SPECIAL ARTICLE Growth sans Employment: A Quarter Century of Jobless Growth in India’s Organised Manufacturing
K P Kannan, G Raveendran
There has been considerable debate in India about the impact of growth on employment especially in the organised manufacturing sector for different periods since the early 1980s. However, changes in the coverage of the Annual Survey of Industries demand a fresh look at the issue over a longer period. This paper attempts such an analysis for 1981-82 to 2004-05. For the period as a whole as well as for two separate periods – the pre- and post-reform phases – the picture that emerges is one of “jobless growth”, due to the combined effect of two trends that have cancelled each other out. One set of industries was characterised by employment-creating growth while another set by employment-displacing growth. Over this period, there has been acceleration in capital intensification at the expense of creating employment. A good part of the resultant increase in labour productivity was retained by the employers as the product wage did not increase in proportion to output growth. The workers as a class thus lost in terms of both additional employment and real wages in organised manufacturing sector.
An earlier version of this paper was presented by the first author at the First National Technical Consultation on Employment Policy for India organised by the Ministry of Labour, Government of India and the International Labour Office (Sub-regional Office for South Asia), on 21 February 2008, New Delhi. The authors would like to thank Arjun Sengupta, T S Papola, Ajit Ghosh, B N Goldar, Arup Mitra and Sukti Dasgupta for several rounds of discussion on various aspects of the findings of this paper. A special word of thanks is due to Ajaya Kumar Naik for his able computational assistance. However, the authors alone are responsible for errors, if any.
K P Kannan (kannankp123@gmail.com) and G Raveendran are with the National Commission for Enterprises in the Unorganised Sector, New Delhi.
T
According to a study undertaken by the World Bank (1989), the stagnation in factory employment in the 1980s is due to acceleration in product wages as a result of a union push. This view has been negated by Papola (1994), Kannan (1994) and Nagaraj (1994). It has been pointed out by Papola that the increase in labour productivity during the 1980s was much faster than the growth in real wages and, therefore, the latter cannot be a reason for stagnation in employment. He has argued that the decline in employment in cotton textiles and food products, which accounted for a sizeable part of factory employment, was caused by closure of mills due to sickness and rationalisation due to obsolescence. Kannan demonstrated that the increase in product wage in organised manufacturing was lower than labour productivity during 1973 to 1988 although the difference narrowed since the early 1980s. There was no convincing evidence to show that the presence of unions was incompatible with dynamic efficiency, i e, a higher growth in labour productivity as compared to product wage. The decline in dynamic efficiency in some industries could have been due to other factors as industrial sickness (as happened to many textile mills) and supply constraints with regard to certain inputs or problems in capacity utilisation.
Nagaraj argued that there was a decline in the bargaining power of organised workers during the 1980s and the structure of employment within the organised sector moved towards smaller sized establishments. It was, therefore, unlikely that unionised labour secured a disproportionate increase in the wage
march 7, 2009 vol xliv no 10
rate. Nagaraj also found that about one half of real earnings per worker was accounted for by an increase in mandays per worker. The alternative explanations given by Papola (1994), Nagaraj (1994) and Bhalotra (1998) for the stagnation of employment in the organised manufacturing sector in the 1980s are (i) changes in industrial composition, and (ii) increase in actual hours worked per worker indicating a more intensive use of the workforce. Nagaraj has also mentioned the overhang of employment by the end of 1970s caused by a markedly decelerated growth of industrial output but a sustained growth of employment. In the 1980s, when demand picked up, the industries would have first used the existing stock of labour intensively before deciding to employ additional workers.
Kannan (1994) argued that those who advocate a “flexible” labour market without intervention emphasise only the cost dimension of wages and not the demand dimension arising out of its role of providing income to the workers. The narrow base of the domestic market is due to the small size of the organised sector workforce. Hence policies are required to help increase labour productivity in the unorganised sector and thus the income of a vast segment of the workforce to create a bigger and wider base for domestic demand, i e, an argument for expanding the home market.
Introduction
The growth of employment in the organised manufacturing sector during the 1990s has also been analysed by a number of researchers and the general consensus has been that employment growth picked up considerably during the first half of the 1990s. Goldar (2000) has shown that employment in the organised manufacturing sector including electricity registered an impressive annual rate of growth of about 2.83% during 1990-96. The growth was mainly contributed by private and joint sector companies as the growth rate registered by the public sector was only 0.39% as against 3.72% by the other firms. Goldar has also shown that there was a marked change in the size structure of industries, particularly in the 1990s in favour of smaller size classes. While firms the size classes of 50 to 500 employees gained significantly, the size classes of 2000 and above lost their share of employment substantially. This structural change must have contributed to the growth of employment during the 1990s till 1997-98. By using econometric analysis, he has shown that growth in output (GVA) and real wages have a significant influence on growth in employment. He concluded that changes in the size structure of industries in favour of small and medium-sized factories and the slowdown in the growth in real wages were the factors which contributed to employment growth in the 1990s. Nagaraj (2000) has, however, contested the findings of Goldar and attributed the employment growth during the 1990s to the investment boom that was witnessed in response to the industrial deregulation and trade policy reform. In another article in 2004, Nagaraj has also noted that jobless growth during the 1980s was followed by an employment boom for four years during 1992-96 and retrenchment thereafter. Between 1995-96 and 2001-02, 1.3 million employees lost their job. These losses have been widespread across major states and industry groups. Real wages have practically
Economic & Political Weekly
EPW
stagnated, when per capita income grew close to 3% per year during the 1990s. Nagaraj, however, seems to have not taken note of non-coverage of electricity undertakings in the Annual Survey of Industries (ASI) from 1998-99. Nagraj’s conclusions, quite significant as they are, also call for further investigation on a number of counts. First and foremost, there is need to pay attention to some database issues since the ASI has excluded certain industries (mainly departmental undertakings such as electricity and water supply). Second, it is important from a policy point of view to identify industries that have contributed to jobless growth performance of the manufacturing sector as a whole. The question is whether jobless growth is a generalised phenomenon or the net result of the jobless growth industries cancelling out the job creating growth performance of some other industries. All these issues can now be examined for a longer period of time of almost a quarter century.
Scope and Objectives
This is the background against which this paper examines the performance of the organised manufacturing sector. In specific terms, the objectives of this paper are: (i) to examine the longterm growth performance since the beginning of the 1980s by dividing the period into pre- and post-reform years to signify the onset of major economic reforms in the early 1990s for economic liberalisation and globalisation, (ii) to examine the employment implications of growth performance in terms of growth in employment as well as the resultant employment elasticities so as to further probe the “jobless growth” phenomenon reported for earlier but shorter periods, (iii) to subject the examination of the growth and employment performance in terms of industry-groups at the 2-digit level to find if there are any discernible patterns, (iv) to examine the changes in the distribution of income arising out of the growth as between capital and labour, and finally (v) to explore the causes underlying the performance of the organised manufacturing sector and put forward certain plausible hypothesis. Some comments on the larger implications to the economy are also offered for further discussion.
The Data Sets for the Present Study
The present study is aimed at analysing the growth trends in organised manufacturing at disaggregated levels. The published results of the ASI from 1981-82 to 2004-05 at the 3-digit level of industrial classification were used for the study. Since the industrial classification used for the surveys up to ASI 1988-89 it was NIC-70 and up to ASI 1997-98 it was NIC-87 and thereafter NIC-98, the concordance between NIC-70 and NIC-87 with NIC-98 at the 3-digit level was used to convert the data sets into NIC-98. The estimates at the 2-digit level of industry classification were then obtained by aggregating the relevant 3-digit level industries. The total employees, including contract workers, supervisory and managerial staff, other employees and unpaid family workers, were considered for the analysis. The workforce is not collected in ASI as a direct headcount of the persons in the firm but the average is calculated by dividing the number of mandays worked with the number of working days.
All the monetary values given here were adjusted for 1993-94 prices by using the Wholesale Price Index (WPI) numbers relevant to specific industry groups at the 2-digit level. The choice of 1993-94 prices was also a matter of convenience as it is one of the middle years on which the earlier series of national accounts were based.1
Changes in the Sampling Design and Coverage
There were significant changes in the classification, sampling and coverage of industrial units in the ASI over different periods of time. Till ASI 1986-87, all large establishments employing 50 or more workers and using power or 100 or more workers without using power and electricity undertakings constituted the “Census Sector” and the remaining establishments constituted the “Non-Census or Sample Sector”. In the case of the sample sector, 50% of the establishments were surveyed every year, covering all the units once in two years. However, in the case of industries in which the total number of units in the country did not exceed 50 and the units were located in relatively less industrialised states2 the manufacturing units were surveyed completely every year. In the case of other establishments, the units with odd serial numbers were surveyed in the first year and those with even numbers during second year, after stratifying by industry and district and arranging in descending order of employment.
From ASI 1987-88 to ASI 1996-97, the Census sector comprised all the units employing 100 or more workers, irrespective of the use of power, and all electricity undertakings. Out of the remaining units, if the number of factories at the 3-digit level of NIC in a state was 20 or less, those units were completely enumerated. Further, the units located in 12 relatively less industrialised states and union territories (UTs) (see Note 2) were also completely enumerated every year. From amongst the remaining units in each industry in each state, one-third of the units subject to a minimum of 20 were selected circular systematically for survey every year. All the units were surveyed once in three years.
For ASI 1997-98 the Census Sector was redefined to consist of the following: (i) The units belonging to all the 12 less industrialised states/UTs, (ii) in the case of other 16 States/UTs: (a) units having 200 or more workers, (b) significant industries in terms of NVA as reflected in ASI 1993-94, ASI 1994-95 and ASI 1995-96 results, and
(c) all units belonging to the public sector undertaking (PSU) and the electricity sector.
All the remaining units were included in the sample sector. The sample size at the all-India level was determined on the basis of variability of specific industry group and further allocated to different states on a proportional basis.
In ASI 1998-99, a number of modifications were made to the design adopted in ASI 1997-98. These are: (i) the number of completely enumerated states/UTs was reduced to Manipur, Meghalaya, Nagaland, Tripura and Andaman and Nicobar Island, (ii) NIC-1998 was introduced for industry classification, (iii) electricity undertakings registered with Central Electricity Regulatory Authority were excluded, and (iv) public sector units were not considered as Census only.
In ASI 1999-2000, the same methodology was used except that the concept of significant units was not used for the identification of census sector units. It was also decided to exclude departmental undertakings like railway workshops, P&T workshops, etc, from the survey. However, in practice, the sampling frame did include the departmental undertakings.
From ASI 2000-01 to ASI 2003-04, the census sector was modified to include units employing 100 and more workers instead of 200 and more workers. In ASI 2004-05, NIC 2004 was introduced and a complete change in sampling design was made. These related to: (i) the units employing 100 or more workers were included in the census sector, (ii) each 4-digit level industry in each state is considered as a stratum, (iii) sampling has been done for each of the years 2004-05 to 2008-09 so that all the units are surveyed during the five-year period, and (iv) a supplementary frame has to be prepared every year and samples have to be selected.
Though the change of sampling design over successive rounds would have introduced some amount of design effect, the unbiased character of the estimates are not expected to be affected, except from ASI 1998-99 onwards when significant changes were introduced in coverage. For example, electricity undertakings were excluded since 1998-99 and departmental undertakings were excluded since ASI 1999-2000. The use of published results for estimating growth and elasticity has to be, therefore, industryspecific taking into account the coverage changes.
The period of 23 years from 1981-82 to 2004-05 has been divided into the pre-reform period up to 1991-92 and the postreform period from 1992-93 onwards for the purpose of the analysis. The division is guided by the initiation of major and wideranging reforms of economic liberalisation in the country in 1991-92. The focus of the analysis is primarily on manufacturing industries as per NIC-98, as there have been significant changes in the coverage of ASI in the case of industries not classified as manufacturing. The industries which are grouped together and are not considered as part of manufacturing are given in Table 1.
Table 1: Industries Excluded from the List of Organised Manufacturing in this Study
NIC Code Description
14 Extraction of salt
40 Electricity, gas, steam and hot water
| 41 50 | Collection, purification, and distribution of water Sale, maintenance and repair of motor vehicles |
| 52 | Retail trade except motor vehicles and motorcycles: repair of personal and |
| household goods | |
| 63 | Storage and warehousing |
| 72 | Maintenance and repair of office, accounting and computing machinery |
| 90 | Sewage and refuse disposal, sanitation and similar activities |
| 92 | Recreational, cultural and sporting activities |
| 93 | Other service activities |
In addition to the above, the industry, Recycling (NIC-37) was also grouped along with non-manufacturing activities, as the industry group was not covered prior to 1998-99.
Growth, Employment and Employment Elasticity
The performance of the organised manufacturing for the two time periods as well as the combined period of nearly a quarter century with regard to output (gross value added), employment and the resultant employment elasticity are given in Table 3 (p 83) and Tables 4, 5 (p 84).
march 7, 2009 vol xliv no 10
The average annual growth of employment in the manufacturing industries during the period from 1981-82 to 2004-05 was 0.78%. During the pre-reform period from 1981-82 to 1991-92, the employment growth rate in manufacturing industries was 0.40% while it marginally increased to 0.63% during the postreform period from 1992-93 to 2004-05.
What is important to note is that a majority of industries – 16 out of 22 – registered positive employment growths during the first period 1981-82 to 1991-92. But this declined to 12 in the second period. However, the employment growth in the first period was strong enough to show a positive growth in 15 industry groups for the whole period. Six industry groups showed a decline in employment but this increased to 12 in the post-reform period. Whether this is indicative of a polarisation of the manufacturing sector in terms of “job creating” and “job displacing” ones even while they continue to grow in terms of output is something that we shall return to later in the discussion.
As can be seen from Figure 1, the employment growth scenario for a period close to a quarter of a century analysed here is not one of continuous stagnation but marked by a period of net increase (roughly from 1987-88 to 1997-98) preceded and succeeded by periods of net decline. Whether the recovery in 2004-05 to the level of 1996-97 is the beginning of a turnaround to sustained employment growth is something we cannot now say given the diverging tendencies of industries. During the whole period of 24 years a mere 1.77 million jobs were created while 0.42 million jobs were destroyed with a net job creation of around 1.35 million. This works out to just 0.3% of the workforce in the economy as on 2004-05. The “excluded industries” accounted for around 12 to 16% of total employment. As such the manufacturing group considered here accounted for 84 to 88% of
Figure 1: Total Employment, Supervisory Staff and Workers (1981-82 to 2004-05, in lakhs) 100
80 60 Workers Total persons engaged 40
20 Supervisory staff
0 1981-82 1984-85 1987-88 1990-91 1993-94 1996-97 1999-2000 2002-03 2004-05
total employment in organised manufacturing including industries that are now excluded.
Unlike the employment scenario, the growth scenario is indeed a buoyant one. All the 22 industry groups examined here showed positive growth of 7.4% per annum for the whole period as well as the second period relating to post-reform. The pre-reform period witnessed only a marginally lower growth rate of around 7% mainly due to the negative growth rates of two industries. In fact, one of them – Medical, Precision and Optical Instruments – rebounded in the second period and registered a growth rate of more than 14%. Therefore, in terms of output growth, all the manufacturing industries seem to have
Economic & Political Weekly
EPW
done quite well with many of them registering double digit growth rates during the post-reform period. Unlike in the case of employment no polarisation is discernible.
Making Sense of Employment Elasticities
Employment elasticity expresses the percentage change in employment growth for a percentage change in growth of output. For the pre- and post-reform periods as well as the combined period we have calculated the employment elasticities for organised manufacturing as a whole and for individual industry groups at the 2-digit level. It must, however, be noted that employment elasticities cannot be used or interpreted uncritically because some of them are meaningless and some of them are not useful. We therefore classify employment elasticities as in Table 2.
In these possible outcomes A2 is clearly meaningless because the industry is declining and the positive sign is due to the double
Table 2: Possible Outcomes in the Sign of Employment Elasticity (EE) and Their Meaning
A EE Positive B EE Negative C EE Zero/Close to Zero
A1 Growth in both B1 Positive growth in C1 Positive growth in employment and output output but negative output but no growth in employment growth or decline in employment
| A2 Growth both in | B2 Positive growth in | C2 No growth or decline |
|---|---|---|
| employment and output | employment but | in employment |
| negative (declining | negative growth in | and output |
| industry) | output |
Table 3: Growth in Output and Employment and Employment Elasticities in Period I
(in average annual %, 1981-82 to 1991-92)
NIC Industry Name Growth in Growth in Employment Code Gross Value Employment Elasticity Added (Arc)
A Employment creating growth 16 Tobacco products 9.10 1.37(58.6) 0.15
18 Wearing apparel, dressing and dyeing of fur 22.53 9.61(76.9) 0.43
19 Leather tanning and dressing 10.74 5.65(49.3) 0.53
21 Paper and paper products 4.69 0.90(12.6) 0.19
23 Coke, refined petro products and nuclear fuel 10.47 2.15(11.1) 0.20
24 Chemicals and chemical products 9.77 2.41(130.6) 0.25
25 Rubber and plastic products 13.42 3.89(57.9) 0.29
26 Other non-metallic mineral products 12.82 2.17(89.7) 0.17
27 Basic metals 2.20 0.23(13.6) 0.10
28 Fabricated metal products 4.51 1.36(36.3) 0.30
29 Machinery and equipments 7.29 2.99(119.2) 0.41
30 Office, accounting and computing machinery 35.92 14.89(22.7) 0.41
31 Electrical machinery and apparatus 6.67 0.46(11.1) 0.07
32 Radio, TV and communication equipment 23.28 7.92(62.9) 0.34
34 Motor vehicles, trailers, etc 6.09 0.87(15.8) 0.14
36 Furniture, manufacturing nec 7.77 1.33(7.5) 0.17
Total of A 7.93 2.07(775.9) 0.26
B Employment displacing growth 15 Food products and beverages 8.75 -1.71(-215.8) -0.20
17 Textile 4.33 -1.37(-200.6) -0.32
20 Wood and products of wood and cork 5.48 -2.00(-13.3) -0.37
35 Other transport equipment 2.27 -0.69(-21.7) -0.30
Total of B 5.58 -1.45(-451.5) -0.26
C Neither growth nor employment 22 Publishing, printing, etc -0.02 -0.89(-13.8) 57.31
33 Medical, precision and optical instruments -4.48 -6.89(-30.0) 1.54
Total of C -0.84 -2.19(-43.7) 2.62
All manufacturing 6.97 0.40(280.6) 0.06
The absolute change in employment (in ‘000) is given in brackets. Source: Annual Survey of Industries, Summary Results for Factory Sector.
| negative signs. B2 is useless because employment is retained even | the first period. This resulted in an employment elasticity of just | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| when the industry concerned is declining in terms of output. C2 | 0.09. Even this marginal increase is mainly due to the perfor | ||||||||
| is also not useful since it is a case of stagnation. Based on this | mance in the last year of the second period, i e, 2004-05. Other | ||||||||
| classification the results of our exercise are given in Tables 3 to 5. | wise the employment elasticity would have been a lower one of | ||||||||
| The 2-digit level industry employment elasticities present a | 0.01. Figure 1 illustrates this point clearly. Industries shed jobs | ||||||||
| differentiated picture. During the pre-reform period 16 out of 22 | that increased to 10 from the earlier six and together they ac | ||||||||
| industry groups showed positive employment elasticities arising | counted for 43% of the total employment in 1992-93. | ||||||||
| out of what we call “employment creating growth”. These varied | For the whole period of 24 years, the picture is somewhat | ||||||||
| from a high of 0.53 in Leather Tanning and Dressing to a low of | brighter from an employment point of view because the employ | ||||||||
| 0.10 in Basic Metals. We may recall here that limited economic | ment elasticity inched up to 0.10. However, this is as good or | ||||||||
| reforms in capacity utilisation, broad-banding and so on were ini | bad as jobless growth since the total employment effect was | ||||||||
| tiated during the 1980s that confined to internal economic re | only 8.29 million in 2004-05 which is less than the peak of | ||||||||
| form. The main reason for hardly any growth in employment | 8.78 million in 1995-96. | ||||||||
| during this period is due to the performance of six industry | The picture emerging from the employment elasticities is one | ||||||||
| groups who accounted for more than half the employment in the | of acceleration in capital intensification in organised manufac | ||||||||
| beginning of the period. Therefore a majority of the industries | turing at the expense of creating employment. While we must | ||||||||
| which performed well, both in terms of employment and output | recognise that this is not a generalised phenomenon across all | ||||||||
| growth, accounted for only a relatively small share of total em | industry groups, but the net effect of employment creating | ||||||||
| ployment to begin with. What is striking is the job loss in two | growth in | some | industries and the employment displacing | ||||||
| major industry groups, viz, Food Products and Beverages and | growth of another group. While the increase in number of such | ||||||||
| Textiles which together accounted for 42% of the employment | individual groups should be a matter of concern, their decreasing | ||||||||
| share. This has resulted in an employment elasticity of just 0.06 | share in employment holds a ray of hope. | ||||||||
| which is close to zero. | The main points arising from the analysis so far may be | ||||||||
| Despite a higher rate of growth in output during the post | summed up as follows. First, the higher growth in organised | ||||||||
| reform period, the growth in employment witnessed only a very | manufacturing both during the pre- and post-reform periods is | ||||||||
| marginal improvement to 0.63% per annum as against 0.40% in | due to an increase in labour productivity. Second, the process | ||||||||
| Table 4: Growth in Output and Employment and Employment Elasticities in Period II | Table 5: Growth in Output and Employment and Employment Elasticities Over the | ||||||||
| (in average annual %, 1992-93 to 2004-05) | Larger Period (in average annual %, 1981-82 to 2004-05) | ||||||||
| NIC | Industry Name | Growth in | Growth in | Employment | NIC | Industry Name | Growth in | Growth in | Employment |
| Code | Gross Value | Employment | Elasticity | Code | Gross Value | Employment | Elasticity | ||
| Added | (Arc) | Added | (Arc) | ||||||
| A | Employment creating growth | A | Employment creating growth | ||||||
| 15 | Food products and beverages | 5.11 | 0.47(73.0) | 0.09 | 16 | Tobacco products | 6.80 | 0.71(70.9) | 0.10 |
| 18 | Wearing apparel, dressing and dyeing of fur | 10.60 | 9.58(300.0) | 0.90 | 18 | Wearing apparel, dressing and dyeing of fur | 15.55 | 9.92(399.0) | 0.64 |
| 19 | Leather tanning and dressing | 3.49 | 2.28(35.5) | 0.65 | 19 | Leather tanning and dressing | 6.93 | 3.54(82.5) | 0.51 |
| 21 | Paper and paper products | 4.45 | 1.13(22.4) | 0.25 | 21 | Paper and paper products | 3.84 | 1.24(44.0) | 0.32 |
| 23 | Coke, refined petro products and nuclear fuel | 9.24 | 1.33(11.6) | 0.14 | 23 | Coke, refined petro products and nuclear fuel | 11.58 | 2.31(32.5) | 0.20 |
| 24 | Chemicals and chemical products | 5.60 | 1.33(115.2) | 0.24 | 24 | Chemicals and chemical products | 8.30 | 2.11(299.7) | 0.25 |
| 25 | Rubber and plastic products | 9.08 | 3.62(105.7) | 0.40 | 25 | Rubber and plastic products | 11.28 | 3.96(179.8) | 0.35 |
| 26 | Other non-metallic mineral products | 7.94 | 0.99(58.3) | 0.12 | 26 | Other non-metallic mineral products | 8.62 | 1.47(149.1) | 0.17 |
| 28 | Fabricated metal products | 3.83 | 0.98(35.3) | 0.26 | 28 | Fabricated metal products | 3.77 | 1.06(68.6) | 0.28 |
| 33 | Medical, precision and optical instruments | 13.79 | 5.03(27.6) | 0.37 | 29 | Machinery and equipment | 7.25 | 1.01(90.0) | 0.14 |
| 34 | Motor vehicles, trailers, etc | 13.86 | 4.46(137.2) | 0.32 | 30 | Office, accounting and computing machinery | 19.69 | 5.50(18.3) | 0.28 |
| 36 | Furniture, manufacturing nec | 11.44 | 8.05(106.6) | 0.70 | 32 | Radio, TV and communication equipment | 15.34 | 2.72(47.0) | 0.18 |
| Total of A | 7.38 | 2.07(1028.5) | 0.28 | 33 | Medical, precision and optical instruments | 6.37 | 0.24(3.3) | 0.04 | |
| B | Employment displacing growth | 34 | Motor vehicles, trailers, etc | 9.90 | 2.91(162.7) | 0.29 | |||
| 16 | Tobacco products | 5.06 | -0.35(-20.4) | -0.07 | 36 | Furniture, manufacturing nec | 8.06 | 5.37(123.3) | 0.67 |
| 17 | Textile | 5.34 | -0.15(-24.8) | -0.03 | Total of A | 8.64 | 2.26(1770.8) | 0.26 | |
| 20 | Wood and products of wood and cork | 0.31 | -2.15(-15.1) | -6.94 | B | Job displacing growth | |||
| 22 | Publishing, printing, etc | 1.69 | -2.28(-36.8) | -1.35 | 15 | Food products and beverages | 6.50 | -0.06(-20.2) | -0.01 |
| 27 | Basic metals | 8.88 | -1.19(-89.4) | -0.13 | 17 | Textile | 4.96 -0.53(-178.9) | -0.11 | |
| 29 | Machinery and equipments | 7.33 | -1.21(-68.6) | -0.16 | 20 | Wood and products of wood and cork | 0.09 | -1.57(-22.2) | -16.55 |
| 30 | Office, accounting and computing machinery | 7.29 | -2.46(-9.0) | -0.34 | 22 | Publishing, printing, etc | 0.35 | -1.44(-45.8) | -4.07 |
| 31 | Electrical machinery and apparatus | 6.24 | -0.57(-16.8) | -0.09 | 27 | Basic metals | 7.13 | -0.09(11.8) | -0.01 |
| 32 | Radio, TV and communication equipment | 9.62 | -1.62(-22.1) | -0.17 | 31 | Electrical machinery and apparatus | 6.46 | -0.03(-1.5) | -0.00 |
| 35 | Other transport equipment | 10.63 | -4.13(-121.9) | -0.39 | 35 | Other transport equipment | 6.79 | -2.44(-141.5) | -0.36 |
| Total of B | 7.41 -0.93(-424.9) | -0.13 | Total of B | 6.05 -0.45(-421.9) | -0.07 | ||||
| All manufacturing | 7.39 | 0.63(603.6) | 0.09 | All manufacturing | 7.41 | 0.78(1348.9) | 0.10 | ||
| The absolute change in employment (in ‘000) is given in brackets. | The absolute change in employment (in ‘000) is given in brackets. | ||||||||
| Source: Annual Survey of Industries, Summary Results for Factory Sector. | Source: Annual Survey of Industries, Summary Results for Factory Sector. | ||||||||
| 84 | march 7, 2009 | vol xliv no 10 | Economic & Political Weekly |
EPWof jobless growth is not uniform across industries. In fact, there is a divergence in the situation with one set of industries able to register employment creating growth while another set registering jobless growth. Since they cancel each other out, the performance of the organised manufacturing as a whole has been a dismal one. Third, the jobless growth phenomenon has been going on for far too long a period, i e, almost a quarter of a century. Fourth, the jobless growth process has profound implications for the distribution of the gross surplus as between capital and labour. If labour has not benefited in terms of expanded employment opportunities, has it benefited in terms of wage share as well as real wages? We turn to this question in the following section.
Trends in Labour Productivity and Share of Wages
When an industry grows, it could result in greater employment as a result of expansion of capacity resulting in creating more employment to the workers as a class. Or, it could result in higher wages if growth is the result of increasing capital intensity. Both these are also possible depending on the character of the techno logy as well as the extent of the sharing of the value added as between capital and labour. The case of organised manufacturing examined here is one of jobless growth. The share of wages has fallen sharply indicating a fall in product wage
Table 6: Percentage Share of Gross Value Added (GVA) and Employment in Organised Manufacturing
NIC Description 1981-82 1992-93 2004-05 Code GVA Employ-GVA Employ-GVA Employ ment ment ment
A Employment creating growth 27 Basic metals 16.0 8.5 12.8 8.7 18.9 7.0
24 Chemicals and chemical products 12.9 7.0 19.1 8.7 16.6 9.5
15 Food products and beverages 8.7 19.6 9.3 16.5 7.3 16.2
28 Fabricated metal products 4.7 3.6 3.2 3.7 2.3 3.9
34 Motor vehicles, trailers, etc 4.3 2.5 3.6 2.6 6.7 4.1
26 Other non-metallic mineral products 4.2 5.4 5.1 6.1 5.0 6.3
21 Paper and paper products 3.1 1.9 2.0 2.0 1.5 2.1
23 Coke, refined petroleum products and nuclear fuel 2.9 0.7 5.7 0.9 11.4 1.0
25 Rubber and plastic products 1.7 1.8 3.1 2.6 3.0 3.7
36 Furniture, manufacturing nec 1.2 0.8 0.9 0.9 1.4 2.1
33 Medical, precision and optical instruments 1.1 0.8 0.4 0.4 0.9 0.7
19 Leather tanning and dressing 0.7 1.0 0.9 1.5 0.5 1.8
18 Wearing apparel, dressing and dyeing of fur 0.4 0.7 1.5 2.0 1.7 5.4
Total of A 61.9 54.3 67.6 56.6 77.2 63.8
B Job displacing growth 16 Tobacco products 1.6 5.8 1.8 6.4 1.7 5.7
17 Textile 14.4 22.4 10.7 18.2 6.7 16.6
20 Wood and products of wood and cork 0.8 1.0 0.4 0.9 0.2 0.6
22 Publishing, printing, etc 4.0 2.3 1.6 2.0 1.2 1.4
29 Machinery and equipment 6.4 5.0 6.3 6.6 5.1 5.3
30 Office, accounting and computing machinery 0.1 0.1 1.0 0.5 0.5 0.3
31 Electrical machinery and apparatus 5.3 3.4 4.9 3.3 2.9 2.9
32 Radio, TV and communication equipment 0.7 0.8 2.6 1.6 1.6 1.2
35 Other transport equipment 5.0 4.7 3.1 4.0 2.9 2.2
Total of B 38.3 45.5 32.4 43.5 22.8 36.2
Total manufacturing 100.0 100.0 100.0 100.0 100.0 100.0
Economic & Political Weekly
EPW
Figure 2: Index of Output of Emoluments in Organised Manufacturing Industries
(1981-82 = 100, Index of GVA employment and emolument) 600
500 400 300 200 100 Emoluments GVA 0 1981-82 1984-85 1987-88 1990-91 1993-94 1996-97 1999-2000 2002-03 2004-05
Figure 3: Share of Total Emoluments of Employees, Wages of Workers and Wages of Supervisors (as % of Gross Value Added)
45 Other than wages
35 25 15 Wages Total emoluments 0
1981-82 1984-85 1987-88 1990-91 1993-94 1996-97 1999-2000 2002-03 2004-05
(i e, share of wages in the value added per worker) which is the relevant element of cost of labour in production. However, it is also important to examine the wage as real wage to workers representing its purchasing power or income.
When organised manufacturing as a whole grows at an annual growth rate of 7.4% for nearly a quarter century what it means is that it has increased its output by more than five times. This could be compared with the increase in share of wages that represents the “product wage”. There was hardly any significant increase in employment except for a short interim period from 1989-90 to 1995-96. The aggregate results are worth noting. As we can see in Figure 2, while output grew by more than five times, the total emoluments paid to employees (wages to workers and supervisory staff combined) grew only by a little more than two and three quarter times (i e, 277%). This means that a good part of the productivity increase – a doubling of labour productivity measured by GVA per employee – was retained by employers. The increase in total emoluments being less than the increase in output resulted in a sharp decline in the share of wages from 41% in 1981-82 to around 32% in 1991-92 and then to around 25% in 2004-05.
There is a sub-text in this story of a steady decline in the share of wages. As we noted above the total emoluments paid called share of wages can be split into two categories, i e, share of wages to workers and the share of wages to the supervisory (including managerial) staff. Two things seem to have happened. First, the share of wages of workers declined from around 27% in 1981-82 to 21% in 1991-92 and to 12% 2004-05. Second, the share of wages of supervisors declined from 14.5 in 1981-82 to 12% in 1991-92 and remained at that level up to 2004-05 (Figure 3). What this tells us is that the decline in the share of wages of workers has been far in excess of the decline in the share of wages to supervisors. The workers’ share went down by half whereas the supervisors’ share went down by less than one-fourth. The share of supervisory (including managerial) staff in total employees remained more or less constant around 22 to 23% throughout the whole period. On the whole the evidence suggests that much of the decline in the share of wages has been at the expense of the low paid blue-collar workers.
The industry-wise details of the fall in share of wages to all employees as well as workers are a generalised phenomenon across industries during the whole period. The only exception seems to be Wearing Apparel, Dressing and Dyeing of Fur where the sharp decline during the first period has been reversed during the second period. This could be due to the dismantling of the Multi Fibre Agreement governing the export of apparels. The sharpest fall has been in six industry groups, viz, Coke, Refined Petroleum Products and Nuclear Fuel, Basic Metals, Other Transport Equipment, Tobacco Products, Other Non- Metallic Minerals, and Office, Accounting and Computing Machinery, in that order.
The industry-wise picture also show that the fall in share of wages to workers has been much faster than share of wages to supervisors across industries. The picture emerging is one that is loaded against the interests of workers who are either
Table 7: Share of Emoluments to Employees, Wages to Workers and Wages to Supervisors in Gross Value Added (in %)
NIC Description Total Emoluments/GVA Total Wages of Worker/ Code GVA
1981-82 1991-92 2004-05 1981-82 1991-92 2004-05
15 Food products and beverages 38.7 33.7 29.1 24.3 21.6 16.2
16 Tobacco products 55.2 31.6 19.6 45.0 27.9 15.4
17 Textile 56.7 48.0 36.0 45.8 38.3 24.3
18 Wearing apparel, dressing and dyeing of fur 44.8 21.8 44.3 30.7 14.9 27.6
19 Leather tanning and dressing 51.8 36.3 41.8 38.2 25.8 26.8
20 Wood and products of wood and cork 40.3 32.9 37.9 28.7 24.0 22.2
21 Paper and paper products 38.9 29.1 30.1 24.8 19.5 17.4
22 Publishing, printing, etc 58.9 47.7 34.8 36.4 30.0 12.6
23 Coke, refined petroleum products and nuclear fuel 15.7 13.2 4.4 8.8 8.3 2.4
24 Chemicals and chemical products 30.3 24.1 17.8 15.2 13.4 7.0
25 Rubber and plastic products 38.5 24.7 24.3 23.2 15.0 12.7
26 Other non-metallic mineral products 42.1 20.8 19.1 28.9 14.1 10.6
27 Basic metals 36.2 29.1 12.5 23.8 18.4 6.8
28 Fabricated metal products 41.1 36.0 34.5 19.3 21.8 18.3
29 Machinery and equipment 42.1 41.0 32.0 23.7 24.2 14.1
30 Office, accounting and computing machinery 54.5 21.8 25.5 31.2 8.2 6.6
31 Electrical machinery and apparatus 37.8 34.9 28.9 20.8 18.6 13.5
32 Radio, TV and communication equipment 50.2 25.2 28.4 26.8 12.5 9.6
33 Medical, precision and optical Instruments 41.6 38.9 26.5 20.8 20.8 10.9
34 Motor vehicles, trailers, etc 37.3 35.9 21.5 22.1 22.7 11.1
35 Other transport equipment 67.9 55.5 23.2 47.4 37.8 12.1
36 Furniture, manufacturing nec 47.7 34.7 31.5 31.6 24.4 19.0
All manufacturing 42.4 32.3 22.7 27.5 21.0 11.8
40+ Non-manufacturing 34.7 27.8 16.4 22.1 17.8 7.8
Total ASI 41.1 31.6 22.6 26.6 20.5 11.7
semi-skilled or skilled but generally with lower educational attainments and engaged in manual work relating to production, transportation, etc.
Increasing Capital Intensity
Having found that employment elasticity is very close to zero in organised manufacturing in India despite a trend rate of growth of output of over 7% during the last quarter century, what emerges is the indisputable fact that there has been a consistent increase in labour productivity. We now investigate the extent of the increase in labour productivity during the two periods for the different industry groups and go into the factors behind such an increase. When capital is substituted for labour, it leads to an increase in labour productivity. However, if the growth in labour productivity is equal to the growth in capital labour ratio (capital intensity) and no decline in capital productivity then the situation is characterised as technological upgradation. If there is positive growth in capital productivity, then part of the growth in labour productivity is due to substitution of capital for labour as another part due to increased efficiency arising out of technological upgradation. What we find here is a case of sustained increase in capital intensity that has resulted in substitution of capital for labour as well as technological upgradation for organised manufacturing as a whole. However, there are notable variations when we examine the 22 industrial groups.
This takes us first and foremost to the question of measurement of capital. In economic theory, the measurement of capital has been a controversial theme. Measuring capital stock poses too many inherent problems such as the age-composition, technological changes embodied in newer capital equipments and so on. However, scholars engaged in empirical research have to resort to some measurement of capital by choosing from feasible alternatives. While examining the performance of organised manufacturing in India, Ghose (1994) adopted a method by using the estimates of net capital stock prepared by the Central Statistical Organisation (CSO) for broad sectors of the economy at 1980-81 prices. The estimates for the ASI sectors “Aggregate Industry” and “Manufacturing” were available for the year 1973-74. The estimates for individual industries were derived for the year 1973-74 by using the ratio of book value of net fixed capital of the industry to the total book value of all the industries in the manufacturing sector. The estimates of capital consumption computed by the CSO for the years 1980-81 to 1988-89 were then regressed against the corresponding values of gross capital stock and the coefficient
6.05 was taken to measure the standard rate of depreciation. The NCS for subsequent years were then estimated by using the following formula
NCSt+1 = d[NCS + (NCS* – NCS*) + DPt+1]
tt+1t
where NCS = net capital stock
NCS* = book value of net fixed capital reported in ASI
deflated by GDP deflator for Gross Fixed Capital Formation
(1980-81=100)
DP = Value of depreciation reported in ASI deflated by the
same deflators
d = estimated standard rate of depreciation
march 7, 2009 vol xliv no 10
The NCS employed in any particular year is then taken as the sector. Further, the gross fixed capital formation for each year average of the preceding and the current year from 1979-80 was obtained by adding the share of depreciation of fixed capital addition during the year to the net fixed capital
(NCSt+1 + NCS)
t
NCSt+1 = formation. For the years prior to 1979-80, gross fixed capital for2
mation was computed by using the total depreciation and depre-
The limitation of his method is that the industry-wise net ciation rates of 1980-81. The wholesale price indices of manufaccapital stock for 1973-74 was derived by using the share of book turing sector were used for obtaining the estimates of gross fixed value of net fixed capital which is a crude approximation. Fur-capital formation at 1993-94 prices. The depreciation rates for ther, the depreciation rate has been derived externally for all the different years as computed from ASI data were used for obtainindustries taken together by using a regression analysis of the ing net fixed capital stock for different years. The methodology data sets of just eight years. It has nothing to do with the actual that we have used is given in the Appendix. depreciation provided by specific industry groups. We discuss the results, given in Tables 8, 9 and Table 10 (p 88),
Goldar (2004) adopted the perpetual inventory method in by keeping the broad division of industries as between “Employwhich he constructed the series of gross investment in fixed ment Creating Growth” and “Employment Displacing Growth”. capital for the entire manufacturing sector at constant prices of During the first period there has been a modest growth in NCS of 1981-82. It was done by subtracting the book value of fixed assets around 1%. However this has resulted in an impressive growth in the previous year from that in the current year and adding to in labour productivity (O/L) of 5.8% largely contributed by an that the reported depreciation in fixed assets in the current year. equally impressive growth in capital productivity (O/K). Capital The implicit price deflators of gross fixed capital formation in intensity (K/L) increased by around 4.3% per year. Given the limited registered manufacturing sector were used for converting gross and internal economic reforms, it could be hypothesised that the investment to constant prices. A constant depreciation of 5% was impressive growth in labour productivity could be due to a better assumed for obtaining net fixed capital. and higher utilisation of capital and additional capital infusion. In this paper, we have used a similar methodology, at the This might have also been accompanied by better management 2-digit industry level rather than for the aggregate manufacturing and related internal efficiency. This period in fact witnessed the creation of 7,76,000 new jobs and displacement of 4,95,000
Table 8: Growth Rate of Net Capital Stock (NCS), Labour Productivity (O/L), Capital
jobs resulting in a net employment creation of just 2,81,000
Productivity (K/L) and Capital Intensity (O/K) in the Organised Manufacturing during 1983-84 and 1991-92 Table 9: Growth Rate of Net Capital Stock (NCS), Labour Productivity (O/L), Capital
NIC Description 1991-92 to 1983-84
Productivity (K/L) and Capital Intensity (O/K) in the Organised Manufacturing during
2- Digit NCS O/L K/L O/K
1992-93 and 2004-05
A Employment creating growth NIC Description 2004-05 to 1992-93 16 Tobacco products 9.5 5.84 7.68 -1.71 2- Digit NCS O/L K/L O/K
18 Wearing apparel, dressing and dyeing of fur 17.8 14.57 6.02 8.07 A Employment creating growth 15 Food products and beverages 6.02 4.62 5.52 -0.86
19 Leather tanning and dressing -1.4 1.99 -7.49 10.25 18 Wearing apparel, dressing and dyeing of fur 15.16 0.93 5.09 -3.96
21 Paper and paper products -0.2 7.10 -1.07 8.25 19 Leather tanning and dressing 9.70 1.19 7.26 -5.66
23 Coke, refined petroleum products and nuclear fuel -2.1 16.63 -4.64 22.30 21 Paper and paper products 16.84 3.29 15.54 -10.60
24 Chemicals and chemical products 8.4 5.92 5.93 -0.01 23 Coke, refined petroleum products and nuclear fuel 15.48 7.81 13.97 -5.40
25 Rubber and plastic products 8.3 7.70 5.11 2.46 24 Chemicals and chemical products 7.24 4.21 5.83 -1.53
26 Other non-metallic mineral products 7.0 10.43 6.08 4.10 25 Rubber and plastic products 10.55 5.27 6.69 -1.33
27 Basic metals 6.6 5.00 10.46 -4.94 26 Other non-metallic mineral products 9.53 6.89 8.46 -1.45
28 Fabricated metal products -1.8 3.07 -3.19 6.46 28 Fabricated metal products 7.16 2.82 6.12 -3.11
29 Machinery and equipments 5.8 2.75 2.80 -0.05 33 Medical, precision and optical instruments 5.39 8.34 0.34 7.98
30 Office, accounting and computing machinery 12.7 17.01 -6.05 24.54 34 Motor vehicles, trailers, etc 8.64 9.00 4.00 4.80
31 Electrical machinery and apparatus 2.7 4.69 2.28 2.36 36 Furniture, manufactured nec 12.80 3.13 4.40 -1.21
32 Radio, TV and communication equipment 11.1 11.89 5.23 6.33 Total of A 10.23 5.20 7.99 -2.59
34 Motor vehicles, trailers, etc 6.7 4.64 5.34 -0.67 B Employment displacing growth
36 Furniture, manufactured nec 5.2 5.16 2.04 3.05 16 Tobacco products 4.74 5.43 5.10 0.31
Total of A 5.2 6.15 3.88 2.18 17 Textile 6.67 5.50 6.83 -1.25
B Employment displacing growth 20 Wood and products of wood and cork 2.41 2.52 4.66 -2.05
15 Food products and beverages 6.4 3.52 5.59 -1.96 22 Publishing, printing, etc 11.50 4.06 14.10 -8.80
17 Textile -1.3 5.62 0.80 4.78 27 Basic metals 5.00 10.20 6.26 3.70
20 Wood and products of wood and cork 1.7 6.18 4.10 2.00 29 Machinery and equipments 1.56 8.64 2.80 5.68
35 Other transport equipment 0.1 2.81 1.26 1.54 30 Office, accounting and computing machinery 16.13 10.00 19.06 -7.61
Total of B 1.6 4.50 2.52 1.94 31 Electrical machinery and apparatus 3.77 6.85 4.36 2.39
C Neither growth nor employment 22 Publishing, printing, etc -1.8 1.17 -0.18 1.35 32 Radio, TV and communication equipment 13.37 11.43 15.24 -3.31
33 Medical, precision and optical instruments 23.4 -0.89 36.73 -27.51 35 Other transport equipment 6.97 15.40 11.58 3.42
Total of C 4.7 0.76 8.42 -7.06 Total of B 5.59 8.42 6.58 1.73
Total manufacturing 4.5 5.78 4.26 1.46 Total manufacturing 7.94 6.72 7.26 -0.50 Source: Annual Survey of Industries, Summary Results for Factory Sector. Source: Annual Survey of Industries, Summary Results for Factory Sector.
Economic & Political Weekly
EPW
(an annual average of 28,000) against an annual output growth rate of close to 7%. Hence the employment elasticity that is closer to zero (0.06).
The situation in the second period (i e, since the beginning of wide ranging reforms) has been quite different except the overall jobless growth performance (see Table 9). First of all the growth in NCS at 7.9% per annum is close to double of that in the earlier period. This gave rise to a high growth in capital intensity of 2.3% per annum and resulting in the growth of labour productivity at 6.72%. The growth in capital productivity has been negative. What this suggests is that the growth in capital stock has been, on the whole, to replace labour without the kind of technological upgradation of the previous period. This could be due to the fact that the scope for further technological upgradation was not so pronounced. But the output growth increased to around 7.4%. New employment of a little more than a million was created but around 4,02,000 jobs was destroyed thus creating net employment of around 6,04,000. Given the high growth in output, employment elasticity remained closer to zero but increased to 0.09.
For the whole period of 24 years, the picture (Table 10) is one of sustained increase in NCS followed by an impressive increase in labour productivity (6.3%) that saw replacement of labour with capital through a continuous increase in capital intensity (6% growth in K/L) along with minimal technological upgradation (a growth rate of 0.30% in capita productivity, i e, O/K).
Table 10: Growth Rate of Net Capital Stock (NCS), Labour Productivity (O/L), Capital Productivity (K/L) and Capital Intensity (O/K) in the Organised Manufacturing during 1983-84 and 2004-05
| NIC | Description | 2004-05 to 1983-84 | |||
|---|---|---|---|---|---|
| 2- Digit | NCS | O/L | K/L | O/K | |
| A | Employment creating growth | ||||
| 16 | Tobacco products | 7.99 | 5.22 | 6.77 | -1.45 |
| 18 | Wearing apparel, dressing and dyeing of fur | 17.88 | 5.49 | 5.83 | -0.32 |
| 19 | Leather tanning and dressing | 6.32 | 2.06 | 2.22 | -0.16 |
| 21 | Paper and paper products | 9.53 | 3.69 | 7.68 | -3.70 |
| 23 | Coke, refined petroleum products | ||||
| and nuclear fuel | 8.46 | 12.34 | 5.40 | 6.58 | |
| 24 | Chemicals and chemical products | 7.91 | 5.47 | 5.34 | 0.12 |
| 25 | Rubber and plastic products | 11.30 | 6.29 | 6.84 | -0.52 |
| 26 | Other non-metallic mineral products | 8.37 | 6.74 | 7.01 | -0.25 |
| 28 | Fabricated metal products | 4.38 | 2.63 | 3.10 | -0.45 |
| 29 | Machinery and equipments | 4.02 | 5.82 | 3.02 | 2.72 |
| 30 | Office, accounting and computing machinery | 15.15 | 12.53 | 7.53 | 4.65 |
| 32 | Radio, TV and communication equipment | 12.38 | 11.22 | 10.24 | 0.89 |
| 33 | Medical, precision and optical instruments | 12.95 | 5.07 | 12.57 | -6.67 |
| 34 | Motor vehicles, trailers, etc | 8.60 | 6.74 | 4.75 | 1.90 |
| 36 | Furniture, manufactured nec | 9.71 | 1.76 | 2.62 | -0.84 |
| Total of A | 8.42 | 6.10 | 5.69 | 0.39 | |
| B | Employment displacing growth | ||||
| 15 | Food products and beverages | 6.92 | 3.53 | 5.49 | -1.85 |
| 17 | Textile | 4.14 | 5.43 | 4.70 | 0.70 |
| 20 | Wood and products of wood and cork | 1.79 | 0.61 | 3.39 | -2.69 |
| 22 | Publishing, printing, etc | 6.23 | 2.02 | 7.83 | -5.38 |
| 27 | Basic metals | 6.44 | 8.95 | 7.80 | 1.07 |
| 31 | Electrical machinery and apparatus | 3.46 | 5.94 | 3.38 | 2.48 |
| 35 | Other transport equipment | 3.44 | 10.03 | 6.21 | 3.60 |
| Total of B | 5.75 | 6.12 | 5.98 | 0.13 | |
| Total manufacturing | 7.11 | 6.29 | 5.97 | 0.30 |
Source: Annual Survey of Industries, Summary Results for Factory Sector.
Figure 4: Index of Total Capital Stock and Capital Intensity (K/L) in the Organised Manufacturing Sector during 1983-84 and 2004-05
500 K/L
400 300 200 100 Total capital stock 0 1983-84 1986-87 1989-90 1992-93 1995-96 1998-99 2001-02 2004-05
This overall picture, while quite instructive to understand the broad trends in the organised manufacturing, has to be further probed in terms of what we call “Employment Creating Growth” industries and “Employment Displacing Growth” industries.
Wage as Cost to Employers and Income to Workers
The distribution of surplus generated in a production system between workers and capitalists is a classical problem because of its implications on the long-term development of capitalism in general and the welfare of the workers in particular. As far as the performance of the organised manufacturing sector in India is concerned, we have seen that the impressive growth performance has been achieved by increasing labour productivity and a corresponding increase in capital intensity. We have also seen that a higher proportion of the incremental surplus has gone to capital resulting in a declining share of wages to all employees in general (except perhaps a thin layer of managerial staff) and workers in particular.
There are two aspects of wages here. When expressed in terms of product prices (i e, share of wages in value added) it represents the cost to the employers and a declining share means a declining cost of labour. When expressed in purchasing power terms, or what is usually referred to as real wages, it represents the income to the workers. These two dimensions of wages along with output growth are given in Table 11. Real wages were derived by deflating money wages with the Consumer Price Index for Industrial Workers.
Table 11: Growth Rates in Labour Productivity, Product Wage and Real Wage
(Annual average growth in %)
| Period | Output | Product Wage | Real Wage | ||
|---|---|---|---|---|---|
| Workers | Supervisors | All Employees | |||
| Period I | 6.54 | 3.68 | 3.46 | 2.58 | 3.26 |
| Period II | 6.72 | 3.69 | 0.27 | 3.79 | 1.60 |
| Whole period | 6.58 | 3.73 | 1.55 | 3.86 | 2.50 |
The implications of the findings are quite significant. The growth rate in product wage was a little more than half during both the periods. However, the real wage increase was only around half of the growth in output during the first period that declined to around one-third during the second period when all employees are taken into account. But the losers in this scenario are the workers. While their real wage growth was less than but closer to the product wage during the first period, it declined sharply to one-fourth of a per cent in the second period. In actual terms, workers hardly experienced an increase in real wages during the second period (post-reform) while the supervisory and managerial staff experienced a 3.8% increase in real wages. This
march 7, 2009 vol xliv no 10
has resulted in a long-term annual growth of 3.9% in real wages for supervisors and just 1.6 for workers. Given the fact that the per capita earnings of supervisory staff is two times higher than the workers in early 1980s, such an uneven growth meant a widening of inequality in the earnings as between supervisory staff and workers. The ratio of earnings at the end of the period was 3.3:1.
Table 12: Industry-wise Growth in Average GVA and Emoluments Per Employee
(% growth per year)
| NIC | Description | GVA Per Employee | Emolument Per Employee | ||||
|---|---|---|---|---|---|---|---|
| Code | Period I | Period II | Whole | Period I | Period II | Whole | |
| Period | Period | ||||||
| 15 | Food products and beverages | 10.64 | 4.62 | 6.57 | 9.11 | 2.59 | 5.26 |
| 16 | Tobacco products | 7.63 | 5.43 | 6.05 | 1.79 | 1.23 | 1.38 |
| 17 | Textile | 5.79 | 5.50 | 5.52 | 4.02 | 2.93 | 3.46 |
| 18 | Wearing apparel, dressing | ||||||
| and dyeing of fur | 11.79 | 0.93 | 5.12 | 4.00 | 5.73 | 5.07 | |
| 19 | Leather tanning and dressing | 4.82 | 1.19 | 3.27 | 1.17 | 2.30 | 2.32 |
| 20 | Wood and products of wood | ||||||
| and cork | 7.64 | 2.52 | 1.69 | 5.49 | 2.53 | 1.42 | |
| 21 | Paper and paper products | 3.76 | 3.29 | 2.56 | 0.82 | 2.69 | 1.43 |
| 22 | Publishing, printing, etc | 0.88 | 4.06 | 1.82 | -1.22 | 1.85 | -0.49 |
| 23 | Coke, refined petroleum products | ||||||
| and nuclear fuel | 8.15 | 7.81 | 9.06 | 6.31 | 1.69 | 3.25 | |
| 24 | Chemicals and chemical products | 7.18 | 4.21 | 6.06 | 4.76 | 2.33 | 3.62 |
| 25 | Rubber and plastic products | 9.17 | 5.27 | 7.04 | 4.42 | 4.87 | 4.92 |
| 26 | Other non-metallic mineral | ||||||
| products | 10.43 | 6.89 | 7.05 | 2.91 | 3.52 | 3.43 | |
| 27 | Basic metals | 1.97 | 10.20 | 7.23 | -0.23 | 2.25 | 2.37 |
| 28 | Fabricated metal products | 3.11 | 2.82 | 2.69 | 1.76 | 1.93 | 1.91 |
| 29 | Machinery and equipments | 4.18 | 8.64 | 6.19 | 3.90 | 6.32 | 4.94 |
| 30 | Office, accounting and | ||||||
| computing machinery | 18.31 | 10.00 | 13.45 | 7.95 | 10.21 | 9.76 | |
| 31 | Electrical machinery and apparatus | 6.19 | 6.85 | 6.49 | 5.33 | 5.55 | 5.24 |
| 32 | Radio, TV and communication | ||||||
| equipment | 14.23 | 11.43 | 12.28 | 6.63 | 12.25 | 9.54 | |
| 33 | Medical, precision and | ||||||
| optical instruments | 2.59 | 8.34 | 6.12 | 1.90 | 5.22 | 4.06 | |
| 34 | Motor vehicles, trailers, etc | 5.17 | 9.00 | 6.79 | 4.78 | 4.29 | 4.26 |
| 35 | Other transport equipment | 2.98 | 15.40 | 9.46 | 0.92 | 7.74 | 4.47 |
| 36 | Furniture, manufacturing nec | 6.35 | 3.13 | 2.55 | 3.02 | 1.36 | 0.72 |
| All manufacturing | 6.54 | 6.72 | 6.58 | 3.68 | 3.69 | 3.73 |
The declining share of wages as well as a slow growth in real wages of workers would suggest a declining power of workers and their organisations. The support for economic liberalisation and globalisation from employers and higher paid supervisory and managerial staff and the opposition to it from the workers and their organisations seem to be grounded in the distribution of benefits to these groups. The workers as a class lost in terms of both additional employment as well as real wages.
Understanding Jobless Growth: Plausible Hypotheses
This section suggests some hypotheses for the phenomenon of jobless growth.
The Argument about Labour Market Rigidity
In the beginning of this paper we dealt with the argument about labour market rigidity as the prime cause for the absence any perceptible increase in employment elasticity in the organised manufacturing sector. The opinion, as we saw earlier, is divided along those who continue to advance labour market rigidity as the prime factor and those who contest it. The analysis here
Economic & Political Weekly
EPW
covering a period of close to a quarter of a century has shown that at the 2-digit level there have been two opposing trends.
One set of industries showing employment creating growth and another set showing employment displacing growth. It is the net effect of these two opposing forces that have led to a near absence of employment growth. This shows that labour market rigidity does not seem to operate across the board, if at all it is a major factor. It is also important to note that the so-called labour market rigidity argument in the Indian context boils down to a particular clause in the Industrial Disputes Act – Chapter VB – that mandates prior permission of the government for an enterprise with more than 100 workers if it wants to retrench its workers. In case permission is granted, the employer is required to give a three-month notice to the worker providing reasons for the proposed retrenchment. However, such a provision is not applicable to a number of categories of workers such as (a) managerial or supervisory staff or to staff in administrative responsibilities, (b) casual or temporary workers including badli workers, and (c) workers who have not yet completed one year of continuous service. Further a wage ceiling is applied to workers who are subjected to this provision which is Rs 6,500 per month (as on 2005). All these have restricted the applicability of the provision under Chapter VB to a narrow segment of workers.
Despite such a restricted application, there is so much heat generated over this provision especially by those who are seen as the advocates of economic liberalisation and globalisation. Employers, despite their opposition to the clause, do not seem to bother too much about when it comes to investment decisions or are confident of dealing with it. It is quite possible that the contestation is more ideological than a practical hindrance to investment and increasing employment. Capital is certainly interested in unhindered control of labour that would give them much flexibility and discretion in the manner and pace of accumulation. Therefore their position could be one of a strategy of labour control. On the other hand, labour in organised manufacturing, especially in the bigger establishments, are unionised and see this as an ideological threat to their very existence, let alone functioning within a framework of collective bargaining in which trade union participation is a legitimate activity. In the Indian context, this takes political overtones since trade unions are affiliated to political parties. Such an ideological contestation cannot be resolved through empirical verification of employment and output growth performance of organised industries. We therefore move to two other plausible explanations.
Has Capital Become Cheaper?
The second set of explanation for the jobless growth in organised manufacturing relates to the wide range of measures that helped reduce the cost of capital such that the employers found it more attractive to continuously increase capital intensity of production for maximising output growth. In a recent paper Chandrasekhar (2008) calculated the cost of capital and compared it with the cost of labour3 and concluded that there is a “negative shift in the price of capital relative to labour” which “points to a major bias in prices that favours capital intensity”. He also points out that there are additional incentives encouraging capital intensity offered by central and state governments in the form of cash subsidy based on level of investment, interest subsidies and a range of other incentives such as exemption from payment of electricity in several cases.
For an earlier period of analysis, Ghosh (1994) had also attributed the increase in real cost of labour as a reason for capital deepening in the organised manufacturing sector. As mentioned earlier, such a view was then contested by both Papola (1994) and Nagaraj (1994).
Given the fact that we Table 13: Cost of Capital and Cost of Labour Per Unit of Value Added and Their Ratios
have covered almost a
Year Interest/GVA (%) Wage/GVA (%) Ratio of (2)/(1)
quarter of a century and
1981-82 12.2 41.9 3.4
have shown the differ
1982-83 12.1 41.8 3.4 ential performance of the 1983-84 13.0 41.5 3.2
| organised manufacturing | 1984-85 | 14.3 | 42.3 | 3.0 |
|---|---|---|---|---|
| sector in terms of indus | 1985-86 | 15.7 | 40.4 | 2.6 |
| tries that are “job creat | 1986-87 | 17.1 | 41.0 | 2.4 |
| ing growth” and “job displacing growth”, we | 1987-881988-891989-90 | 14.9 13.5 13.2 | 39.8 34.5 33.7 | 2.7 2.6 2.6 |
| think it is important to | 1990-91 | 13.0 | 32.0 | 2.5 |
| further examine the the | 1991-92 | 15.9 | 32.4 | 2.0 |
| sis of relative cheapness | 1992-93 | 15.2 | 32.2 | 2.1 |
| of capital vis-à-vis labour. | 1993-94 | 16.8 | 28.7 | 1.7 |
| While the WPI for ma | 1994-95 | 16.6 | 27.1 | 1.6 |
| chinery and index of money wages could rep | 1995-961996-971997-98 | 13.7 12.6 17.9 | 27.1 24.3 27.9 | 2.0 1.9 1.6 |
| resent the cost of capital | 1998-99 | 18.0 | 25.7 | 1.4 |
| and labour, respectively, | 1999-2000 | 18.6 | 25.3 | 1.4 |
| we would argue that we | 2000-01 | 22.3 | 28.5 | 1.3 |
| need to find out the cost | 2001-02 | 24.3 | 28.0 | 1.2 |
2002-03 19.7 25.9 1.3
of capital and labour in
2003-04 17.1 23.7 1.4
curred by the firms. This
2004-05 12.4 20.9 1.7
ex-post data would then show the relative cost of capital vis-à-vis labour as experienced by the firms. For this we have taken the share of interest paid in gross value added to represent cost of capital and share of wages in gross value added to represent cost of labour. These are shown in Table 13 and Figure 5.
Figure 5: Relative Cost of Capital and Labour (in %)
50 40 30 20 10 0 Wage/GVA Interest/GVA Wage share/Interest share 1981-82 1984-85 1987-88 1990-91 1993-94 1996-97 1999-2000 2002-03 2004-05
Clearly the cost of capital here has been showing an increasing trend except for the latest year (2004-05) when it came down to the level of the initial year (1981-82). However, the share of wages in value added shows a more or less secular decline to such an extent that it is exactly half that of the initial years. The ratio of these two shows that it is the cost of labour that has cheapened over time vis-à-vis cost of capital. The puzzle here then is to explain the continuous increase in capital intensity for both “job-creating” and
90 “job-displacing” groups of industries. Since early 1990s the process of capital intensification has accelerated as compared to the 1980s.
Demand Side Explanation: Changing Nature of Demand
We now move to another set of explanations that may be clubbed as demand-side explanations. It would appear that there is a strong case to move away from cost of production and problems in labour hiring explanations to those which are related to the changing nature and composition of demand for manufactured products both in the domestic and foreign markets. Chandrasekhar (2008) has dealt with this demand side effects as an added reason for the jobless growth in organised manufacturing. We feel that this is perhaps the dominant factor that has pushed India’s organised manufacturing to a situation of jobless growth arising out of economic reform policies.
We have already seen how the distribution of the value added in organised manufacturing has shifted in favour of capital and to the managerial class of employees. Given the same logic, similar shifts might also have occurred in the organised segment of the service sector. In fact this has been the experience in most countries that have embarked on the path of economic liberalisation and globalisation. In the Indian case, the shift in demand takes place in favour of those goods demanded by the newly rich classes, which has been made easy by a rather aggressive pursuit by banks expanding personal finance loans. This satisfied the demand for products that are similar to “foreign goods” that were not earlier satisfied. Since the enterprises also have to compete in an open economy context, they have to produce goods, which would be similar to those that could now be imported. If they are export-oriented, then they have to produce goods that are demanded in the world market, produced with modern technology, packaging, branding and so on. As Chandrasekhar points out, opening the domestic market for transnational enterprises also results in high import intensity of domestic manufacturing that will in turn reduce the employment elasticity of growth in manufactures. In a nutshell, what we are witnessing is a drastic change in the quality of products characterised by high capital intensity, branding, import intensity and so on that results in slowing down both the absorption of direct labour as well as backward and forward linkages within the domestic economy.
Trade policies especially import duties and special incentives for export, credit policies that push up the personal finance for middle- and high-income segments, technology acquisition policies that are capital-intensive modern technologies, and fiscal policies that favour a reduced rate of taxation and special incentives for capital-intensive projects in fact work in favour of such a qualitative shift in the composition and structure of demand. This has manifested in several countries in terms of jobless growth in organised manufacturing. This leaves the vast informal sector in manufacturing in India where around 71% of the total workforce in manufacturing are engaged, to cater to the demand for goods that are low value (arising out of the low-income of the households), low productivity and low quality. Employment in this sector is mostly by default in the form of self-employment since many workers have no opportunities for wage employment, let alone regular wage employment.
march 7, 2009 vol xliv no 10
As we have noted earlier, jobless growth is not all pervasive However, employment elasticity has remained within a narrow across all industries. Our analysis shows that a set of industries has range of 0.26 to 0.28 between the two periods analysed here. been able to grow with some net job creation. However, there is While there has been reference to a “hollowing” of the smallanother set of industries that grew largely by shedding employ-scale sector of Indian industry, what we have found is an increasing ment perhaps to stay on course with the changing nature of the divide between the formal and informal segments of Indian manuproduct market and domestic competition. The interaction of these facturing. In another study (NCEUS 2008), we have reported that the two trends resulted in jobless growth over nearly a quarter of a informal segment of manufacturing registered an annual growth century. While growth has been high, it has not been high enough rate of 4.9% between 1999-2000 and 2004-05, the formal segment to generate additional employment to come out of the syndrome has grown by 7%. What this points to is the relative decline of the of “jobless growth”. Examining Table 6, one might be tempted to share of informal segment since the growth rate differential is so say that there is some streak of hope in favour of employment since huge. If this persists, there is sufficient reason to worry about industries that are “job creating growth” sectors have increased increasing inequality and its attendant economic and social repertheir share of employment from 54% in 1981-82 to 64% in 2004-05 cussions. The jobless growth performance of India’s organised manuwith a corresponding increase in share of output from 62% to 77%. facturing sector is indeed a matter of serious concern.
Notes
1 The sectoral wholesale price indices used for different industry groups are given in the Appendix.
2 These are: Goa, Himachal Pradesh, Jammu and Kashmir, Manipur, Meghalaya, Nagaland, Tripura, Andaman and Nicobar Islands, Chandigarh, Dadra and Nagar haveli, Daman and Diu and Pondicherry.
3 “The ‘cost of investment’ is captured not just by trends in the prices of capital goods, but also by the opportunity cost of capital as captured by the prevailing rate of interest. One way to represent the combined effect of these two elements is to apply the rate of interest on an index of the price of capital goods, say the wholesale price index of machinery, and build an index of the resulting values. This is what has been done to construct the index of cost of capital, also presented in Chart 6. What is interesting is that when we consider this composite index, the trend has been more complex than revealed merely by the relative movements of the prices of capital goods and money wages. The high interest rate regime that kicked in after the crisis of 1991-92, and remained in place till the second half of the 1990s meant that the ‘cost of capital’ rose sharply during the first half of the 1990s, often at a rate much faster than the rate of rise in money wages. However, after the government managed to engineer a low interest rate regime starting from the late 1990s, movements in money wages and the cost of capital diverged with the former rising at fast rate while the latter stagnated or declined” (Chandrasekhar 2008: 10).
References
Bhalotra, S R (1998): “The Puzzle of Jobless Growth in Indian Manufacturing”, Oxford Bulletin of Economics and Statistics, 60, 1.
Chandrasekhar, C P (2008): “Revisiting the Policy Environment for Engendering Employment Intensive Growth”, Background Paper prepared for the International Labour Office, New Delhi.
Dutta Roy, S (1998): “Lags in Employment Adjustment and Inter-industry Differentials: An Analysis Using Dynamic Inter-Related Factor Demand Function”, Discussion Paper No 149 (Mumbai: Indira Gandhi Institute of Development Research).
Fallon, P R and R E B Lucas (1993): “Job Security Regulations and the Dynamic Demand for Industrial Labour in India and Zimbabwe”, Journal of Development Economics, Vol 40, pp 241-75.
Ghose, A K (1994): “Employment in Organised Manufacturing in India”, Indian Journal of Labour Economics, Vol 37, No 2.
Goldar, B (2000): “Employment Growth in Organised Manufacturing in India”, Economic & Political Weekly, 1 April, pp 1191-95.
Economic & Political Weekly march 7, 2009
EPW– (2004): “Indian Manufacturing: Productivity Trends in Pre- and Post-Reform Periods”, Economic & Political Weekly, 20 November, pp 5033-43.
Kannan, K P (1994): “Levelling Up or Levelling Down? Labour Institutions and Economic Development in India”, Economic & Political Weekly, 23 July, pp 1938-45.
Nagaraj, R (1994): “Wages and Employment in Manufacturing Industries: Trends, Hypothesis and Evidence”, Economic & Political Weekly, Vol 29, No 4, 22 January.
NCEUS (2008): “Contribution of the Unorganised Sector to GDP Report of the Sub Committtee of a NCEUS Task Force”, Working Paper 2, New Delhi.
Papola, T S (1994): “Structural Adjustment, Labour Market Flexibility and Employment”, Indian Journal of Labour Economics, Vol 37, No 1.
World Bank (1989): “India: Poverty, Employment and Social Services: A World Bank Country Study” (Washington DC: World Bank).
Appendix: Methodology to Calculate Total Capital Stock
The estimation of capital stock employed in the production process in any year is generally based on a number of reasonable assumptions. Given the data sets available from different sources, there exists no ideal method. Nevertheless, the perpetual inventory method is considered to be useful and realistic in the estimation of capital stock. The method has been used in this study for the estimation of 2-digit level industrywise capital stock in the manufacturing sector at 1993-94 prices. The time series data released by the Central Statistical Organisation contain information on Net Fixed Capital at the end of each accounting year and net fixed capital formation and depreciation since 1979-80. During the period from 1973-74 to 1978-79, data on yearwise depreciation and net capital formation are not available though net fixed capital data are available. The net fixed capital estimates are book values after depreciation and net capital formation estimates are at current prices.
In this exercise, one-fifth of the difference between the net fixed capital estimates at the end
vol xliv no 10
of 1978-79 and 1973-74 was notionally estimated to be the net capital formation after depreciation during each of the above years. The net fixed capital at the end of 1973-74 and net depreciation during each of the years up to 2004-05 were then converted into 1993-94 prices by using wholesale prices indices for machinery and equipments. Thus = (NFC78-79 – NFC73-74)/5
NCF*74-75where NCF* is Net Capital Formation after depreciation NFCR = NFC73-74 × (WPI93-94 )
73-74/WPI73-74 NCFR = NCF × (WPI93-94 / WPI)
t tt
where NFCR is net fixed capital at constant prices WPI is wholesale price index for machinery and equipments and NCFR is net capital formation at con
t
stant prices. In the next step the rate of depreciation for each year from 1979-80 was estimated by dividing the depreciation at current prices with the sum of the Net Fixed Capital of the previous and net capital formation of the current year
RD = D /(NFCt-1 + NCF)
ttt
where RD is the rate of depreciation in the
t
year t and Dis the amount of depreciation in the
t
year t. The capital stock for each of the years from 1973-74 to 1978-79 is then estimated by using the formula
NCS* = NFC* + NCF*
t+1tt+1
where NCS*t+1 is the net capital stock at the end of year t+1, at constant prices NFC* is the net fixed capital at the end
t
of year t and NCF*t+1 is net capital formation during the year t+1, both at constant prices.
The capital stock for each of the years from 1979-80 was estimated by using the formula NCS* = (NCS* + NCF* )×RD
t+1tt+1t
Since these capital stock estimates relate to the end of the production year, the average of the previous year and the current year was taken to reflect the mean capital stock during the year. Thus
NCS* (mean) = (NCS* + NCS* )/2
tt-1t
