SPECIAL ARTICLE Where Is the Missing Labour Force?
C Rangarajan, Padma Iyer Kaul, Seema
This paper examines the trends in employment and wages as thrown up by the 66th round of the National Sample Survey Organisation that was the quinquennial employment-unemployment survey. The publication of the summary results has generated a lot of controversy. It is only the NSSO surveys that capture detailed comparable data over long time periods, and therefore, it is important that the present survey data is carefully analysed and objectively used for understanding the impact of policy and for course corrections if required.
C Rangarajan (c.rangarajan@nic.in) is chairman of the Economic Advisory Council to the prime minister, Padma Iyer Kaul is executive director in the Pension Fund Regulatory and Development Authority and Seema is the deputy advisor in the Economic Advisory Council to the prime minister.
T
The paper is organised into five sections. Section 1 analyses the aggregate labour force, workforce and unemployment numbers that are thrown up by the 66th round. Section 2 looks at the sectoral disaggregation of the workforce. It focuses on the changing shares and growth rates and the implications of this for the economy. Section 3 deals with the category-wise disaggregation of the workforce and looks at how Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) affects the shifts from one category to another. In Section 4 we comment on the wages and in Section 5, we make some concluding remarks.
1 Labour Force, Workforce and Unemployment
Undoubtedly the workforce is an important parameter and has fittingly received a lot of attention. On the contrary, the labour force – an equally important parameter has been largely ignored in discussions. Some understanding of the NSSO terminology is in order not only to set the context, but also to establish the interlinkage between the labour force and workforce. The survey is based on a sample. Depending on the replies to the survey questions, the sample is bifurcated into two categories, i e, those in the “labour force” and those “not in the labour force”. The first category consists of those who are seeking work. This is essentially the category that either finds employment or remains unemployed. Those who find employment are designated by the NSS
SEPTEMBER 24, 2011 vol xlvi no 39
EPW
SPECIAL ARTICLE
as the “workforce”, while those who do not find employment are designated as “unemployed”. Since the “labour force” is the total of which the “workforce” is a part, any changes in the former are bound to have an impact on the latter. This is an extremely important feature which must be kept in mind before drawing inferences about the workforce from the surveys. The second category, i e, “not in the labour force” consists of persons who are not seeking work. This withdrawal from the labour force could be on account of pursuit of education, sickness, domestic work, disability, etc.
Table 1: Labour Force, Workforce and Unemployed (UPSS)
the workforce declined from 2.9% to 0.05% in these two periods. A segment-wise break-up (Tables 2 and 3) shows trends which more or less mirror those of the labour force. In the period 200405 to 2009-10, there was an addition of 22 million males to the workforce accompanied by a decline of 21 million females from the workforce. While the male addition to the workforce was fairly evenly distributed between rural and urban areas, the decline in the female workforce was mainly concentrated in the rural areas. Of the 21 million decline in female workforce, more than 19 million was in rural areas. It will be interesting to locate the sectors where this has happened to under
1993-94 1999-2000 2004-05 2009-10 1993-94 to 1999-2000 2004-05 to stand the reasons for this. We attempt this in 1999-2000 to 2004-05 2009-10
one of the subsequent sections.
In Million CAGR (%)
Notwithstanding the slowdown in the em-
Labour force 381.94 406.84 470.14 469.87 1.03 2.93 -0.01
ployment creation, the total number of unem-
Workforce 374.45 397.88 458.99 460.17 0.98 2.90 0.05
ployed declined from 11.15 million in 2004-05
Unemployed 7.49 8.96 11.15 9.70
to 9.7 million in 2009-10. Even as a proportion
As a proportion of labour force in per cent Unemployment rate 1.96 2.2 2.37 2.06 of the labour force, the unemployed declined
The numbers in the above table have been derived by applying the NSS segment-wise worker-population ratios and the
from 2.37% in 2004-05 to 2.06% in 2009-10. On
labour force participation rates to the census population. All figures for workforce pertain to UPSS, i e, for usual principal and subsidiary status. CAGR is the compound annual growth rate.
Table 2: Gender-wise Break-up of Labour Force (in million)
| NSS | Rural | Urban | Total | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Male | Female | Male | Female | ||||
| 1999-2000 201.98 | 106.75 | 78.87 | 19.25 | 280.85 | 126.00 | 406.85 | |||
| 2004-05 | 222.91 | 126.49 | 94.24 | 26.50 | 317.15 | 152.99 | 470.14 | ||
| 2009-10 | 236.09 | 106.41 | 103.13 | 24.25 | 339.22 | 130.66 | 469.88 |
| Table 3: Gender-wise Break-up of the Workforce (in million) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| NSS Round | Rural | Urban | Total | ||||||
| Male | Female | Male | Female | Male | Female | ||||
| 1999-2000 198.61 | 105.69 | 75.38 | 18.20 | 273.99 | 123.89 | 397.88 | |||
| 2004-05 | 219.30 | 124.21 | 90.77 | 24.72 | 310.06 | 148.93 | 458.99 | ||
| 2009-10 | 232.27 | 104.80 | 100.17 | 22.92 | 332.44 | 127.72 | 460.17 |
In a distinct break from past, the labour force declined, albeit marginally, from 470.14 million in 2004-05 to 469.87 million in 2009-10 (Table 1). In the two previous periods of 1993-94 to 1999-2000 and 1999-2000 to 2004-05, it had increased by 25 million and 63 million, respectively. This decline has come as a surprise since in this period 2004-05 to 2009-10, not only was the population growing at a compound annual growth rate (CAGR) of 1.44%, the economy was also doing well with a CAGR of 8.6%. A number of people have viewed this result with disbelief raising questions on the whole survey.
The segment-wise disaggregation of the labour force reveals that in the period 2004-05 to 2009-10, both rural and urban males experienced deceleration in growth rates as compared to the previous period. Nevertheless there was an addition of 22 million men into the labour force in the five-year period as compared to the 36 million in the previous period (1999-2000 to 2004-05). On the contrary, 22 million women withdrew from the labour force in the recent period of which 20 million were rural.
The recent period between the 61st and 66th NSS rounds also witnessed a slowdown in the additions to the workforce. In the five-year period of 1999-2000 to 2004-05, 60 million jobs were created against which the next five years, 2004-05 to 2009-10 witnessed an addition of just about a million jobs. The CAGR of
Economic & Political Weekly
EPW
the face of it this is puzzling. With such a large
slowdown in employment generation, how could the total number of unemployed decline? The answer clearly lies in the fact that the actual labour force has declined. In this context, it is important to understand why a larger number of people, especially the rural females, did not choose to offer themselves for work.
1.1 Why Did People Withdraw from the Labour Force?
There are several reasons for people opting out of the labour force. In the 66th round about 707 million people did not offer themselves for work as against 625 million in the 61st round. The largest share at 44% was that of people who opted out of the labour force to pursue education, 31% opted out for attending to domestic activities, 15% were in the 0-4 age group and the remaining categories (disabled, pensioners, etc) added up to a 10% share.
India is studying – Sarva Shiksha Abhiyan (SSA), mid-day meal and the right to education seem to be working. In the period 2004-05 to 2009-10, 313 million people opted out of the labour force to study as against 267 million in the previous five years 1999-2000 to 2004-05. In the period 2004-05 to 2009-10, interestingly, both rural and urban India showed equal CAGR’s of the people who withdrew from the labour force for education. A gender-wise disaggregation does not show too much variation between men and women with both growing at a CAGR of 3% plus. However, within females, the rural woman overtook her urban counterpart for education, with the former growing at a CAGR of 3.3% as against 2.7% for the latter. In 2009-10, about 137 million women opted out of the labour force to educate themselves as against 176 million men.
The second largest category was of those who opted out of the labour force to attend to domestic duties including activities like weaving, tailoring and gathering firewood for free for the household. In 2004-05, this category constituted 170 million persons, which rose quite sharply to 220 million in 2009-10 growing at a CAGR of 5.3%. Predictably these withdrawals have been
SPECIAL ARTICLE SPECIAL ARTICLE
| almost completely by the females, the rural female withdrawals | may be at work impacting the workforce numbers. However, this |
| being higher than that of urban females. This is interesting, since | segment has the potential to be productive and appropriate inter |
| 2009-10 was a drought year and agricultural growth rate was | ventions to persuade larger numbers here to become economically |
| 0.4%. According to contemporary literature these are appropri | active would be an important strategy to boost incomes and |
| ate conditions for women to seek “distress employment” to aug | growth momentum. |
| ment family incomes, especially in the rural areas. However, the results of the 66th round show quite the opposite phenomenon. | 2 Sectoral Movements in Employment |
| Some explanations that can be offered are that (a) agriculture | Economic development is accompanied by a falling share of agri |
| has become somewhat drought resilient at least in terms of farm | culture in the gross domestic product (GDP) and employment. In |
| incomes, (b) NREGA has managed to provide supplementary jobs, | India the former has occurred with agriculture accounting for |
| and (c) wages in general have gone up. However to make strong | only about 15% of the GDP (2009-10). However, the pace of shift |
| statements on this require an in-depth study. The phenomenon is | in employment from agriculture to the other two sectors has been |
| nevertheless intriguing. | somewhat sluggish in the past. The 66th round results suggest |
| Table 4: Sectoral Disaggregation of Workforce | that this has changed. In the period 2004-05 to 2009-10, about 21 |
| Workforce (in million) Shares (%) | million people moved out of agriculture leading to a drop in its |
| Primary Secondary Tertiary Primary Secondary Tertiary | employment share from 56.5% in 2004-05 to 51.76% in 2009-10. |
| 1999-2000 240.3 64.6 93.6 60.39 16.24 23.52 | Since 1993-94, this is the largest decline both in absolute and |
| 2004-05 259.3 85.9 113.9 56.50 18.71 24.82 2009-10 238.2 100.7 120.8 51.76 21.89 26.25 | relative terms (Table 4). The declining share of the workforce in agriculture was mainly |
| The third largest category of non-participants in the labour | picked up by the secondary sector, whose proportionate share in |
| force is of children in the 0-4 age group. In 2004-05, the share of | creased from 18.71% in 2004-05 to 21.89% in 2009-10. In the 66th |
| this group was at 18.2%, while in 2009-10 it had declined to 15%. | round the secondary sector workforce crossed the 100 million mark |
| Even in absolute terms the total number in this category declined | adding about 15 million workers in the five-year period 2004-05 to |
| from 113 million in 2004-05 to 105 million in 2009-10 consisting | 2009-10. Further disaggregation into subsectors reveals that the |
| almost completely of the rural segment. The urban numbers | manufacturing sector lost about 3.7 million jobs. The job losses are |
| remained unchanged in the period 2004-05 to 2009-10. The decline | not surprising since the 66th round data was collection followed |
| here translates into comparatively lower withdrawals from the | the crisis hit period of 2008-09 when the GDP growth in the manu |
| labour force in this category. Is this indicative of a demographic | facturing sector had decelerated to 4.2%. Even though manufac |
| trend? This may well be the case since the recently released cen | turing growth did pick up subsequently but it did not reach the |
| sus data, shows a decline in the share of the 0-6 age group from | pre-crisis levels. The global recession affected exports which re |
| 16% to 13% in the period 2001-11. The 66th round also confirms | mained sluggish. There is anecdotal evidence to show job losses in |
| the gender bias and the worsening sex ratio. In 2009-10, as | the export-oriented sectors in the economy in 2008-09 and 2009-10.1 |
| against 51 million females in the 0-4 age group there are 54 mil- | There was practically no job creation in the other two subsectors, |
| lion males. However, in the period 2004-05 to 2009-10, the de | i e, mining and electricity which were also affected by the crisis, |
| cline (CAGR) in the 0-4 age group for males at 1.86% was higher | their GDP growth rates decelerating to 1.3% and 4.9% in 2008-09. |
| than that of females at 1.32%. Does this mean a reversal of the | Bulk of the jobs created in the 66th round were in the construction |
| gender bias? We will have to wait and watch. The 66th round | sector, which added about 18 million to the workforce. |
| also provides evidence on the fact that the ageing population in | The total workforce in the tertiary sector increased from 114 |
| India is increasing. The category consisting of “pensioners, rent | million in 2004-05 to 121 million in 2009-10. However, the net |
| iers and people receiving remittances” is growing at a fast pace | addition of seven million workers in this sector was way below |
| recording a CAGR of 7% in the period 2004-05 to 2009-10. The | the 20 million additions in the previous five-year period 1999 |
| previous period of 1999-2000 to 2004-05 recorded an even higher | 2000 to 2004-05. The impact of the deceleration in GDP growth |
| CAGR at 10%. These are clear indications of a growing depend | rates in this sector was also visible in the tapering off of employ |
| ency ratio which warrants a serious look at policy action for pro | ment creation. A further disaggregation shows that the trade, |
| viding social security for the elderly. | hotels and restaurant subsector which had added nine million |
| The above discussion shows that there are a complex set of fac | jobs in 1999-2000 to 2004-05, managed additions of two million |
| tors at work vis-à-vis the labour force. In the recent period, large | only in the period 2004-05 to 2009-10. There were additions of |
| number of men and women are not offering themselves for work | the same order to the workforce in the other two subsectors – |
| because they wish to study. This is clearly a desirable develop | “transport” and “financing” while the “community” subsector |
| ment though this may in the short run possibly translate into | added less than a million jobs. |
| lower workforce numbers. There is a high probability that some | |
| low paying jobs in the unorganised sector do not have takers as | 3 Category-wise Shifts in the Workforce |
| the option to study, improve skills and employability is now avail- | The NSSO survey provides a category-wise disaggregation of the |
| able with the youth. Larger number of women are withdrawing | workforce. The three categories are – self-employed (SE), regular |
| from the labour force to attend to domestic duties. This may be a | wage and salaried (RWS) and casual labour (CL). The total work |
| result of improved incomes and a similar phenomenon as above | force in the self-employed category declined from 259 million in |
| 70 | SEPTEMBER 24, 2011 vol xlvi no 39 Economic & Political Weekly |
EPW 2004-05 to 233 million in 2009-10. The workforce in the casual labour category increased from 130 million in 2004-05 to 151.6 million in 2009-10, while that in the RWS segment increased from 70 million to 75.3 million. A significant proportion of the jobs in the self-employed category is in the unorganised sector and may often be inadequately remunerative. To that extent, a decline here is not necessarily undesirable. It would be ideal if the workforce moves to the RWS category which is a proxy for organised sector employment. In the period 2004-05 to 2009-10, this category has seen additions of 5.4 million jobs which is a welcome development (Table 5). Even in the previous five-year period this category had seen large additions to the workforce. The share of this category has been improving steadily over time and currently accounts for 16.4% of the total workforce. There is however no room for complacence on this count and it is important to create conditions for a faster movement of workforce into this segment.
Table 5: Category-wise Disaggregation of Workforce
| Workforce (in million) | Shares (%) | |||||
|---|---|---|---|---|---|---|
| SE | RWS | CL | SE | RWS | CL | |
| 1999-2000 | 209.3 | 58.2 | 130.3 | 52.6 | 14.6 | 32.8 |
| 2004-05 | 259.0 | 70.0 | 130.0 | 56.4 | 15.2 | 28.3 |
| 2009-10 | 233.2 | 75.3 | 151.6 | 50.7 | 16.4 | 32.9 |
The casual labour segment seems to have picked up a large part of the decline in the self-employed adding 21.6 million workers in the period 2004-05 to 2009-10. To make a comment on the quality of these jobs a more in-depth analysis is required.
A gender-wise analysis reveals that the shift out of the selfemployed category consisted largely of females. In the period 2004-05 to 2009-10, the number of females in the self-employed category declined by about 23 million of which only two million picked up jobs in the other two categories – 1.7 million in CL and
0.2 million in RWS. The withdrawals were largely by the rural women (21 million) and there is a high probability that with increasing rural affluence they moved out of low paying selfemployment activities choosing either to study or devote themselves to domestic duties. A similar trend is visible for urban females though the absolute numbers are much smaller. A clear message that emerges is that women are still not a part of the mainstream and are playing the role of supplementing the family incomes. This has to change if we are looking at a growth process which is fair and equitable. The other evidence of this bias was that, of the 5.3 million jobs in the RWS category, 5.1 million jobs were picked up by men. The RWS category numbers also reveal the urban bias in organised sector employment creation since in the period 2004-05 to 2009-10 almost all the jobs in this RWS category were created in the urban areas.
In this paper we have used the usual principal and subsidiary status (UPSS) for all calculations of the workforce numbers. The workforce under MGNREGA programme is classified as “casual labour” but information for this category is not collected under the UPSS. Instead, it is collected under current weekly status and under the currently daily activity status. Nevertheless this is an important programme and some comment on it is appropriate. MGNREGA was notified in February 2006, for 200 districts in the first phase. One hundred and thirty additional districts were notified in the financial year 2007-08 and from April 2008 the
Economic & Political Weekly
EPW
remaining districts were covered. The first set of MGNREga data was collected in the 64th round survey 2007-08. However, the 64th round survey document expresses an apprehension that in a general household survey, with the design not particularly tuned to capture and identify persons under a specific government scheme, it may be difficult to differentiate between workers in MGNREga and public works. The 66th round expresses no such apprehension. In 2007-08, under the current weekly status, a total of 1.6 million person days of employment was created under MGNREga with almost equal number of jobs being created for men and women. In 2009-10, the employment in terms of person days had gone to 2.48 million – a CAGR of 24%. Here again the malefemale employment ratio remained practically equal.
4 Wages
The discussion in the previous sections has alluded to the increased wages, especially in the context of female withdrawals from labour force. There is clear evidence of increased remuneration to labour in the current survey. First a few stylised facts – irrespective of the category, urban wages are higher than rural wages and male workers earn more than the female workers. This is true of both private and public employment including MGNREGA. A case in point is the wage differential in the RWS category. In the rural areas, female wages were only 63% of the male wages, while in the case of the urban females the wages were 82% of the urban male wages.
In the RWS category the recent period 2004-05 to 2009-10 witnessed large wage increases cutting across all segments – ruralurban and male-female. The CAGR of these wage increase was the highest at 15% in the case of urban female and the lowest at 11.4% for rural male. This increase is of a significantly higher order as compared to the previous period 1999-2000 to 2004-05.
In the casual labour category, the survey gives the wage rates for three categories, i e, works other than public works, other public works and public works under MGNREGA. The wages for casual labour in the first category, proxy for private sector remunerations. The numbers in the survey confirm the several anecdotal accounts of an increase in the cost of farm labour post the launch of MGNREGA. The rural wages for casual labour for the “work other than public work” category have increased at a CAGR of 13% plus in the period 2004-05 to 2009-10. Even for the urban sector the wage rates increase has been strong though it is somewhat lower than the rural wages. Interestingly, in the 66th round, the private sector average wage rates for rural males was higher than the wages in both categories of public works. The situation in the 61st round was exactly opposite with private sector wages being least remunerative for casual workers.
The NSS defines “public works” as activities sponsored by the government or local bodies, and included local area development works like construction of roads, dams, bunds, digging of ponds, etc, as relief measures, or as outcomes of employment generation schemes like MGNREGA, Sampoorna Grameen Rozgar Yojana (SGRY), etc.2
In the period, 2004-05 to 2009-10, both categories under public works, witnessed a substantial rise in wages, though it was of a lower order than in the private sector. The male-female differentials in wages are significantly lower in the casual labour employed in
SPECIAL ARTICLE
public works. The wages under MGNREGA were marginally lower than the wages under other public works as were the malefemale wage rate differentials.
5 Conclusions
In the period 2004-05 to 2009-10, the labour force declined from
470.1 million to 469.9 million. This decline in the labour force was mainly on account of rural female withdrawals. This is surprising. An overall decline of labour force at a time when both population and GDP are growing is somewhat difficult to explain. The decline in the labour force was coupled with a slowdown in the additions to the workforce. As against a 60 million job creation in the period 1999-2000 to 2004-05, just about a million jobs were created in 2004-05 to 2009-10. However, in the recent fiveyear period, the employment picture for men looks diametrically opposite to that for women. In the case of men, there was an addition of 22 million to the workforce in the period 2004-05 to 2009-10, while in the case of women there was a decline of 21 million. Did men pick up the jobs that females had vacated? That does appear to be the case as the decline in workforce was concentrated in agriculture, while the increase of workforce was spread to the secondary and tertiary sectors. Interestingly, a decline in labour force coupled with an increase in workforce led to a decline in the total number of unemployed by 1.5 million in the period 2004-05 to 2009-10. Along with this absolute decline, relative unemployment (unemployed as a ratio of the labour force) also declined in this period.
Education emerged as the major reason for people choosing to opt out of the labour force with 313 million people withdrawing in 2009-10 to study. The other reason was withdrawals, mainly by women to attend to domestic duties. These withdrawals especially those of rural women are indicative of improvements in wages and improvement in agricultural incomes. The survey provides evidence of a significant improvement in wages of both rural-urban and male-female. The launch of the MGNREG also had an impact on private sector wages which have increased much faster than the increase in the wages offered by the government for public works. Another way of looking at these withdrawals is that people may no longer be willing to pick up jobs which are unremunerative instead preferring to improve their skill sets.
In the period 2004-05 to 2009-10, there was a large shift of workforce out of agriculture which moved into the secondary sector (mainly construction) and tertiary sector. The other change in the workforce composition was a decline in the selfemployed category which consisted mainly of women. This result when juxtaposed on the labour force decline is indicative of a high probability that with increasing rural incomes, women moved out of low paying self-employment activities choosing either to study or devote themselves to domestic duties. The workforce in the casual labour segment increased.
The 66th round results have recorded many positive developments. In the period 2004-05 to 2009-10:
labour force to educate themselves and improve their skill sets – the right course for India to leverage the demographic dividend.
However, the 66th round results do leave us with an unanswered question. How do we explain a decline in the labour force in a period where both population and GDP were growing strongly.
Notes
1 Reference to be given of the study by Ministry of Labour on the job losses in export-oriented sectors.
2 The coverage of schemes under public works was restricted to those schemes through which the government-generated wage employment under these programmes.
References
GOI (1993-94): “Ministry of Statistics and Programme Implementation (1993-94): Employment and Unemployment in India, July 1993-June 1994”, NSS 50th round, Government of India, New Delhi.
PERSPECTIVES ON CASH TRANSFERS
| May 21, 2011 | |
|---|---|
| A Case for Reframing the Cash Transfer Debate in India | – Sudha Narayanan |
| Mexico’s Targeted and Conditional Transfers: | |
| Between Oportunidades and Rights | – Pablo Yanes |
| Brazil’s Bolsa Família: A Review | – Fabio Veras Soares |
| Conditional Cash Transfers as a Tool of Social Policy | – Francesca Bastagli |
| Cash Transfers as the Silver Bullet for Poverty Reduction: | |
| A Sceptical Note | – Jayati Ghosh |
PDS Forever? – Ashok Kotwal, Milind Murugkar, Bharat Ramaswami
Impact of Biometric Identification-Based Transfers – Arka Roy Chaudhuri, E Somanathan
The Shift to Cash Transfers: Running Better But on the Wrong Road? – Devesh Kapur
For copies write to: Circulation Manager,
Economic and Political Weekly,
320-321, A to Z Industrial Estate, Ganpatrao Kadam Marg, Lower Parel, Mumbai 400 013. email: circulation@epw.in
SEPTEMBER 24, 2011 vol xlvi no 39
EPW
