DISCUSSION
Counting and Profiling the Missing Labour Force
K P Kannan, G Raveendran
This comment on “Where Is the Missing Labour Force?” (EPW, 24 September 2011) attempts to answer four questions: (1) What is the magnitude of the decline in the labour force and which segment of the population has been affected most during the two surveys, 2004-05 and 2009-10? (2) What proportion of the decline can be attributed to an increase in enrolment for education? (3) What is the economic status of those who dropped out of the labour force for reasons other than education?
(4) What is the extent of decline in the workforce, of which labour status and from which sectors of the economy?
The authors thank J Krishnamurty and Gerry Rodgers for their comments on an earlier draft and Ajaya Naik for research assistance.
K P Kannan (kannankp123@gmail.com) was earlier with the Centre for Development Studies, Thiruvananthapuram and G Raveendran (gravi19@hotmail.com) with the Central Statistical Office.
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The main ex post facto reason given for this decline in LFPR has been the increase in enrolment of young people for education that has been duly noted by official documents (Planning Commission 2011: 9-10) as well as by scholars (e g, Chandrasekhar and Ghosh 2011; Choudhury 2011 and Rangarajan et al 2011). But all of them agree that the increase in this category does not fully match the decline in the labour force. Moreover, the decline has been identified to be among women, especially in the rural areas. Choudhury (2011) has proposed that “the decline in the LFPR of women, irrespective of age, might be because of a decline in overall employment opportunities” and that “social orthodoxy may have played a role in pushing out women rather than men from the labour force”
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(2011: 24). However, C Ranagarajan, the chairman of the Prime Minister’s Economic Advisory Council, has offered a positive view when he says:
There is a high probability that some low paying jobs in the unorganised sector do not have takers as the option to study, improve skills and employability is now available with the youth. Large numbers of women are withdrawing from the labour force to attend to domestic duties. This may be a result of improved incomes and a similar phenomenon as above may be at work impacting the workforce numbers (2011: 70).
If this, indeed, is the reason, then it raises an important question as to why the decline is more among rural women engaged in such low earning activities as self-employment and casual labour and not among others.
Given the seriousness of the employment question in India, we attempt to answer the following questions in this note:
Magnitude of the Decline
In general, the NSS surveys provide underestimates of population. The level of underestimation varies from round to round. For example, the level of underestimation in 61st round was 12% for men and 9.6% for women, while it increased to 13.9% for men and 14.2% for women in 2009-10. It is, therefore, necessary to adjust the survey estimates to conform to population projections so as to have any valid comparisons between any two rounds. In this exercise, it has been done at the level of the four population segments – rural male, rural female, urban male and urban female – in each of the states. The estimates of population, labour force, workforce and unemployed and the corresponding rates thus derived
DISCUSSION
Table 1: Comparative Estimates of Population, Labour Force and Workforce (in million) applying the partici pation rates of
Category 2009-10 2004-05
2004-05 in different age groups. The
Male Female Person Male Female Person
differences between this projected and
Population 612.44 575.29 1,187.73 565.79 523.82 1,089.61 Labour force 340.46 129.90 470.36 315.94 150.84 466.78 actual estimated labour force are given
Workforce 333.59 126.84 460.43 308.81 146.89 455.70 in Table 2. Although the phenomenon
Unemployed 6.87 3.06 9.93 7.13 3.95 11.08
LFPR 55.59 22.58 39.60 55.84 28.80 42.84
WPR 54.47 22.05 38.77 54.58 28.04 41.82
UR 2.02 2.36 2.11 2.26 2.62 2.37
LFPR = Labour force participation rate; WPR = Worker participation rate; UR = Unemployment rate. Population is estimated on the basis of population growth rates between 2001 and 2011 in each of the population segments in each state.
Table 2: Age Groupwise Projected and Actual Labour Force and Differences in 2009-10 (in million)
of demographic transition in India, albeit slow, resulting in an upward shift in the age cohort of the population and improved educational attainments are likely to increase the participation rates, we have assumed constant rates
AgeGroup Projected Actual Differenceas a first approximation. Table 2 reveals Male Female Total Male Female Total Male Female Total
that there was a desirable reduction of 3.7
0-14 4.89 4.00 8.89 3.23 1.96 5.19 1.66 2.04 3.70
million children in the labour force. It
15-19 32.05 14.27 46.32 23.33 8.45 31.78 8.72 5.81 14.54
consisted of 1.66 million male and 2.04
20-24 43.64 19.39 63.03 39.52 14.24 53.76 4.12 5.15 9.27 25-29 45.95 22.07 68.02 45.54 17.12 62.65 0.41 4.95 5.36 female children.
30-34 44.10 23.22 67.31 44.11 17.11 61.22 -0.02 6.11 6.09 The answer to the first question, there
35-39 43.88 24.63 68.51 44.00 19.18 63.18 -0.11 5.45 5.34 fore, is that assuming the same LFPR for 40-44 37.10 18.66 55.76 37.37 14.81 52.17 -0.26 3.85 3.59
2009-10 as in 2004-05, the reduction in
45-49 33.89 15.72 49.62 33.99 12.72 46.70 -0.10 3.01 2.91
labour force (15 years and above) was
50-54 24.87 10.74 35.61 25.04 9.30 34.34 -0.17 1.44 1.27
51.65 million consisting of 12.81 million
55-59 18.30 8.36 26.66 18.48 6.81 25.29 -0.17 1.55 1.38
men and 38.83 women. In the case of men,
60-64 12.81 5.76 18.57 13.01 4.78 17.79 -0.20 0.98 0.78
the reduction was solely in the younger
65+ 13.45 3.96 17.41 12.85 3.44 16.29 0.60 0.52 1.11 Total 354.93 170.77 525.71 340.46 129.90 470.36 14.48 40.87 55.35 age groups and in those aged 60 years
15+ 350.04 166.77 516.82 337.23 127.94 465.17 12.81 38.83 51.65 and above. The reduction in the case of
25+ 317.99 152.50 470.50 313.90 119.49 433.39 4.09 33.02 37.11 women was across all the age groups but the maximum reduction was in the age
Table 3: Age Groupwise Projected and Actual Number of Persons Attending Educational Institutions and Differences in 2009-10 (in million) group of 30 to 34. In fact, 72% of the
Age Group Projected Actual Differencewomen who dropped out of the labour Male Female Total Male Female Total Male Female Total
force were in the age group of 25 years and
0-14 117.85 93.61 211.46 124.69 103.06 227.75 -6.84 -9.45 -16.29
above compared to a marginal increase
15-19 32.22 21.04 53.27 40.78 28.49 69.27 -8.56 -7.45 -16.01
in entry into the labour force for men.
20-24 7.07 3.96 11.03 10.96 6.62 17.58 -3.89 -2.66 -6.55
25-29 0.79 0.25 1.04 1.04 0.59 1.63 -0.25 -0.34 -0.59
Decline Due to Education
30-34 0.06 0.03 0.09 0.05 0.05 0.10 0.00 -0.02 -0.02
35-39 0.01 0.04 0.05 0.00 0.02 0.02 0.00 0.02 0.02 There has been a consistent increase in
40-44 0.00 0.02 0.02 0.00 0.03 0.03 0.00 -0.01 -0.01 the percentage of people attending 45-49 0.00 0.01 0.01 0.00 0.00 0.00 0.00 0.01 0.01
educational institutions and a conse
| 50-54 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
|---|---|---|---|---|---|---|---|---|---|
| 55-59 | 0.01 | 0.02 | 0.03 | 0.00 | 0.03 | 0.03 | 0.01 | -0.01 | 0.00 |
| 60-64 | 0.01 | 0.01 | 0.02 | 0.00 | 0.01 | 0.02 | 0.00 | 0.00 | 0.00 |
| 65+ | 0.04 | 0.02 | 0.06 | 0.10 | 0.02 | 0.12 | -0.06 | 0.00 | -0.06 |
| Total | 158.05 | 119.02 | 277.07 | 177.64 | 138.93 | 316.57 | -19.59 | -19.91 | -39.50 |
| 15+ | 40.20 | 25.41 | 65.61 | 52.95 | 35.86 | 88.81 | -12.75 | -10.46 | -23.20 |
from the data are given in Table 1. All the results presented here are estimates based on the unit level data. Labour force and workforce data refer to the Usual Principal and Subsidiary Status.
The estimates reveal an absolute reduction of 20.94 million women in labour force and 20.05 million in workforce during 2009-10 as compared to 2004-05, although the share of women in the population improved from 48.1% in 2004-05 to 48.4% in 2009-10. In other words, there was an average annual rate of decline of about 2.9% in the female labour force, while there was an average growth rate of 1.9% in female population between 2004-05 and 2009-10. In the case of men, the labour force growth rate was 1.5% as compared to the male population growth rate of 1.6%. These estimates do not take into account the expected increase in labour force, if the participation rates of 2004-05 continued till 2009-10. For our purposes of measurement, we therefore, work out the decline by estimating the projected labour force in 2009-10 by
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quent reduction in the labour force participation rates of those in the younger age groups. In order to factor this phenomenon in the reduction of the labour force, we projected the number of people likely to have been attending the educational institutions in 2009-10 by applying the attendance rates of 2004-05. The projected numbers along with the actual estimates and differences are given in Table 3. As expected, there were
16.29 million additional children, consisting of 6.84 million boys and 9.45 million girls attending educational institutions in 2009-10. The net addition in the other age groups was 23.20 million over and above the projected number of persons attending educational institutions. It consisted of 12.75 million men and
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DISCUSSION
10.46 million women. Thus, among the
12.81 million men who went out of labour force, 12.75 million were in the educational institutions.
The answer to the second question, therefore, runs as follows. All the men who dropped out of the labour force have been accounted for by the additional enrolment for education. Of the 38.83 million women who dropped out of the labour force only 27% is accounted for by the additional enrolment for education.
Therefore, the status of the remaining 28.38 million women has to be examined focusing on those aged 25 years and above. The labour force in 2009-10 by assuming the participation rates of 2004-05 in the age group of 25+ was projected and the difference between the projected and estimated labour force in different monthly per capita consumption expenditure (MPCE) deciles was estimated. The results are given in Table 4. There was an aggregate shortage of 28.16 million women in the labour force which is almost equal to the net shortage after adjusting for educational impact. The first five deciles accounted for 17.04 million (61%) of the missing women labour force in the age group 25 and above. The next three deciles accounted for
7.27 million (26%) and the last two deciles accounted for 3.85 million (13%) of the missing female labour force. It also needs to be noted that 83% of the missing women labour force is in rural areas.
In order to find the current status of the missing labour force the same analysis was repeated for those categorised as attended domestic duties only (Code 92) and attended domestic duties and was also engaged in free collection of goods, sewing, tailoring, weaving, etc (Code 93). The results are given in Table 5. While there was a shortage of 28.16 million women aged 25 years and above, the additional women in the categories of Code 92 and Code 93 were 29.19 million. In almost all the lower deciles, except the first one, there were additions of small numbers. However, in the last two deciles, there were shortages as compared to missing women. It is thus clear that those 28.16 million women, who
Table 4: Differences between the Projected and Estimated Labour Force Aged 25+ by MPCE Deciles Group in 2009-10 (in million)
ought to have been in the labour force, are compelled to confine themselves in the four walls of their dwellings despite poor living conditions.
The answer to the third question, therefore, is that an overwhelming proportion of women who dropped out of the labour force were from rural areas belonging to economically poor households. To the extent that a small proportion belonged to the higher economic groups, the withdrawal of such women could be interpreted as arising out of an improvement in the economic status.
Impact on Women
The reduction in labour force also had an almost equivalent reduction in workforce. However, the reduction is not uniform across different industry groups and acti vity statuses. Assuming that the same WPR for 2009-10 as that in 2004-05, the differences between projected and estimated men workers in different industry groups are presented in Table 6 (p 80) and the same for women are given in Table 7 (p 80). In the case of men aged 15 and above, there was a net reduction of 13.07 million workers. The largest reduction of 17.75 million workers was in
MPCE Decile Rural Urban Rural + Urban
agriculture followed by 4.68 million work
Male Female Total Male Female Total Male Female Total
ers in manufacturing and 1.89 million in
0-10 0.10 2.37 2.48 0.06 0.93 0.99 0.17 3.31 3.47
trade. However, the construction sector
10-20 -0.22 2.37 2.15 0.11 0.60 0.71 -0.10 2.97 2.86
20-30 -0.29 3.29 3.00 -0.09 0.69 0.60 -0.38 3.98 3.60 employed 11.57 additional workers, 96%
30-40 -0.03 3.00 2.97 -0.11 0.61 0.49 -0.14 3.60 3.46 of them casual labour. The reduction was
40-50 0.00 2.72 2.72 0.11 0.47 0.58 0.11 3.19 3.30 primarily in the categories of own account 50-60 0.01 2.39 2.40 0.06 0.17 0.23 0.07 2.55 2.63
worker, unpaid family worker, employers
60-70 -0.02 2.10 2.08 0.22 0.36 0.58 0.21 2.45 2.66
and regular wage paid employees. How
70-80 0.04 1.97 2.00 0.22 0.30 0.52 0.26 2.26 2.52
ever, there was a net addition of casual
80-90 0.24 1.93 2.17 0.19 0.43 0.62 0.43 2.36 2.79
workers over and above the projected
90-100 0.22 1.29 1.51 0.18 0.20 0.37 0.40 1.48 1.88
workers to the tune of 10.32 million. In
Total 0.07 23.41 23.48 0.94 4.75 5.69 1.01 28.16 29.17
the construction sector, the increase in
Table 5: Difference between the Projected and Estimated Persons in Activity Status 92 and 93 by MPCE
casual labour was 11.09 million. It appears
Deciles Group in 2009-10 (in million)
that men were pushed out of household
MPCE Deciles Rural Urban Rural + Urban
Male Female Total Male Female Total Male Female Total
agricultural and manufacturing activities
0-10 -0.03 -2.53 -2.56 -0.04 -0.72 -0.76 -0.07 -3.25 -3.32
to casual labour in construction.
10-20 0.01 -2.56 -2.55 -0.02 -0.63 -0.65 -0.01 -3.19 -3.20
In the case of women, there was a net
20-30 0.04 -3.56 -3.52 0.01 -0.76 -0.75 0.05 -4.32 -4.27
reduction of 36.35 million workers in agri
30-40 -0.02 -3.27 -3.29 0.03 -0.60 -0.57 0.02 -3.88 -3.86
culture and 4.59 million in manufacturing.
40-50 -0.03 -2.70 -2.73 -0.03 -0.49 -0.52 -0.06 -3.20 -3.26 50-60 0.02 -2.53 -2.51 -0.02 -0.30 -0.32 -0.01 -2.82 -2.83 The reduction was primarily in the case
60-70 0.04 -2.24 -2.19 0.00 -0.27 -0.27 0.04 -2.51 -2.47 of unpaid family workers, own account
70-80 -0.02 -2.07 -2.10 0.01 -0.45 -0.44 -0.01 -2.52 -2.53 workers, regular wage paid employees 80-90 -0.05 -1.94 -1.99 -0.02 -0.26 -0.28 -0.07 -2.20 -2.27 and casual workers although there was 90-100 -0.04 -1.24 -1.28 -0.01 -0.06 -0.07 -0.05 -1.30 -1.35
an increase in the casual labour of public
Total -0.07 -24.65 -24.72 -0.09 -4.54 -4.63 -0.17 -29.19 -29.35
works in construction and agriculture.
Activity Status 92 = attended domestic duties only; Activity Status 93 = attended domestic duty along with free collection of goods (vegetables, roots, firewood, etc), sewing, tailoring, weaving, etc, for household use. The former seems to be the impact of the
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DISCUSSION
Table 6: Differences in Projected and Actual Workforce of Men Aged 15 Years and Above in 2009-10 (in million) due to education. For women only 27%
Industry Group Own Account Worker Employer Unpaid Family Regular Wage Casual Labour in Casual Labour Total
could be accounted for due to additional
Worker Employee Government Work
enrolment for education. Of the remain-
Agriculture 7.85 0.68 7.74 0.79 -0.01 0.70 17.75 Mining 0.03 0.00 -0.03 -0.07 0.00 0.03 -0.04 ing women, 83% belonged to rural areas.
Manufacturing 1.75 0.00 1.28 1.11 0.02 0.53 4.68 By examining the decline in workforce,
Electricity -0.01 -0.01 -0.01 0.25 0.00 -0.03 0.20 we find 53 million of which 44% has been
Construction 0.16 0.19 -0.06 -0.76 -1.86 -9.23 -11.57
due to additional enrolment for education.
Trade 0.52 0.22 0.23 0.85 0.00 0.07 1.89
Hotels 0.12 0.04 0.01 0.01 0.00 -0.10 0.08
Transport 0.28 0.14 0.07 -0.12 0.02 -0.46 -0.06
Finance -0.09 0.00 0.01 -0.44 0.00 -0.03 -0.55
Real estate -0.18 0.07 0.05 -0.85 0.00 0.02 -0.88
Administration 0.04 0.00 0.00 0.18 0.03 -0.06 0.20
Education 0.34 0.01 0.01 -0.09 0.01 -0.02 0.26
The remaining are all women who seem to have gone back to domestic activities with or without engaging in non-monetary work but economically important chores.
Given the fact that most of those who have gone out of the labour force are
Health 0.20 -0.01 0.01 0.16 0.01 0.00 0.36 women from rural areas and overwhelm-
Community 0.24 -0.06 0.36 0.21 0.00 0.07 0.82
Household 0.00 0.00 0.00 -0.04 0.00 -0.04 -0.07
Total 11.25 1.27 9.68 1.19 -1.77 -8.55 13.07
Table 7: Differences in Projected and Actual Workforce of Women Aged 15 Years and Above (in million)
Industry Own Account Worker Employer Unpaid Family Regular Wage Casual Labour in Casual Labour Total Worker Employees Government Work
Agriculture 4.07 0.24 24.10 0.30 -0.17 7.81 36.35
Mining 0.00 0.00 -0.01 0.00 0.00 0.15 0.13
ingly belonging to poorer households, raises an important question of work and welfare. The fact that the NREGS seems to have made only a marginal impact, the question of gainful employment for poor women in general, and rural women in particular, continues to be quite relevant
Manufacturing 1.37 0.05 2.40 0.71 0.00 0.07 4.59 in a fast growing India. In any case, our
Electricity 0.00 0.00 0.00 -0.04 0.00 0.00 -0.05
Construction -0.02 0.00 -0.01 -0.03 -2.12 -1.12 -3.31
Trade 0.29 -0.02 0.62 -0.09 0.00 0.03 0.84
Hotels 0.08 -0.01 0.18 0.05 0.00 0.01 0.31
Transport 0.01 0.00 0.05 0.05 0.01 -0.08 0.04
Finance -0.08 0.00 0.01 -0.04 0.00 0.00 -0.11
Real estate 0.00 0.00 0.03 -0.16 0.00 -0.01 -0.14
Administration 0.00 0.00 0.00 -0.24 0.01 0.01 -0.23
exercise does not support the hypothesis that the withdrawal of women could be due to improved economic conditions.
This news of an economy wide “jobless growth” might have come as a shocker to the policymakers, especially those in the Planning Commission. Instead of “shoot-
Education 0.23 0.01 0.07 0.03 0.01 -0.03 0.30 ing the messenger” (EPW 2011), the results
Health 0.02 0.01 0.01 -0.02 0.00 0.00 0.02
Community 0.24 0.01 0.41 -0.56 0.00 -0.41 -0.31
Household 0.00 0.00 0.00 1.16 0.00 0.34 1.49
Total 6.20 0.29 27.86 1.09 -2.27 6.76 39.93
Table 8: Accounting for the Decline in Labour Force and Workforce loss of employment as casin 2009-10 (in Million)
ual labour in agriculture in
Male Female Total
rural areas also affected the
A Decline in Labour Force 1 Decline in labour force 12.81 38.83 51.65 women, pushing them back
2 Decline due to education 12.75 10.46 23.20
to the household. This is our
3 Decline due to other than (2) 28.37 28.45
“economic” explanation. Is
4 Share of those in (3) belonging to
this the result of social
rural area (%) -83.00
orthodoxy? We are not sure.
B Decline in Workforce 1 Decline in workforce 13.07 39.93 53.00 Men in self-employment in
2 Decline due to education 12.75 10.46 23.21 agriculture and related acti3 Net decline after deducting (2) 0.32 29.47 29.79
vities seem to have sought
4 Addition to activity status 92 and 93 0.17 29.19 29.36
work as casual labour in
5 Residual 0.15 0.28 0.43
the expanding construction
National Rural Employment Guarantee Scheme (NREGS).
The scenario seems to be a case where men lost some of their self-employment activities leading to a greater number of women losing their status as unpaid family labour since many self-employment activities of men in rural areas are assisted by women as unpaid family labour. The sector. Since much of this construction took place in urban areas this could have led to migration of such men from rural areas.
Summing-up
We sum up our exercise in Table 8. While the labour force declined by 51.65 million, 45% of it has been due to additional enrolment for education. For men, it is all
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should have been subjected to a coolheaded and detailed examination as much for a realistic understanding as for pondering over its implications. Of course, the NSS 66th round has called the bluff of the Planning Commission’s claim to create 50 million additional jobs during the Eleventh Plan; at the same time, it has also brought before the country some much needed welcome news of accelerated enrolment of girls and boys for education as well as an increase in an otherwise starvation wages of the mass of casual labour.
References
Chandrasekhar, C P and J Ghosh (2011): “Latest Employment Trends from the NSSO”, Business Line, 12 July.
Choudhury, S (2011): “Employment in India: What Does the Latest Data Show?”, Economic & Political Weekly, 6 August , Vol XLVI, No 32.
EPW (2011): “Don’t Shoot the Messenger”, editorial, Economic & Political Weekly, 9 July, Vol XLVI, No 28.
Planning Commission (2011): Faster, Sustainable and More Inclusive Growth: An Approach to the Twelfth Five-Year Plan (New Delhi: Planning Commission, Government of India), April.
Rangarajan, C, Padma Iyer Kaul and Seema (2011): “Where Is the Missing Labour Force?”, Economic & Political Weekly, 24 September, Vol XLVI, No 39.
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