Sunday, February 21, 2016

Comparing Census and NSS data on employment and unemployment


Reproduced from my article in the Economic and Political Weekly May 30, 2015





Unemployment rates in India are not particularly interesting. Available most frequently from the National Sample Survey (NSS), they are relatively low and have barely changed over the years.

Recently available census data provides far higher estimates of unemployment than the NSS.[1] Census unemployment numbers are especially high for youth aged 15 to 29 who are new entrants to the labour force. Over forty million youth are seeking work and the unemployment rate stands at above 15% and 30% for young men and women respectively.[2]These numbers make the case for a closer look at census and NSS employment and unemployment data to understand why they differ and what they represent.

This article begins with a brief discussion of the census and NSS methodologies to identify comparable data from the two data sets. This is followed by a comparison of aggregated employment, underemployment and unemployment data from the two sources to see how well they agree and how that agreement has changed over time. The last section looks at disaggregated data from the last census for clues to explain the wide difference in unemployment estimates.

Areas of broad compatibility

For estimates from two different data collection exercises to be comparable, they must at a minimum work with similar concepts and have the same reference period[3].  The areas of broad compatibility between the NSS and the census starting with the 1991 census are briefly captured below.[4]

Both the NSS and the census divide the country into rural and urban areas for data collection in a mutually consistent manner.[5] The census uses a reference period of one year for employment data and the NSS also provides data for such a period.

The census provides only limited data on employment and unemployment. It separates the population into ‘workers’ and ‘non-workers’ and provides estimates of the number of ‘workers’, the extent of underemployment among ‘workers’ and unemployment among ‘non-workers’. These then are the data of interest for a comparison between the census and NSS.

Both the census and the NSS have similar criteria for identifying ‘workers’ and the ‘unemployed’. ‘Workers’ are persons engaging in ‘economic activity’ and the set of production related activities accepted as ‘economic activity’ is almost the same in both exercises. The ‘unemployed’ among the non-working population are identified by determining if they are ‘seeking work or available for work if there is work available’. In urban areas, this test requires a person to be making tangible efforts to obtain work. In rural areas it is less stringent and only requires that a person be available for work if work is available. Both exercises estimate underemployment in workers and both identify students in the non-working population.

Getting to the specifics, Census B Series tables provide the count of ‘main workers’ - workers who have worked six months or more in the last year and ‘marginal workers’ – those who have worked less than six months.[6] The broadest count of workers is obtained by adding the count of ‘main workers’ and the count of ‘marginal workers’. From among the rest termed the ‘non-workers’, those who pass the test of ‘seeking or available for work’ make up the count of the census unemployed.[7] The census also measures underemployment among ‘marginal workers’ by applying the above test. Non-workers are additionally categorised by ‘main activity’ including as ‘students’ and persons ‘engaged in household duties’.

In the NSS, a person’s ‘activity status’ can be ‘worker’, ‘unemployed’ or ‘not in the labour force’ during the reference period and the ‘principal status’ is determined by  the ‘activity status’ in which relatively longer time has been spent (also referred to as the ‘major time’ criteria). [8] The broadest count of workers with a 1 year reference period is obtained from the tabulation referred to as ‘usual activity status (principal status + subsidiary status)’ in the NSS “Employment and Unemployment Situation” reports.[9] This includes persons whose ‘principal activity status’ is ‘worker’ as well as persons whose ‘principal activity status’ is other than ‘worker’, but who have worked for at least 30 days in the reference period. This tabulation also provides the categorization of non-working persons as ‘unemployed’, ‘students’ and as those ‘engaged in domestic duties’. The NSS additionally provides several indicators of underemployment among ‘workers’ which will be discussed later.

Worker population ratios

Large sample surveys are conducted every five years and the NSS large sample rounds closest to census years have been selected for the comparison. Table 1 compares NSS and census worker population ratios across 3 censuses. The female worker population ratios in the NSS (1993-94) round show a large difference with the corresponding ratios of Census 1991.

Table 1. Workers in every 1000 persons aged 15 and above


Men
Women

Rural
Urban
Rural
Urban
Census - 1991
825
726
406
136
NSS (1993-94)
864
768
486
223
Census - 2001
810
720
463
167
NSS (1999-00)
841
752
452
197
Census - 2011
779
724
430
202
NSS (2011-12)
800
741
352
195

Source: Census of India[10] and NSS ‘Employment and Unemployment Situation in India’ reports[11]

A government committee of experts that was privy to the 1991 census data attributed the differences in census and NSS estimates to two main factors – a) differences in the set of activities that constituted ‘economic activity’ and b) differences in the minimum time spent working to be considered a ‘worker’.[12] 

More specifically, the National Statistical Commission (also known as the Dr Rangarajan Commission) was of the view that the exclusion of certain non-market economic activities from the definition of work adopted in the census could be the reason for the low female worker population ratios of Census 1991 in comparison with the NSS 50th round.[13]

The scope of non-market economic activities was expanded in Census 2001 by treating persons engaged in cultivation and growing of crops solely for domestic consumption and persons engaged in rearing of animals for production of milk for their own use as ‘workers’.[14] There is a dramatic improvement seen in the agreement between Census 2001 and NSS female workforce ratios, possibly as a consequence of this change. The differences in the male workforce ratios have also narrowed further compared to Census 1991.

Census 2011 shows a further narrowing of differences with NSS workforce estimates for rural men and urban men and women. The only spoiler is the count of rural working women where there is a large difference.[15]

The sharp fall in rural female workforce ratios seen in both the NSS 66th round (2009-10) and the NSS 68th round (2011-12) compared to NSS 61st round (2004-05) without any accompanying increase in unemployment has puzzled researchers following employment trends. There is an extensive literature attempting to throw light on this phenomenon termed the “missing labour force”.[16] If Census data is to be believed, much of the rural female labour force may not have gone missing at all.

The next two sections feature comparisons of underemployment and unemployment estimates. The comparisons will be confined to Census 2001 and Census 2011 which have better comparability with NSS data than Census 1991 for reasons stated earlier.

Underemployment in workers

The census, as mentioned earlier, counts the number of ‘marginal workers’ who are seeking or available for work.This is a measure of underemployment in workers who have worked for less than six months.

The NSS has several indicators of underemployment among usual workers. Among them, the one with a liberal interpretation of underemployment, is the one which measures usual workers (principal status+ subsidiary status) who were without work for at least 1 month and who sought or were available for work on at least some days during those month(s). Table 2 shows the underemployment numbers from the census and the range provided by this NSS indicator.

Table 2. Underemployed workers in every 1000 persons aged 15 and above


Men
Women


Rural
Urban
Rural
Urban
Census - 2001
52
25
36
9
NSS (1999-00)
183-203
67-75
93-112
19-25
Census - 2011
98
32
69
17
NSS (2011-12)
155-160
48-53
58-62
15-16

Source: Census of India and NSS ‘Employment and Unemployment Situation in India’ reports[17]

As the table shows, the census generally underestimates underemployment when compared with this NSS indicator. The probable reason for the wide margin of underestimation is that the census does not test ‘main workers’ – those who have worked greater than six months in the year - for underemployment. This means that the census population for the underemployment test is far smaller than the NSS population which includes all workers.

Unemployment and underemployment in non-workers

Table 3 compares census figures of non-working persons ‘seeking work’ with the NSS numbers of ‘unemployed’ for the last two censuses. NSS figures show dramatically lower unemployment than the census.

Table 3. Non-workers seeking work in every 1000 persons aged 15 and above


Men
Women

Rural
Urban
Rural
Urban
Census – 2001
44
84
54
106
NSS (1999-00)
15
35
5
12
Census – 2011
48
61
79
94
NSS (2011-12)
14
23
6
11

Note: Census number refer to non-workers seeking or available for work; NSS numbers are for those termed ‘unemployed’
Source: Census of India and NSS ‘Employment and Unemployment Situation in India’ reports

The National Statistical Commission noted many years back that NSS estimates of unemployment were low because of the definitions and concepts followed in its framework of employment and unemployment.[18]

What are the definitions and concepts in the NSS framework that makes its unemployment estimates low compared to the census?

The NSS uses the ‘major time’ criteria to decide if non-workers are ‘unemployed’ or outside the labour force.[19] Persons spending a major portion of their time in study or domestic duties are considered to be outside the labour force. They do not add to the count of the ‘unemployed’ even if they are seeking work.

In the census, on the other hand, the test of ‘seeking work’ is applied to all non-workers without any hard time criteria associated with it. Persons spending a major portion of their time in study or household duties can still qualify the test and be counted among the census unemployed.[20]

Students and unemployment

The above arguments, to the extent that they involve the double counting of students among the unemployed in the census, can be substantiated by examining age disaggregated data on non-working men (Table 4). The discussion can be limited to men in the age group 15-29 without compromising the analysis as this group accounts for 85% of the census unemployed.

Table 4. Age disaggregated profile of non-working men seeking work gathered from Census 2011 and NSS 2011-12


Census
NSS

Age group
Not working
Of which

‘Unemployed’
Students
Seeking work
* Students seeking work
Rural
15-19
659
544
128
72
30

20-24
294
190
117
51
46

25-29
107
26
50
0
21
Urban
15-19
768
651
140
76
33

20-24
430
295
161
68
70

25-29
164
47
77
0
45

Notes: Numbers are ratios per 1000 population; * Lower bound on number of students seeking work
Source: Census of India[21] and NSS “Employment and Unemployment Situation in India” report

The census count of those seeking work far exceeds the NSS count of ‘unemployed’ for each age group as expected. Census numbers indicate that the bulk of non-working men of age 15-24 are students. Some of them can be expected to figure in the census count of those seeking work. A lower bound on the number of students seeking work has been computed and presented in Table 4 using the detailed breakup of non-workers by ‘main activity’ published as part of the census. [22]

The NSS count of male ‘unemployed’ agrees more closely with the census numbers after students seeking work have been excluded from the latter. It needs to be re-emphasised that what is listed in Table 4 is only a lower bound and exact numbers of students seeking work, if available, will further improve the fit between census and NSS data on unemployment among non-students. Even with the available data, it is clear that the census unemployment is much higher than NSS unemployment in males predominantly because it factors in students seeking work.

Women engaged in domestic duties and unemployment

Census figures indicate that one must consider women between 15 and 39 to account for 80% of female unemployment. Since disaggregated data is not available for this range from both census and NSS, the discussion below is with aggregated numbers. Table 5 presents data from the census and NSS for non-working women aged 15 and above. NSS data shows that these women are overwhelmingly students or engaged in domestic duties according to the ‘major time’ criteria.

Table 5. Profile of non-working women aged 15 and above seeking work gathered from NSS 2011-12 and Census 2011


NSS
Census
Not working
Of which
‘Unemployed’
Women in DD available for work^
Seeking work
of which
Engaged in domestic duties(DD)
Students
‘Non-students’ seeking work *
Rural
648
499
85
6
33
79
54
Urban
806
611
122
11
41
94
59

Notes: Numbers are ratios per 1000 population; ^ Estimate of the number of non-working women usually engaged in domestic duties who are willing to take up regular full time work at home;* Upper bound on the number of ‘non-students’ seeking work
Source: Census of India[23] and NSS report “Participation of women in specified activities along with domestic duties”[24]

The census data allows a rough division of the total number of women ‘seeking work’ between students and ‘non-students’.[25] Table 5 lists the upper bound on the number of ‘non-students’ seeking work. From the NSS perspective, these non-students would almost entirely be women engaged in domestic duties.[26]

Again from the NSS perspective, non-working women who spend ‘major time’ in domestic duties would not qualify as ‘unemployed’ even if they were seeking work. However, the NSS recognizes this situation as a form of underemployment and provides several indicators of its extent. One such indicator – the number of non working women, engaged principally in domestic duties, that are willing to take up regular full time work if offered such work at home – is also shown in Table 5.

It can be seen that there is a fair agreement between the census numbers of ‘non-students’ seeking work and the aggregate of the NSS numbers of ‘unemployed’ and women primarily engaged in domestic duties who are available for work at home full time. Too much should not be read into the agreement as the NSS and census ‘tests’ of the availability of women engaged in domestic duties for work are not quite the same.

Nontheless, the available evidence makes it clear that census unemployment in women is far higher than NSS unemployment predominantly because it factors in students seeking work as well as women, primarily engaged in domestic duties, seeking work.

Concluding remarks

The comparison of NSS and census data reveals that the differences in employment estimates have narrowed over the last three censuses, the only exception being the estimates of rural women in Census 2011. This exception merits further study especially because the NSS numbers have not been on expected lines.

The NSS provides several indicators of underemployment among workers; however none of these are strictly comparable with census data as the coverage of workers is different in the two exercises.

Census unemployment estimates are far higher than the NSS estimates because they also include students and persons primarily engaged in domestic duties who are seeking work. The desire for work in students and in women primarily engaged in domestic duties is in some sense a reflection of underemployment in these sections. The census unemployment estimate, in this sense, is an aggregate estimate of the unemployed and underemployed.

While the underemployment among women engaged in domestic work is an ongoing part of NSS employment studies, it has been left to the census, with its relatively crude methodology, to uncover the extent of the latent Indian youth labour force.

References:

Census (2011), “Instruction Manual for Updating of Abridged House list and Filling up of the Household Schedule”, Census of India, (http://censusindia.gov.in)

Hirway, Indira (2012): “Missing Labour Force, An Explanation”, Economic and Political Weekly, vol xlvii no 37, Sept 15, 2012

NSC (2001), “Report of National Statistical Commission”, Sept 5, 2001, (http://mospi.nic.in)

NSSO (2008), “Review of Concepts and Measurement Techniques in Employment and Unemployment Surveys of NSSO”, National Sample Survey Organisation, Dec 2008, (http://mospi.nic.in)

NSSO (2014a), “Employment and Unemployment Situation in India, NSS 68th round”, National Sample Survey Organisation, Jan 2014, (http://mospi.nic.in)

NSSO (2014b), “Participation of Women in Specified Activities along with Domestic Duties”, NSS 68th round”, National Sample Survey Organisation, Sept 2014, (http://mospi.nic.in)

Thorat Amit (2004), “NSS Employment Surveys; Problems with comparisons over time”, October 2004, Viewed on 10 Feb 2015 (http://www.macroscan.org/anl/oct04/pdf/NSS_Data_Critique.pdf)



[1] Census 2011 tables containing data on workers were released in Sept 2014. The Census estimate of unemployment in urban men aged 15 and above exceeds the NSS estimate by a factor of 2.6. The factors for rural men and rural and urban women are much higher.
[2] Data from Table B1, Census 2011
[3] The ‘reference period’ is the period to which the data pertains
[4] For a brief historical overview of the problems of comparing NSS and census employment data starting from the 1951 census, see Thorat (2004)
[5] See Sec 1.5 NSSO (2014a) for a description of survey sampling in rural and urban areas
[6] Census B series tables for various years are available at the Census of India website (http://www.censusindia.gov.in)
[7] The census figures of ‘seeking or available for work’ are popularly interpreted as unemployment figures though it must be pointed out that the census itself refrains from using the term ‘unemployed’.
[8] A complete explanation of the ‘major time’ criteria may be found in Sec 2.21 of NSSO (2014a)
[9] These reports are available at the Ministry of Statistics and Program Implementation website (http://mospi.nic.in/)
[10] Ratios computed by author using population figures from the Table B1 for various years
[11] Data is from the ‘usual activity status (ps+ss)’ table 
[12] Sec 10.1, NSSO (2008)
[13] Sec 9.4.34 (xiv) , NSC(2001)
[14] See Metadata of Census 2001 at Census of India Website
[15] The census and NSS have different minimum time criteria for categorising persons as workers (30 days in NSS, none in census). Census data for 2011 shows that only 37 in 1000 rural women aged 15 and above were ‘marginal workers’ working less than 3 months. Even if all of these were missed out by the NSS, it would account for only a small part of the NSS underestimation.
[16] See Hirway (2012) for a summary of the various explanations attempted
[17] NSS data for 2011 is from Table 61 of NSSO (2014a). The table provides estimates of ‘usual status workers (ps+ss)’ who were without work for at least 1 month and who sought or were available for work on at least some days during those month(s). This number (N) is regardless of the age of the workers, and may include some workers below 15 years of age. ‘N’ serves as an upper bound of this indicator of underemployment among workers of age 15 and above. A lower bound is obtained by subtracting the total number of ‘usual status (ps+ss)’ workers aged below 15 from N
[18] Sec 9.4.27 (a) of NSC(2001)
[19] See note 8
[20] Sec 6.166, Census(2011)
[21] Raw data is from Tables B1 and B13 of Census 2011. Authors computation of  the number of students seeking work is explained in note 22
[22] Table B1of the census provides the total number of non-workers seeking work (U). Table B13 divides non-workers into categories by ‘main activity’ including the categories of ‘students’ (S) and ‘others’ (O). According to the census enumeration guidelines all ‘non-workers’ seeking work, other than students, are placed in the category ‘others’. The ‘others’ category also includes some persons who are not seeking work. (Sec 6.160, Census(2011)) ‘O’ is therefore an upper bound on the number of non-students seeking work and (U-O) represents a lower bound on the number of students seeking work
[23] ibid
[24] Table 6 of NSSO (2014b) provides the fraction of women aged 15 and above, usually (principal status) engaged in domestic duties and without subsidiary status work, who are ready to accept work at home. Table 5 provides the fraction of those willing to work at home (irrespective of subsidiary status) that are ready to accept regular full time work. The estimate of ‘women in domestic duties available for work’ is arrived at by applying these two fractions to the estimate of women usually engaged in domestic duties and without subsidiary status work (Table 2)
[25] See note 22
[26] As an example, after removing students from the rural ‘non-working’ women aged 15 and above, women engaged in domestic duties constitute nearly 90% of the rest (Table 2, NSSO(2014b))


Links:

Another paper analyzing the same data sets as above - India's rural transformation: A myth or reality?

Links to this article:
1. Changes_in_indias_rural_labour_market_in_the_2000s
2. Positives_outweighing_negatives_the_experiences_of_Indian_crowdsourced_workers
3. Emerging_Trends_and_Patterns_of_India%27s_Agricultural_Workforce_Evidence_from_the_Census
4. indias-unemployment-rate-conundrum
5. Changing Employment and Enterprise Structure in Gujarat: 1990-2005

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