.9%) whereas India has experienced
a rise (from 8.2% to 13.5%) during the same period (appendixTable 11).
To sum up, structural changes in growing trade towards more technology intensive
manufactures has been much more pronounced in case of China, both in terms of there
share in total domestic exports as well as in global merchandise exports. India however
has experienced a rapid rise in more technology intensive services.
Changing Production and Labour market conditions
The growth success and questions of sustainability
China’s GDP grew the fastest in the world at an average rate of 10.3% per year during
1980-90, while India’s grew at 5.7% (World Bank 2005). This difference between the
remarkably high growth rates of GDP in China and the more moderate though sustained
growth in case of the Indian economy has also started narrowing recently. The Chinese
growth has been relatively volatile around the trend growth rate of 9.8 while the Indian
economy broke from its average post-Independence annual rate of around 3 per cent
growth to achieve annual rates of more than 5 per cent from the early 1980s. However in
the most recent period ( 2003- 2007) the Indian economy has apparently grown at rates in
excess of 8 per cent per annum, coming close to the Chinese average.
In terms of absolute level of Gross National Income (GNI) at Purchasing Power
Parity (PPP) exchange rates in 2003, China, with $10.15 trillion in GNI, was second
largest in the World ( just behind the U.S figure of $ 13.23 trillion) with India falling
marginally behind Japan ($ 4.22 trillion approx) in the fourth position with a GNI of
$4.21 trillion. According to IMF (2005), India’s share in global output at PPP exchange
rates rose from 4.3% in 1990 to 5.8% in 2004, and India’s growth during 2003 and 2004
to have accounted for one-fifth of Asian growth and one-tenth of World growth, as
compared to China’s contribution respectively of 53% and 28% (Table 1).
The shares of the two countries (GDP levels and growth) have been increasing over
time, although more so in the case of China than India. The two together accounted for
more than a sixth of global growth during 1990-2003 and account for a large share of
GDP and growth of low and middle income countries (Table 2).
Their exists a high correlation between the remarkable rates of growth in China and its
corresponding rates of domestic investment and capital formation as a share of GDP
(varying between 32 per cent and 44 per cent of GDP) which have been very high by
global standards and a large part of them has been directed towards manufacturing and
related sectors. According to Chandrasekhar and Ghosh (2007), this combined with the
fact that both these indicators have exhibited marked volatility around trend growth rates,
seem to suggest that the cyclical pattern of GDP growth around a high trend growth rate
is related to the pattern of investment. To the extent the latter is related to trade flows, it
would again have a significant impact on the structural transformation in production
patterns. In case of India, the higher investment rates (around 30% in 2004-05) have
largely been correlated with the growth in services.
The high rates of growth have raised the obvious questions of their sustainability in the
long run, especially in case of China. These in turn involve the nature of the current
growth process and its sources including supply side factors. In this regard, Srinivasan
(2006) points out that given the higher capital intensity15 of China’s current growth
process, its incremental capital output ratio was substantially higher than that of India
(6.7%). Where total factor productivity is concerned, TFP growth rose from 2.06%
during 1989-1995 to 2.49% per year during 1995-2003 in case of India while China’s
TFP16 growth fell from a dramatically high 6.33% per year to 2.49% between the same
periods. Its contribution to GDP growth continued to be almost the same (41.0% and
40.0%) in the two periods in India, while it fell from 64.3% to 34.9% in case of China.
The estimates carried out by Jorgenson and Vu (2005) reveal that China witnessed a
faster TFP growth than India during most of the period 1953-2003, except during 19952003 when their TFP growth rates were almost the same17 .
Sources of Output Growth in China and India (% Per Year)
Period 1989 – 1995
GDP
15
Capital
L a b ou r
Period 1995 – 2003
TFP
GDP
Capital
L a b ou r
TFP
Given that manufacturing output accounts for a larger share of total output and its substantially higher
investment in more capital intensive infrastructure.
16
The TFP estimates need to be taken very cautiously given notorious problems with datasets and
methodologies in case of both these countries.
17
though the revised data could raise China’s estimates.
Growth
ICT
Non
-ICT
hours
qualit
y
Growt
h (%)
ICT
NonICT
hour
s
quality
China
9.94
0.17
2.12
0.87
0.45
6.33
7.13
0.63
3.17
0.45
0.39
2.49
India
5.03
.09
1.18
1.27
0.43
2.06
6.15
0.26
1.77
1.22
0.41
2.49
SOURCE: Jorgenson and Vu (2005)
Also, given the higher rates of investment and gross domestic capital formation (44%
and 42% in case of China and 30% and 24% in case of India), it appears then that limits
to investments in physical capital are already being reached in China and sustainability of
the growth process would require not only a rising TFP growth but also a more efficient
utilization of its existing labour force18. This further underlines the need for the agrarian
transition of workers from low productivity primary sector to the high productivity high
growth manufacturing sector in case of the Chinese economy.
Where India is concerned, the limits to growth in terms of both factor accumulation as
well as TFP growth are far from being reached given the much lower levels of investment
and gross fixed capital formation and hence there exists substantial scope for further
unleashing its growth potential.
Jobless Growth and the incomplete agrarian transition
Where trends in employment growth are concerned, a variety of alternative estimates 19
at the broad macroeconomic and sectoral level are available, all of which however
18
Srinivasan (2006) also points out how a rise in labour force given rising population dependency ratios
and very high ratios of working age population.
19
See Key Indicators of labour market (ILO), Chandrasekhar and Ghosh (2007), Ghose (2005) Palinivel
(2006), Uma Kapila (2006), Goldar (2002) among others.
indicate certain distinct trends20. We begin with a structural picture of output and
employment shares in total value added followed by value added growth rates and
estimation of employment elasticities .
A note on methodology
The standard method of calculating employment elasticities is the arc elasticity
formula
eio  (Ei1  Ei0 / Ei0 )/(Yi1 Yi0 /Yi0 )
However this formula has a built in instability while calculating year over year elasticities

and is thus not very appropriate for comparitive purposes. So a different approach
commonly employed these days21 is adopted using a log linear regression model with
country dummy variables C interacting with log GDP to give estimates of point elasticity:
InE i    1InYi  2 (InYi  Ci )  3Ci  i
Here 1   2 represents the change in employment associated with a differential change

in output. The sectoral value added elasticities w.r.t overall GDP are then calculated
using the same formula with E representing employment by sector and for calculating

value added elasticities by sector Y is replaced by V representing total value added for
sector i.
Thus two sets of sectoral elasticities besides overall elasticities are calculated for the
period 1992-2005 : the first give an indication of whether employment has been rising or
falling in a sector relative to both overall GDP as well as other sectors. The value added
elasticity gives an indication of whether growth in a sector is largely productivity driven
or employment driven and hence whether trends indicate a move towards labour
substituting production . These calculations are used with other estimates on output and
employment shares and elasticities to arrive at a more comprehensive picture regarding
the processes at work.
Where China is concerned, recruitment, remuneration as well as migration in labour
markets was tightly controlled through an elaborate policy framework and state owned
institutional structure until an initial relaxation of state control during early and mid
1980’s post the 1978 economic reforms. However the real move towards liberalization of
20
It must be remembered that where employment is concerned , there exist severe data limitations in case
of China
21
See for instance KILM (2005) and Trade and human poverty in Asia Pacfic , UNDP( 2006).
labour market conditions came with fresh reforms in 1994 with a relaxation of state
control over recruitment, working tenure and remuneration in case of both urban state
owned and collective enterprises as well as rural Township and Village enterprises
(TVE’s). The institutional structure also underwent a change with liberalization of
production and ownership conditions in urban and Industrial enterprises and a movement
from commune systems towards a ‘new responsibility system” in rural areas which
effectively brought back family farming under a fixed rent tenancy system22.
The impact on the institutional nature of employment is clear. Uptil 1990, a large
chunk of urban employment was in state and collective enterprises and rural employment
was in TVEs and in small family farms that emerged under the “responsibility system”.
By the end of the decade, the state and collective enterprises ceased to be the principal
employers, and there emerged a broad variety of production and trading units in both
rural and urban areas ranging from “cooperative enterprises”, “joint ownership
enterprises”, “limited liability corporations”, “share holding corporations” to enterprises
owned and operated by investors from Hong Kong, Macao, Taiwan province and foreign
countries. A substantial numbers of recognized and registered small- scale private
enterprises and individual businesses, officially recognized and registered also came into
existence (Ghose 2005). As a result, the post 1990 period becomes significant in
analyzing the impact of economic reforms and trade liberalisation of a more market
oriented production and employment structure on both the level and nature of changes in
labour market variables. However, certain important features in terms of labour market
conditions in China that need to be kept in mind over here include the
public
provisioning of shelter, food and basic amenities alongwith the existence of externalities
generated by the presence of substantial investments in heavily subsidized basic
infrastructural services and activities. These imply lower input costs without implying an
equivalent fall in terms of adverse welfare consequences where working conditions are
concerned as a result of pro-active state intervention.
The shifts in terms of sectoral value added shares reflect the influence of external trade
patterns post opening up and the consequent implications in terms of being caught at
specific ends of global value added chains. During the initial decade and a half of reforms
22
See Ghose (2005) for further details.
post 1978-79 in China, while the percentage share of value added in output of the
secondary sector continued to be the highest, it progressively declined from 46% in 1975
to 41.6% in 1990 while the share of services rose to 31.3% in 1990 as compared to 22%
in 1975. At the same time, the secondary sectors share in employment grew from 17.4%
to 21.4 % in 1990 while that of services grew from 12% in 1978 to 18.9% in 1990 ( table
6).
Table 6: Sectoral shares in GDP and Total Employment
India
1983
38.9
Agriculture,
value added
(% of GDP)
Industry,
24.5
value added
(% of GDP
Services, etc., 36.6
value added
(% of GDP)
Employment
in agriculture
(% of total
employment)
Employment
in industry
(% of total
employment)I
Employment
in services (%
of total
employment
1990
31.3
2003
21
China
1975 1985
32
28
27.6
26
46
43
41.6
47
50.2
47
41.1
53
22
18
31.3
33
33.4
40
69.1
59.8
77.2
62.4
53.4
52.2
46.3
44.8
13.6
13.7
13.5
20.8
19
23
17.3
23.8
17.3
26.5
9.3
16.8
27.6
24.8
36.4
31.4
1990
27
1995
20
2000
16.4
2005
13
Source: World Development Indicators 2006. (Figures in red are estimates from national
accounting sources in case of India)
The value added growth rates were highest for services (12.2%) followed by a 9.5%
value added growth rate for Industry during 1980-1990 while the employment elasticities
were relatively high at 0.65 and 0.62 for services and industry respectively ( table 7).
Table 7: Rates of growth of output and employment in China, 1980-2000
1980- 199090
2000
Primary sector
Annual employment growth
Annual Value Added growth
Employment elasticity
Secondary sector
Annual employment growth
Annual Value Added growth
Employment elasticity
Tertiary Sector
Annual employment growth
Annual Value Added growth
Employment elasticity
All sectors
Annual employment growth
Annual Value Added growth
Employment elasticity
2.8
6.2
0.45
-0.8
3.8
-0.21
5.9
9.5
0.62
1.6
13.5
0.12
7.9
12.2
0.65
5.1
9.1
0.56
4.1
9.3
0.44
1.1
10.1
0.11
The following decade post WTO accession together with a substantial rise in
economic liberalisation and labour market reforms saw changes in this trajectory with
Industry’s share in total value added progressively rising around a trend of 50% during
1990-2005 while that of services declined initially to rise marginally above the 1990 level
at 40% in 2005 largely at the cost of a continuously declining share of the primary sector.
The value added growth rates were 12.5% and 8.8% respectively for Industry and
services over 1992 -2005 (table 9). China thus had made its transition from agriculture to
Industry in terms of output growth. At the same time, paradoxically employment
elasticities of Industry both relative to overall GDP as well as industrial value added
growth fell dramatically23. Manufacturing employment actually fell at a rate of more than
3% p.a during the latter half of 1990’s when value added growth rates were above 8%
p.a ! The figures indicate not merely a structural shift in employment from both
agriculture and industry towards services, but also that the impressive growth (9.7%)
overall is largely productivity driven rather than employment-led with sectoral
employment elasticities not being very high even for services as compared to most other
economies within the entire region. At the same time, real manufacturing wages more
23
Other estimates ( Ghose 2005, Chandrasekhar and Ghosh, 2007, UNDP 2006, KILM 2005) also confirm
this sharp decline in Industry employment growth rates and elasticities during the 1990’s .
than doubled between 1990 and 2005 further strengthening grounds for belief in an
exceptionally high productivity growth in manufacturing ( appendix Table 17a).
Table 8: Employment elasticities and GDP growth (1991-1995, 1995-1999 and 1999-2003)
Average Annual GDP
Total Employment Elasticity
Growth (%)
1992-
1996-
2000-
1992-
1996-
2000-
1996
2000
2004
1996
2000
2004
China
0.14
0.14
0.17
12.7
8.3
8.1
India
0.4
0.43
0.36
6.3
6.3
5.3
Table 9
China
India
Agriculture
Elasticity
(1992-2005)
gdp
Value
added
0.09
0.23
0.03
Industry
Elasticity
(1992-2005)
gdp
Value
added
0.07
0.06
0.18
0.20
Services
Elasticity
(1992-2005)
gdp
Value
added
0.47
0.50
0.54
0.41
Sector value added growth and total
growth (1992-2005)
Agriculture
Industry
Services
Total
3.7
2.8
12.5
6
8.8
8.1
10
6.5
Overall employment growth fell from 4.3% in the 80’s to 1.1% in the 90’s on an
average (table 12). The unemployment rate also climbed from 2.5 per cent in 1990 to 3.1
percent in 2000 and 4.3 per cent in 2003 (ILO 2005).
Ghose (2005) further sub divides the period after 80’s into 1990-1995 and 1995-2002 in
order to assess the specific impact of labour reforms on employment conditions. Where
employment growth rates are concerned, urban employment grew more rapidly than rural
employment over the entire period. However, while the period pre 1995 reforms was
marked by improvement in employment conditions and the rise of regular employment in
both rural and urban areas, the situation worsened considerably afterwards. There was
massive labour shedding post the 1995 labour market reforms on part of state and
collective enterprises, decline in urban formal and informal wage employment and an
increase in irregular employment over the period 1995-2005 ( Ghose 2005). However,
paradoxically in rural areas, the structure of employment saw a rise in regular and formal
and informal wage employment and a decline in irregular employment while employment
in township and village enterprises continued to grow. Given the fact that overall
employment growth in rural areas was actually zero during this period, this merely
indicates a structural shift in nature of employment patterns in rural China while all net
additions to employment growth were in the urban areas and were brought about by a rise
in irregular employment.
India on the other hand has experienced a structural transformation towards services
where both value added as well as employment is concerned , though the intersectoral
transition from agriculture either to manufacturing or services in the latter case is far from
being complete with the primary sector still accounting for almost 60% of the total
employment.
The value added shares indicate a shift towards services the share of which grew from
38% in 1983 to 42% in 1994 to more than half of total value added at 53% approx in
2003. At the same time the share of Industry stagnated at about a quarter of total value
added fluctuating between 25-27% approx while that of agriculture progressively
declined from 37% in 1983 to 21% in 2003 (table 6 ).
Services also experienced the highest average annual value added growth rates during
1992-2005 at 8% followed by Industry with a growth rate of 6% (table 9 ). At the same
time while services employment elasticities (0.42) and employment growth was higher,
employment elasticities of agriculture as well as overall manufacturing were low during
the 1990’s ( 0.01 and 0.29 according to some other estimates24). Overall, the late 1990s
was a period of quite dramatic deceleration of aggregate employment generation, which
fell to the lowest rate recorded level since such data began being collected in the 1950s.
There seems to have been some rise in employment in case of services in the most recent
years25.
Most estimates26 confirm the dramatic fall in employment growth and elasticities in
case of agriculture during the 90’s, not surprisingly indicating the limits to the
24
Palinivel (2006 ), Kapila (2006), Goldar (2002) , Chandrasekhar and Ghosh (2007) also confirm these
trends overall.
25
NSSO , 61 th ROUND, 2004-2005.
26
Kapila (2006), Palinivel (2006), UNDP(2006), KILM (2006).
employment growth potential of the sector. Where manufacturing is concerned,
employment growth has stagnated while there has been a substantial rise in labour
productivity. According to Goldar (2002), while employment elasticities of organized
manufacturing rose slightly from 0.26 in the pre-reform period, 1973-74 to 1989-90, to
0.33 in the post-reform period, 1990-91 to 1997-98, they fell for overall manufacturing
given a fall in employment elasticities for unorganized manufacturing which accounts for
more than four fifths of the total employment share in manufacturing with growth rates of
overall manufacturing employment being as low as 1.87%. At the same , Chandrasekhar
and Ghosh point out the sustained increase in labour productivity as measured by the net
value added (at constant prices) generated per worker in case of organised manufacturing.
Labour productivity tripled between 1981-82 and 1996-97, stagnated and even slightly
declined during the years of the industrial slowdown that set in thereafter, but has once
again been rising sharply in the early years of this decade. Where trend in real
manufacturing wages are concerned, they point out a corresponding fall in share of wages
in value added which declined progressively from the late 1980s till mid 1990s to fall
further to half of their mid 1990s level after a brief period of stability. Wages now
account for only 15 per cent of value added in organised manufacturing, which is one of
the lowest such ratios anywhere in the world. They explain this paradox of rising
productivity and falling share of wages in terms of falling employment in manufacturing
alongwith stagnating real wages despite a rising trend in output growth which indicates a
clear worsening of the bargaining strength of Industrial workers (Chandrasekhar and
Ghosh 2007).
Given the rise of both employment growth as well as value added in services, the
nature and level of employment creation in this sector becomes crucial. However, despite
India’s much celebrated success in dynamic software and IT enabled services sector, total
employment in this sector as a percentage of total non agricultural employment is
insignificant. The rapid rates of growth of the late 1990s were from very small bases, and
the sector typically remained very small relative to the rest of the economy, with fewer
domestic multiplier effects because of high import dependence . Also, services as a
whole is a very heterogeneous sector covering a wide range of activities some of which
provide merely a ‘refuge’ employment to those workers not absorbed elsewhere. The
recent rise in services employment in India has been at both high and low value added
ends of the services sub-sectors, reflecting both some dynamism and some increase in
“refuge” low productivity employment. We shall look at this sector in greater detail in the
next section.
It has also been pointed out widely that there is growing evidence of labour force
flexibilisation and informalisation with Indian labour markets being characterised by high
degrees of underemployment and underutilisation of labour alongwith rising open
unemployment27 (ILO 2005, ADB 2005). More recently in case of India, evidence seems
to suggest a rise in employment as well as in labour force participation rates with the real
expansion coming from a substantial rise in estimates for self employment. In this regard,
again Chandrasekhar and Ghosh (2007) in a detailed survey of recent employment trends
in India and China , indicate that available evidence suggests not only a significant
decline in proportions of all forms of wage employment alongwith paradoxically falling
or stagnating real wages but also that the latest NSS survey itself indicates the rise in self
employment to be largely a distress-driven phenomenon, led by an inability to find
adequately gainful paid employment on part of a vast section of the labour force in the
current context.
To sum up the discussion here, three broad trends seem to emerge where patterns of
growth in output and employment are concerned. Firstly, as compared to the 1980s a fall
in average annual as well as sectoral employment growth rates and elasticities alongwith
a rise in unemployment rates for both the countries during the 1990’s and the first half of
the current decade accompanied the higher rates of growth of output. Secondly, though
there has been a structural shift away from the primary sector towards manufacturing in
case of China and services in case of India where output growth rates and contributions to
total output are concerned, a corresponding shift in terms of employment growth and
shares in total employment has not occurred. While manufacturing employment rose
during the 1980’s in China, there has been a dramatic fall in employment growth rates
during the 1990’s which continues till date with a rising unemployment rate. In case of
India, though employment growth has been sluggish in Industry, some growth at both the
high end and low end services has occurred recently but this is yet to transform into a
27
Unemployment rate rose from 2.2 per cent in 1995 to 4.3 per cent in 2000 (ILO 2005).
sectoral transition from employment in low productivity agricultural sector to high
productivity, high growth sectors of the economy. Thirdly, the nature of employment in
itself has undergone a dramatic change with rising contractualisation, informalisation and
flexibilisation of labour force in both these countries with adverse welfare consequences
for those at the bottom half.
In case of both India and China , massive labour shedding on part of state owned
and public sector enterprises during the decade of the nineties alongwith rising labour
productivities in the dynamic high growth sectors of the economy led to these broad
outcomes. Srinivasan (2006) dismisses the falling employment elasticities as mere
adjustments to shifts in demand and supply conditions which are transitory rather than
structural in nature and would rise with an increase in aggregate consumption demand.
However falling employment elasticities to the extent accompanied by a sustained rise in
output and labour productivity alongwith changing patterns of output growth seem to
indicate certain structural transitions in the growth and employment trajectories of these
large surplus labour economies.
While Chandrasekhar and Ghosh (2007) explain the overall decline in the nature
and level of employment conditions on the nature of trade liberalisation as well as
implementation of domestic privatisation and labour market reforms, others like Ghose
(2005) tend to explain it in terms of the transition to more efficient economic structures
brought about by a shedding of surplus labour besides technological changes. To the
extent that surplus labour is not absorbed by the growing sectors of the economy, the role
of technological change and its impact on demand for labour becomes crucial. In the
following section, in order to correlate changing trade patterns and hence forms of
integration with the global economy with the transformation in output and employment
patterns, a more disaggregated perspective on existing conditions in the growing
manufacturing and services sectors of the two countries is attempted.
Output and Employment growth in Manufacturing and services- A disaggregated
perspective
As far as services are concerned, LABORSTA, the ILO database gives disaggregated
time series data on employment by economic activity over the period under discussion
based on national accounting statistics of both these countries (see tables 18-21 ).
As would be expected on the basis of trends in broad sectoral employment elasticities,
there has been a rise in percentage shares of employment in all sub categories in case of
services for both the countries. For both the countries, the percentage shares as well
growth rates in employment were high in Construction and Wholesale and Retail Trade
and Restaurants and Hotels which again is not surprising given our earlier discussion on
rise in labour force flexibilisation and informalisation, given that both these sectors are
typically refuge sectors with an employment elasticity greater than one . However unlike
construction, the latter category given its heterogeneity, also involves a rising
employment of more skilled labour with a rise in growth due to greater diversification of
economic activities. Community and social and personal services are an important sub
sector in case of both the economies both in terms of their share in total services
employment as well as their welfare consequences. Their percentage share has been on
rise in case of both the countries, but the rise was more accentuated in case of China
where their share grew from 2.6% in 1990 to 6% in 200228 .
India initially witnessed a marginal rise in this sectors share between 1983-1993 which
again fell slightly in 2000. Though the growth rates of employment in this sector actually
fell in 1990s as compared to the 80s, the GDP growth rates of this sector too fell as a
result of which employment elasticities of growth turned negative29. Again as expected
on the basis of developing patterns of comparative advantage in trade, employment
growth in the services sector exhibits greater dynamism in case of India in case of
Transport, Storage and Communication and Financing, Insurance, real Estate and
Business Services where growth rates rose in the 1990s at higher rates than that prevailing
28
However, there are problems in identification and categorization in case of the Chinese Economy given
the command structure of the economy where public provisioning of services is concerned. The rise in
percentage share could hence be accounted for merely due to change in classification of these services from
activities not adequately defined.
29
This would occur if negative GDP growth is accompanied by negative growth in productivity so that
even a small rise in employment growth would turn the elasticity negative. Given that this sector is
employment intensive by nature, this trend has adverse welfare consequences implying lower public
provisioning of essential services during times of rising unemployment, labour force flexibilisation and
informalisation and falling real wages.
in the Chinese economy . However the percentage shares of these sectors in total
employment though rising marginally (more so in case of India), still remain very small.
According to the S.P.Gupta committee report, capital intensity of output in case of the
Indian economy rose not only at the aggregate level but also in most sectors including
services except in case of these two sub sectors. Hence, the overall decline in the
employment elasticity is partly due to the technology impact of labour-capital
substitution with rising capital-intensity of output growth occurring even in the small and
unorganised sectors and services. The aggregate ICOR has increased from 3.4 during
1991/92-1996/97 to nearly 4.4 in 1996/97 and to over 5.0 during the Ninth Plan.
Where structural transformation and growth in manufacturing sector is concerned, the
disaggregated analysis presented here is based on the 3 digit ISIC dataset provided by
World Bank trade and production database30. The industries are classified as low skill and
technology intensive, medium skill and technology intensive and high skill and
technology intensive on the basis of UNCTAD classification31. Also, specifically trends
in major groups of Industries (in terms of their share in total manufacturing output and
employment as well as their increasing importance in rising merchandise trade flows)
being analysed here include ‘Food, Beverages and tobacco’, ‘Textiles, clothing and
leather’, ‘Chemicals, rubber and plastic’, ‘Basic Metals ‘and ‘Machinery and
equipment’. The analysis here however comes with very strong caveats where
employment growth and elasticities is concerned as marked volatility in estimates could
arise due to very small changes in underlying variables given the highly disaggregated
nature of the data. Also given missing data, the time period covered might not be
adequately represented ( tables 23-27).
Where China32 is concerned the share of low and medium technology intensive
industries in total manufacturing output and employment remained high as compared to
high technology intensive Industries and was the highest for medium skill and technology
intensive Industries. The share of ‘Food, Beverages and tobacco’, ‘Textiles, clothing and
leather’, ‘Chemicals, rubber and plastic’ and ‘basic metals’ in total manufacturing output
30
Nicita A. and M. Olarreaga (2006), Trade, Production and Protection 1976-2004, World Bank Economic
Review 21(1).
31
See appendix note.
32
See tables
remained more or less stagnant or declined slightly while that of ‘Machinery and
equipment’ rose, whereas except for ‘Chemicals, rubber and plastic’, the share of all
these industries in total employment fell. While output growth (ranging from 7%-15%)
and productivity was higher in case of all the categories and industry groups being
analysed over here in the 90s as compared to the 80s, high technology industries and
‘ Machinery and equipment’ followed by medium technology industries and chemicals
experienced the highest growth in output as well as labour productivity. Despite
limitations of the dataset being used here, the trends are in conformity with those
expected on the basis of broad sectoral trends in terms of growth in exports, output and
employment patterns.
In case of India, again while the share of medium skill and technology intensive
Industries in total manufacturing output was the highest followed by low technology
industries, their share in total employment was lower than that of low technology
industries. The share of Industrial chemicals in output was highest followed by
machinery and equipment while the share of employment was the highest in textiles,
clothing and footwear and food , beverages and tobacco. Output and productivity growth
both fell in case of low and medium technology industries while employment growth rose
marginally in case of low technology Industries but fell substantially for medium
technology Industries whose share in total output is the highest. Though output,
productivity and employment growth rose in case of high technology industries, their
share in manufacturing output and employment remains marginal. Where specific
industries are concerned, output growth fell in most categories, in particular for basic
metals which also experienced a substantial fall in employment and productivity growth.
Except for machine and equipment, productivity growth fell in most industries while
employment growth rates grew marginally. However given the fall in output,
employment elasticities would have risen more than proportionately to growth in
employment. This gives us a mixed picture overall but does clearly show that the
structural transition in terms of its employment effects has been more pronounced in case
of China as compared to India.
To sum up, both in case of services as well as manufacturing a preliminary survey of
disaggregated data seems to be in conformity with expectations regarding the more
dynamic trading sectors demonstrating greater dynamism and growth in terms of output,
productivity and employment indicators. Though adverse employment effects are more
pronounced in case of the more aggregated analysis carried out in the earlier section, this
could well be a result of limitations in existing data, especially where China is concerned.
Concluding Comments- Directions for further research ?
Some basic facts which emerge from the above discussion and have been discussed in
recent literature are the coexistence of rising trade, high rates of growth of output
accompanied by disappointingly low rates of growth of employment and labour
absorption in case of both India and China despite fundamental differences in their basic
economic structures (mixed developing economies vs. a command economy) that
continue to influence their differing trajectories in the post reform period.
Several questions become important from whichever perspective one approaches the
issue: Is rising unemployment transitional or structural? How long is the time period of
adjustment? Are there any path dependent implications? How important are regional and
other contextual specificities?
The role of technology remains crucial but the exact mechanism through which it
operates is debatable. The argument put forward by the new growth theorists attempts to
explain wage inequality and employment effects in terms of a “skill bias” arising out of
technology imports to the developing world. As pointed out earlier, to the extent the ‘skill
gap’ that arises can be explained in terms of absence of requisite skill, it is transitional
and can be overcome with adequate infrastructural and R and D investment. Under such
circumstances, persistence of long run unemployment and wage inequalities can only be
explained in terms of institutional rigidities and lack of adequate investment which hinder
the growth potential of such economies. Given that both the Asian giants (in particular
China) have experienced relatively high levels of investment and also have a relatively
elastic supply of skilled labour due to existence of a “ pool of labour with basic skills”
these explanations do not seem to provide all the answers. Moreover to explain these
phenomenon in terms of institutional rigidities is to merely state how history unfolds
itself.
Here India and China given the sheer size of their economies, provide interesting
grounds to explore the interaction between domestic structural adjustments and the
imposition of production patterns due to integration with global production chains. In
keeping with changes observed elsewhere in the developing world, rising trade
integration alongwith domestic economic reforms has led to loss of employment and job
security in both the countries due to massive labour shedding on part of state-owned
enterprises, rising import penetration, as well as macroeconomic fluctuations resulting
from short-term capital movements.
At the same time, trade integration combined with delocalization of production and
services from the developed world has led to rising trade, production in case of various
groups of Industries such as food processing, textiles or garments, Industrial chemicals,
office equipment, electronics, and ICT (information & communications technologies). As
pointed out earlier, to the extent that surplus labour is not being absorbed by the growing
sectors of the economy, the role of technological change and its impact on demand for
labour becomes crucial.
The changing structure and growth of employment and the nature of labour market
conditions in these developing Asian giants has significant implications for both, the
resultant welfare consequences as well as their instrumental role in realising the growth
and development potential of developing economies. In both these cases, there exist
some differences in the nature of the problem facing India and China which are in turn
related to differences in the nature of state intervention, resource base as well as levels of
development in the two countries.
As far as welfare effects are concerned, active state intervention in the form of public
provisioning of basic amenities and social infrastructure has to some degree counteracted
the adverse consequences of the rising informalisation and flexibilisation of the labour
force. Real wages too seem to have risen. However the increasing pace of labour market
reforms and rising labour force migration under conditions of extreme working poverty
(Li Shi 2006) could aggravate the situation considerably. In India on the other hand, low
real wages, absence of substantial public provisioning and basic social infrastructure have
further exacerbated the adverse welfare consequences of the worsening employment and
working conditions.
However, the preoccupation of this paper has been with the second aspect of these
changes which is related to the consequences of the structural transformation being
wrought in these labour abundant economies for their specific growth trajectories. Given
that agriculture even now accounts for more than half of the labour force in these regions,
as compared to less than 5% in developed countries, the process of structural
transformation is far from complete and if the prospects of rural population are to
improve in the presence of bias towards manufacturing and services in terms of both
output and employment growth, then there has to be rapid labour absorption in these
sectors largely through migration. To the extent that the trend shows high rates of growth
are accompanied by high rates of growth of labour productivity and low employment
elasticities, a more cogent explanation of the processes at work is required which explain
why the vast reserves of manpower within developing Asia are not tapped by the
operation of market forces in the long run.
As discussed earlier, the effects of trade integration in India have been largely one-way
and domestic, with the possible exception of services, in the sense of its influencing the
rate of GDP growth and the share of trade in domestic GDP, rather than India’s more
rapid GDP growth influencing global GDP growth significantly. Also, with a few
exceptions the share of traditional and labour and resource intensive exports remained the
same in total exports even though output patterns indicate a move towards medium skill
and technology production in the recent decade. Manufacturing employment elasticities
as well as growth remained low and while there was some employment growth in the
dynamic sub sectors of the services economy, most of the employment growth remained
concentrated in the low productivity ‘refuge’ sub sectors. Hence, even though, the
traditional patterns of merchandise trade have not altered dramatically with growth in
trade, they have not led to an increased exploitation of India’s comparative advantage in
terms of its vast labour reserves. Infact, almost all sectors of the Indian economy have
experienced rising capital intensity of production in the era of increased economic
openness33.
Where China is concerned, both its integration with the global economy as well as its
share in global trade, especially where merchandise exports are concerned have risen and
33
S.P. Gupta committee report, 2002.
have also brought in a shift towards a more technology intensive trading and production
structure. This was also accompanied by rising TFPs and capital intensities of production.
At the same time, employment growth and elasticities of the dynamic and growing
manufacturing sector in particular have fallen drastically by all accounts.
It is arguable that limits to physical capital accumulation have been reached and
realisation of higher productivity gains through intersectoral shifts in labour force is
essential to sustain the current growth process in case of the Chinese economy. At the
same time, given its sheer size and its growing impact on global economic growth and
trade, China is much better placed than India in experimenting with an alternative
technological growth trajectory which involves a more efficient utilisation of its abundant
labour force. However, as proposed by Patnaik (2007), it seems to have become
increasingly caught in a growth paradigm where the pace of its technological (as an
imitator rather than innovator) as well as structural change gets interlinked with that
prevailing in the advanced capitalist economies. The success of China’s export drive
arises therefore from the fact that she can produce manufactured goods at much lower
prices than in the West, even while using the same technologies as are available in the
West and hence does not seem to guarantee a dynamic change in its labour market
conditions.
This might be an indication of the existence of structural processes that, given the
nature of current growth and development strategies based largely on some variant of the
dominant economic orthodoxy, are linked to the course of contemporary global economic
integration. The question then arises- are there any processes leading to similar growth
trajectories for large developing nations, which as a result of mutually reinforcing
influences (export orientation and international technological diffusion), keep pushing
even growing economies such as India and China in a direction which involves potential
underutilization of its labour reserves?
One way to begin exploring these issues would involve investigating certain crucial
hypotheses. Firstly, Is the rise of intra industry trade between the US and the two Asian
economies an important channel of technological diffusion for the latter? Are their any
similarities in the resultant growth trajectories embarked upon by India and China which
go beyond fundamental differences in their economic structure? How and to what extent
is the process of technological diffusion different for the two countries? This would
involve estimating international R and D spillover regressions employing a production
function approach using import/export shares as bilateral weights to capture the relative
importance of foreign Rand D activities on domestic factor productivities. The proxies
for estimating trade related R and D effects that have been fruitfully employed in earlier
studies and could be used over here include patent citations and applications, royalty fees,
licensing fees etc. The empirical tools required for this purpose would entail usage of
regression analysis to cross-section and time series data for the last two and a half
decades.
At the second level, the relationship between productivity differentials that can be
traced to changes in composition of trade flows after the first stage would have to be
correlated with employment and wage indicators for the two Asian economies in the post
liberalization era. Again since TFP depends on both Y/L and K/L – even if there is TFP
growth due to technological diffusion, the neo classical presumption is that K/L would be
lower in developing countries because of factor price differences. However there are
others (Findlay1978, Rosenberg 1978, Patnaik) who contend that there isn't much choice
of techniques open to developing nations as their pace of technological and structural
change gets increasingly linked to the global economy with rising trade integration. As a
result, the Y/L in developing countries (at least in tradeables) converges to Y/L in
developed countries . It would be interesting to test these competing hypotheses vis-à-vis
the characteristics of the global value added chains emerging as a consequence of rising
intra industry trade. This would involve exploring possibilities of examining
the
cointegration relationship between Y/L in developed and developing countries.
Alternatively one might try to look at responsiveness of K/L in developing countries to
domestic factor-price movements--though this will be more difficult as there might not be
enough variability in factor prices in the sample and the response would anyway be
expected to take place after a long lag. Again differences in logs of labour productivity of
developed and developing countries might throw up some interesting results.
As far as wage and price indicators are concerned, it would be interesting to look at
wage differentials for the same class of labor between the tradeable and non-tradeable
sector. If there is a substantial differential after eliminating composition effects, then it
might be said that working in the tradeable sector requires some special skills that are not
captured by the official categorization of labor between 'skilled' and 'unskilled'. If only
we could increase the supply of this special labor, the tradeable sector would grow even
faster and cancel out the negative employment effects of productivity increase. On the
other hand, if there is no substantial wage differential, then we can presume that there is
no labor constraints on the tradeable sector and therefore perhaps we cannot hope to
further raise its growth rate (this is not conclusive because there might be other
constraints like infrastructure). In terms of distribution, it might be interesting to look at
growth linkages between the export sector and the rest of the economy. Are we seeing
export-led growth or are we seeing growth of export enclaves isolated from the rest of the
economy? Or does this simple dichotomy overlook something else which is happening in
the economy- an export-led growth or openness-inspired growth over an area that is not
necessarily small but is detached from the rest of the economy and therefore constitutes a
sort of enclave.
It is in this context that questions surrounding the prospects of unleashing latent growth
possibilities given the sheer size of their domestic product and labour markets become
significant. Given the necessity of structural transformation in employment growth
patterns, in order to realize not only the development potential and welfare of their
respective labour forces, but also to ensure a more sustainable and equitable growth
process, an urgent rethinking on alternatives to current strategies of growth and
development becomes imminent in case of both the developing Asian giants.
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APPENDIX
Note 1:
In case of manufacturing, the following classification of Industries (based on UNCTAD ) into low skill and
technology, medium skill and technology and High skill and technology industries is used in the 3 digit 1SIC
analysis:
Low skill and technology intensive manufactures - Textiles, Clothing, Cork, wood and paper products, Non-metallic
mineral manufactures, Low-skill and technology-intensive manufactures, Iron and steel, Ships and boats
Medium-skill and technology-intensive manufactures - Non-electrical machinery, Electrical machinery excluding
electronics
High-skill and technology-intensive manufactures - Electronics, Communications equipment (less parts thereof) and
household equipment, Computers and office machines (less parts ther
Table 5
1982
1990
2000
2003
CHINA
Goods
exports
as as
%age of
Total
Exports
of
goods
and
services
85.43
85.31
85.29
87.46
Services
exports
as
%age of
Total
Exports
of
goods
and
services
11.86
7.66
5.71
4.67
INDIA
Goods
exports
as
%age of
Total
Exports
of
goods
and
services
72.27
78.32
69.25
68.59
Services
exports
as
%age of
Total
Exports
of
goods
and
services
22.97
19.81
26.71
27.04
Source: World Development Indicators 2006.
Table 6
CHINA
1980
1990
2000
2003
2005
Commercial
service
exports
(current
US$)
..
5750
30100
46400
73900
Travel
services
(% of
commercial
service
exports)
..
30.24
53.84
37.53
39.64
Transport
services
(% of
commercial
service
exports)
..
47.08
12.18
17.05
20.87
Computer,
communications
and other
services (% of
commercial
service exports)
..
22.69
33.98
45.42
39.49
Source: World Development Indicators 2006.
Table7
INDIA
1980
1990
2000
2003
2005
Commercial
service
exports
(current
US$)
2860
4610
16000
23100
..
Travel
services
(% of
commercial
service
exports)
54.24
33.81
21.58
16.83
Transport
services
(% of
commercial
service
exports)
15.6
20.81
12.34
13.26
..
Source: World Development Indicators 2006.
Computer,
communications
and other
services (% of
commercial
service exports)
30.16
45.38
66.07
69.91
Table 8
CHINA
Commercial
service
imports
(current
US$
('000000)
1980
1990
2000
2003
2005
4110
35900
54900
83200
Travel
services
(% of
commercial
service
imports)
..
11.43
36.57
27.69
26.16
Transport
services
(% of
commercial
service
imports)
..
78.9
28.99
33.24
34.2
Computer,
communications
and other
services (% of
commercial
service imports)
..
7.39
27.27
30.33
30.79
Insurance
and
financial
services
(% of
commercial
service
imports)
2.29
7.16
8.74
8.85
Source: World Development Indicators 2006.
Table 9
INDIA
1980
1990
2000
2003
2005
Commercial
service
imports
(current
US$('000000)
2910
5940
18900
25500
Travel
services
(% of
commercial
service
imports)
3.88
6.62
14.24
13.76
..
Transport
services
(% of
commercial
service
imports)
61.35
57.52
46.06
36.68
..
Source: World Development Indicators 2006.
Computer,
communications
and other
services (% of
commercial
service imports)
29.39
30.08
28.64
43.07
..
Insurance
and
financial
services
(% of
commercial
service
imports)
5.38
5.79
11.06
6.5
..
Table10
PRODUCT STRUCTURE OF EXPORTS, 1975 - 2003 (Percentage of Total Merchandise Imports)
Chinaa
Product Group
Indiaa
1987
1995
2003
1975
1985
1995
2003
37.7
15.6
6.3
3.4
12.4
35.7
15.7
8.3
1.8
2.1
3.6
37.3
9.2
4.4
0.7
1.6
2.5
27.7
55.1
37.7
4
12.3
1.1
27.8
41.8
25.3
2.8
7.6
6
42.2
25.6
19
1.3
3.6
1.7
48.5
23
11.4
1.3
4.4
5.9
40.3
16.2
14.5
2.4
1.4
1.2
4
9.5
16.3
6.8
2.4
2.3
8.8
6.2
11.9
4.5
3.3
1.8
7.2
13.8
4.5
5.3
0.4
3.8
6.1
11.6
10.2
6.8
0.2
13.4
2.5
14
13.2
4.4
0.5
16.4
6.2
11
10.7
2.9
0.7
14.9
9.2
1.1
2.2
0.3
0.4
6.4
3.7
3
1.5
0.6
8.8
1.2
3.3
2
0.7
12.1
2.7
2.1
1.2
0.1
5.7
0.5
1.4
0.6
0
5.8
3.3
1.9
1.1
0
6.3
5.1
3.3
0.6
0.2
8.4
Rubber and plastic products
Non-electrical machinery
Electrical machinery excluding
electronics
Road motor vehicles
High-skill and technology-intensive
Manufactures
Industrial chemicals
Pharmaceuticals
Scientific instruments
Electronics
Communications equipment (less parts
thereof) and household equipment
0.5
1.4
0.6
2.2
3.2
3
2.2
4.9
4.2
0.5
3
1.1
0.8
3
1
1.7
2.2
0.7
1.4
3.6
1.4
3.9
0.4
0.6
1.1
0.9
1.8
2
5
1.1
1.6
3.4
2.3
5
1.1
2.6
12.3
4.4
3.8
0.7
2.6
30.3
6
1.8
0.7
0.3
0.8
0.4
2.2
1.5
0.4
0.8
0.1
5.9
2.3
0.3
1.9
0.2
8.5
3.2
0.6
1.9
0.3
Computers and office machines (less
parts thereof)
Parts and components
Other Manufactures
0.3
2.1
9.9
0.1
0.1
0.3
0.3
0.7
5.1
5.8
8.1
14.4
6.2
0.3
1.6
0.5
2.6
1.3
2.8
1.3
4.7
Primary Commodities
All Food products
Agricultural Raw Materials
Minerals, ores and metals
Fuels
Labour and resource-intensive
manufactures
Textiles
Clothing
Footwear, leather and travel goods
Cork, wood and paper products
Non-metallic mineral manufactures
Low-skill and technology-intensive
manufactures
Iron and steel
Fabricated metal products
Simple transport equipment
Ships and boats
Medium-skill and technologyintensive manufactures
Source: Source: UNCTAD secretariat calculations, based on UN COMTRADE.
a) Data for earlier years not available; b) Includes SITC 759, 764, 772 and 776
Table 11
PRODUCT STRUCTURE OF IMPORTS, 1975 - 2003 (Percentage of Total Merchandise Imports)
Product Group
1987
Primary Commodities
All Food products
Meat and meat preparations
Fish and seafood
Cereals and cereal preparations
Fruits and vegetables
Vegetable oilseeds and oils
Agricultural raw materials
Cotton
Rubber
Cork and wood
Minerals, ores and metals
Metalliferous ores and metal scrap
Non-ferrous metals
Fuels
Labour and resource-intensive manufactures
Textiles
Clothing
Cork, wood and paper products
Non-metallic mineral manufactures
Low-skill and technology-intensive manufactures
Iron and steel
Ships and boats
Medium-skill and technology-intensive
manufactures
Non-electrical machinery
Electrical machinery excluding electronics
High-skill and technology-intensive manufactures
Electronics
Communications equipment (less parts thereof) and
household equipment
Computers and office machines (less parts thereof)
Parts and components b
China
1995 2003
1975
India
1985 1995
2003
18
7.4
0
0.1
1.9
0.1
1
6.3
0
0.9
1.4
3
1.2
1.7
1.3
12.9
8.6
0
3.1
0.8
13.8
11.1
0.5
27.7
20.4
7
0.1
0.5
2.8
0.1
2.1
5
1.1
0.6
0.4
4.5
2.3
2
3.9
14.4
8.5
0.8
2.5
0.8
7.5
5
0.8
26.2
20.1
3.6
0.2
0.5
0.1
0.2
2.1
3.7
0.3
0.6
0.9
5.6
2.9
2.5
7.2
6.9
3.5
0.3
1.4
0.9
6.7
5.3
0.2
20.1
44.3
31.9
0
0
29.1
1.4
0.6
2.5
0.8
0.2
0
5.4
0.4
2.7
4.4
4
0.3
0
1.7
2
9.8
8.4
0.1
15.8
45.4
8.4
0
0
0.6
1.3
3.9
3.4
0.1
0.5
0.2
7
1.9
2.8
26.6
8.2
0.8
0
1.2
6.1
8.9
7.1
0.3
17
42.3
4.6
0
0
0.1
1.6
2.3
4.3
0.5
0.6
0.7
7.5
2.5
3.7
25.9
9.7
1.1
0
1.5
6.8
5.6
4.2
0.3
16.6
45.4
5.8
0
0
0
1.5
3.8
3.3
0.5
0.4
1
4.3
1.8
1.9
32
13.5
1.6
0.1
1
10.5
5.2
2
1.9
10.4
19.2
1.8
20.8
2.8
12.6
3.9
11.6
2.9
14
1.1
12.9
1.6
7.4
1.6
8.3
2.1
12.7
0.8
26.2
0.4
1.9
0.1
3.2
0.1
4.3
0.1
9.4
0.3
1.3
4.9
0.9
11
2.8
23
0.2
1.5
0.5
2.6
0.7
3.5
1.6
7.4
Source: UNCTAD secretariat calculations, based on UN COMTRADE.
a Data for earlier years not available; b Includes SITC 759, 764, 772 and 776
Table 12: Rates of growth of output and employment in China, 1980-2000
1980- 199090
2000
Primary sector
Annual employment growth
2.8
-0.8
Annual Value Added growth
6.2
3.8
Employment elasticity
0.45
-0.21
Secondary sector
Annual employment growth
5.9
1.6
Annual Value Added growth
9.5
13.5
Employment elasticity
0.62
0.12
Tertiary Sector
Annual employment growth
7.9
5.1
Annual Value Added growth
12.2
9.1
Employment elasticity
0.65
0.56
All sectors
Annual employment growth
4.1
1.1
Annual Value Added growth
9.3
10.1
Employment elasticity
0.44
0.11
Source: Chandrasekhar and Ghosh (2007)
Table 13:
India
1980’s
Annual
employment
growth
Annual Value
Added growth
Employment
Elasticities
1990’s
1.50
1.23
5.81
0.26
5.51
0.22
Table 14
Sectoral Employment Elasticities in India
1983 to 1987-88
Agriculture, Hunting,
Forestry and Fishing
0.87
0.70
1993-94 to 19992000
0.01
Mining and Quarrying
1.25
0.59
0.30
2.81
0.87
0.59
0.38
0.63
0.86
0.68
-0.41
0.33
-0.52
0.82
0.62
0.47
0.55
0.63
0.49
0.45
0.64
0.52
0.68
-0.16
0.68
0.52
0.16
Manufacturing
Electricity, Gas and water
Construction
Wholesale and Retail
Trade and Restaurants
and Hotels
Transport, Storage and
Communication
Financing, Insurance,
real Estate and Business
Services
Community, Social and
Personal Services
All sectors
Source: National Account Statistics
1983 to 1993-94
Table 15: Employment elasticities and GDP growth (1991-1995, 1995-1999 and 1999-2003)
Average Annual GDP
Total Employment Elasticity
Growth (%)
1991-
1995-
1999-
1991-
1995-
1999-
1995
1999
2003
1995
1999
2003
China
0.14
0.14
0.17
12.7
8.3
8.1
India
0.4
0.43
0.36
6.3
6.3
5.3
0.34
0.38
0.3
2.9
3.6
3.5
Global Total
Source: Key Indicators of Labour Market 2006
Table 16: Sectoral Employment Elasticities and GDP and Value Added growth rates
Sector Value-added Growth and Total
Growth, 1991-2003 (Average Annual %)
GDP
Agriculture
Industry
Services
Growth
China
3.7
12.5
8.8
9.7
India
2.8
6
7.7
6
2
2.1
3
Global Total
Source: Key Indicators of Labour Market 2006
Table 17: Sectoral shares in GDP and Total Employment
India
1983
38.9
Agriculture,
value added
(% of GDP)
Industry,
24.5
value added
(% of GDP
Services, etc., 36.6
value added
(% of GDP)
Employment
in agriculture
(% of total
employment)
Employment
in industry
(% of total
employment)I
Employment
in services (%
of total
employment
1990
31.3
2003
21
China
1975 1985
32
28
1990
27
1995
20
2000
16.4
2005
13
27.6
26
46
43
41.6
47
50.2
47
41.1
53
22
18
31.3
33
33.4
40
69.1
59.8
77.2
62.4
53.4
52.2
46.3
44.8
13.6
13.7
13.5
20.8
19
23
17.3
23.8
17.3
26.5
9.3
16.8
27.6
24.8
36.4
31.4
Source: World Development Indicators 2006. (Figures in red are estimates from national
accounting sources in case of India)
Table 17a) Annual percentage change in real wages in China
1978
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Average of all
units
6.0
6.1
5.3
-4.8
9.2
4.0
6.7
7.1
7.7
3.8
3.8
1.1
7.2
13.1
11.4
15.2
15.5
12.0
10.5
12.8
State-owned
units
6.2
6.0
4.8
-4.6
9.7
3.2
7.0
5.7
8.7
0.4
2.6
4.2
6.7
12.9
10.9
16.2
16.3
12.3
11.1
13.6
Source : Chandrasekhar and Ghosh (2007)
Urban
collective units
5.1
6.9
6.6
-6.1
6.6
5.6
4.1
5.9
0.2
3.7
0.6
1.7
3.1
9.7
7.6
8.9
12.7
12.2
9.5
13.2
Units of other
ownership type
22.5
-2.3
8.9
10.5
5.3
7.9
1.5
1.4
1.7
3.2
-1.7
11.0
10.9
9.7
9.9
9.3
8.0
10.4
Table 18: Percentage Shares of Employment – China (1990, 2000, 2002)
China
Agriculture, Hunting,
Forestry and Fishing
Mining and Quarrying
Manufacturing
Electricity, Gas and water
Construction
Wholesale and Retail Trade
and Restaurants and Hotels
Transport, Storage and
Communication
Financing, Insurance, real
Estate and Business
Services
Community, Social and
Personal Services
Activities not adequately
defined
1990
2000
2002
53.4
1.4
13.5
0.3
3.8
46.3
0.8
11.2
0.4
4.9
44.1
0.8
11.3
0.4
5.3
4.4
6.5
6.7
2.5
2.8
2.8
0.4
0.6
0.6
2.6
2.8
6.0
17.7
23.7
22.1
Total
Source: INTERNATIONAL LABOUR ORGANIZATION Geneva, LABORSTA Labour Statistics Database
Table 19: Percentage Shares of Employment – India (1983, 1993, 2000)
India
1983
1993
2000
Agriculture, Hunting,
Forestry and Fishing
Mining and Quarrying
Manufacturing
Electricity, Gas and water
Construction
Wholesale and Retail Trade
and Restaurants and Hotels
Transport, Storage and
Communication
Financing, Insurance, real
Estate and Business
Services
Community, Social and
Personal Services
Activities not adequately
defined
68.4
64.8
59.8
0.6
11.2
0.3
2.2
6.3
0.7
11.3
0.4
3.1
7.4
0.6
12.1
0.3
4.4
9.4
2.4
2.8
3.7
0.6
0.9
1.3
7.9
8.6
8.4
0.0
0.0
0.0
Total
100
100
100
Source: INTERNATIONAL LABOUR ORGANIZATION Geneva, LABORSTA Labour Statistics Database
Table 20: Growth Rates of Employment by Economic Activity - China
Economic Activity
China
1990s
1 Agriculture, Hunting, Forestry and Fishing
2 Mining and Quarrying
3 Manufacturing
4 Electricity, Gas and water
5 Construction
6 Wholesale and Retail Trade and Restaurants and Hotels
7 Transport, Storage and Communication
8 Financing, Insurance, real Estate and Business Services
9. Community, Social and Personal Services
10 Activities not adequately defined
Total
-0.23
-3.83
-0.70
3.99
3.89
5.14
2.62
5.01
1.93
4.19
1.21
Source: INTERNATIONAL LABOUR ORGANIZATION Geneva, LABORSTA Labour Statistics Database
Table 21: Growth Rates of Employment by Economic Activity- India
India
Economic Activity
1 Agriculture, Hunting, Forestry and Fishing
2 Mining and Quarrying
3 Manufacturing
4 Electricity, Gas and water
5 Construction
6 Wholesale and Retail Trade and Restaurants
and Hotels
7 Transport, Storage and Communication
8 Financing, Insurance, real Estate and
Business Services
9. Community, Social and Personal Services
10 Activities not adequately defined
Total
1980s
1990s
1.51
-0.34
4.16
2.14
4.50
5.32
-2.85
2.05
-0.88
7.09
3.57
5.04
3.24
6.04
7.18
6.20
2.90
0.55
2.04
0.98
Source: International Labour Organization LABORSTA Labour Statistics Data Base
Table 23: Share of Output to Total Output according to ISIC: 1980s and 1990s
China
1980s
Avg Low
Technology
Avg Med
Technology
Avg High
Technology
Food,
beverages &
tobacco
Textiles,
clothing and
leather
Chemicals,
rubber &
plastic
Basic metals
Machinery
and
equipment
India
1980s
1990s
1990s
0.47
0.45
0.42
0.42
0.53
0.54
0.58
0.57
0.01
0.01
0.00
0.01
0.15
0.14
0.17
0.17
0.16
0.14
0.14
0.14
0.19
0.15
0.14
0.15
0.27
0.16
0.25
0.15
0.23
0.30
0.19
0.21
Source: Nicita A. and M. Olarreaga (2006), Trade, Production and Protection 19762004, World Bank Economic Review 21(1).
Table 24: Share of Employment to Total Employment according to ISIC: 1980s and
1990s
China
India
1980s
1990s
1980s
1990s
Avg Low
Technology
Avg Med
Technology
Avg High
Technology
Food,
beverages &
tobacco
Textiles,
clothing and
leather
Chemicals,
rubber &
plastic
Basic metals
Machinery
and
equipment
0.41
0.45
0.60
0.58
0.57
0.54
0.39
0.42
0.01
0.01
0.01
0.01
0.10
0.08
0.22
0.22
0.15
0.14
0.24
0.22
0.14
0.11
0.21
0.11
0.11
0.12
0.12
0.11
0.35
0.27
0.20
0.21
Source: Nicita A. and M. Olarreaga (2006), Trade, Production and Protection 19762004, World Bank Economic Review 21(1).
Table 25: Growth in manufacturing output according to ISIC: 1980s and 1990s
China
1980s
Avg All
Manufacturing
Avg Low
Technology
Avg Med
Technology
Avg High
Technology
Food,
beverages &
tobacco
Textiles,
clothing and
leather
Chemicals,
rubber &
plastic
Basic metals
Machinery
and
equipment
India
1980s
1990s
1990s
7.39
8.42
8.60
6.55
6.92
6.95
8.83
7.38
7.94
9.93
8.26
4.77
9.05
15.52
8.07
10.27
8.02
7.60
8.77
6.16
5.23
7.86
9.57
8.35
7.51
4.81
8.83
8.87
8.13
10.56
5.83
2.59
11.64
12.65
8.19
7.19
Source: Nicita A. and M. Olarreaga (2006), Trade, Production and Protection 19762004, World Bank Economic Review 21(1).
Table 26: Productivity Growth in Manufacturing according to ISIC: 1980s and 1990s
China
1980s
Avg All
Manufacturing
Avg Low
Technology
Avg Med
Technology
Avg High
Technology
Food,
beverages &
tobacco
Textiles,
clothing and
leather
Chemicals,
rubber &
plastic
Basic metals
Machinery
and
equipment
India
1980s
1990s
1990s
3.38
6.75
6.22
4.99
3.49
5.56
6.56
5.72
2.85
7.85
5.75
3.59
6.91
13.70
5.01
6.76
2.08
3.88
7.28
6.22
2.40
4.08
4.63
2.84
-0.18
1.55
6.07
6.18
5.63
6.21
1.31
4.83
9.81
10.84
5.88
6.05
Source: Nicita A. and M. Olarreaga (2006), Trade, Production and Protection 19762004, World Bank Economic Review 21
Table 27: Employment Growth in Manufacturing according to ISIC: 1980s and 1990s
China
Avg All
Manufacturing
Avg Low
Technology
Avg Med
Technology
Avg High
Technology
Food,
beverages &
tobacco
Textiles,
clothing and
leather
Chemicals,
rubber &
plastic
Basic metals
Machinery
and
equipment
India
3.70
6.16
3.04
2.91
3.34
5.64
2.44
2.99
4.47
7.07
4.08
2.73
2.28
5.82
2.99
3.34
6.06
2.71
1.77
1.92
1.67
7.62
4.80
5.03
6.33
3.77
11.34
11.45
3.92
6.70
4.28
1.27
1.96
5.26
2.22
2.66
Source: Nicita A. and M. Olarreaga (2006), Trade, Production and Protection 19762004, World Bank Economic Review 21(1).