To begin with, it is relevant to point out that
the term ‘employment’ has generous interpretations in India’s workforce
statistics. In addition to those gainfully employed on a full time basis, it
also includes unpaid workers, part timers, apprentices, etc. Oddly, it includes
almost anyone who may have done even a few days of work during the year. It
therefore becomes necessary to draw distinctions when unravelling statistics
and not rely solely on the headline figure.
Methodology and definitions
India has no hard data on employment. Very
few people, in any event, pay taxes and there is no system to collect payroll data,
which is the norm in most other countries. India therefore has to rely on
survey-based statistics. Primarily there are two sources for this. First, the
National Sample Survey Organisation (NSSO), which undertakes a comprehensive
survey but only every five years; second, the Labour Bureau, which publishes a
more frequent survey, annually. Strangely, despite similar definitions and with
a sizeable sample, exceeding interviews with 100,000 households, figures from
the two sources do not always match. Worse, there are internal conflicts such
as state totals not adding up to the national count. The only way to enable any
sort of comparison is through recalibrations and adjustments, which we
therefore had to do. One would logically assume that the most comprehensive
survey would be the national census. However, this is undertaken only once in a
decade. Its findings are released 5-6 years later and are therefore practically
useless. Consequently, our research used NSSO data for 2004-05 and 2011-12
along with Labour Bureau data for 2011-12 and 2015-16.
The workforce
for the purposes of this exercise is defined as adults above the age of 14
years, seeking work. This would include those currently employed, either with a
full time job or part time, as well as the unemployed. Everybody else is
defined as being out of labour force (OLF).
This includes students, home-makers, pensioners, invalids and really anybody not
looking for a job. Therefore, the workforce plus OLF constitutes the adult
population of the country.
Gross employment hides more than it
reveals
The way the statistics are commonly
presented makes no distinction between full and part time employees. Therefore,
even those that may have worked for a few weeks in a year are counted as those
with a job. Based on these definitions which at the risk of reinforcement are obvious
over-estimates, employment fell from 467 million in 2011-12 to 462 million in
2015-16. During the same period, the figure for the unemployed rose from 10
million to 18 million. The comparative sums for the period between 2004-05 and
2011-12 are 451 million employed and 11 million unemployed, leading to the deduction
that things have worsened in the more recent time period. However, a more
complete break down of the population into the following categories – full
time, part time, unemployed and OLF – led to different conclusions. Those with proper,
full-time jobs actually rose from 409 million to 444 million in the four year
period i.e. 35 million new full-time jobs in four years, or 8.6 million a year.
Against this, 26 million jobs were created in the previous 7-year period, from
383 million to 409 million, at an annual accretion of a mere 3.7 million jobs a
year. The comparison is turned on its head.
What has really changed is part time
employment. In 2004-05, there were an astonishing 68 million people who were part
time workers. They were effectively bloating the employment count as many of
them may have worked for no more than a few weeks in the year. By 2011-12 that number
dropped only slightly to 58 million. The real change happened thereafter with
part timers falling to 19 million by 2015-16. This prompts the question, where
did these 39 million people end up? Since unemployment increased by only 8
million during this period, it would imply that the remaining 31 million people
either shifted to full time jobs or, more plausibly, chose to stop working, a
conclusion substantiated by the swell in the OLF population from 377 million to
446 million. The fact is, many part timers were really students who should not
have been working in the first place or home makers doing extra jobs possibly
to make ends meet. Their exit from the workforce would suggest that the earlier
compulsions no longer apply, presumably because incomes have risen and
non-working options have become feasible or preferable. One could conversely argue
that they exited because those jobs were no longer available. This may well be
true in some cases but is unlikely to explain the majority of the shift. A
scenario in which full time jobs are being created at more than twice the
earlier rate while proxy indicators are robust, cannot logically be reconciled
with a large-scale evaporation of part time jobs.
In terms of sectors, agriculture remains
the largest employer in the country. However, aggregates have dropped over the
ten year period FY05 to FY16 from 253 million to 211 million. There has been a
commensurate rise in sectors such as construction, trade and other services. This
should also be construed as good news since agriculture is the least productive
sector of the economy and services, the most. Over the ten year period, the share
of employment in services has risen from 32% to 44%.
What about unemployment?
Official unemployment, as previously
mentioned, increased from 11 million to 18 million between FY05 and FY16. Here
again, the headline figure does not tell the full story. The fact is, there
were 107 million unpaid workers in
2004-05, which incorrectly are counted as ‘employed’. These are basically
family members working in household enterprises, ‘kirana stores’ or farms, for no salary or wages. Their inclusion
within the ranks of the employed is frankly an artificial suppression of the
unemployment scores. Many analysts have in the past called out this figure for
what it really is – disguised unemployment – yet the statistics continue to be
compiled in the same way. Over the ten year period from 2004-05 to 2015-16,
this population has fallen drastically to 62 million. Therefore, effective
joblessness, including both unpaid workers and the officially unemployed, is down
from 118 million to 80 million. This from any benchmark should be construed as
a positive development and quite the opposite of what the superficial figures
tell us.
What further substantiates the unemployment
conundrum is an analysis of National Rural Employment Guarantee Scheme (NREGS[1]) figures. If unemployment were truly rising, NREGS numbers should
have responded commensurately. Instead, in the four year period between FY12
and FY16, NREGS enrolments declined from 75 million to 68 million. Even more remarkably,
only 10% of those enrolled actually completed the 100 days of work that the
scheme offers. One explanation for this might be that since NREGS is now on the
Aadhar platform, duplicate and ghost accounts may have been removed. Still,
this cannot explain the sheer magnitude of the shift. A more plausible
explanation would seem to be that real unemployment is actually falling, as
alluded to above; therefore, the number of people requiring NREGS support has also
dropped.
Ghosh & Ghosh
A recent study by two economists, Professor
Pulak Ghose of the Indian Institute of Management, Bangalore and Dr Soumya
Kanti Ghosh, Chief Economist of the State Bank of India, based on social
security databases concluded that in 2018, approximately 7 million formal
sector jobs have been created. In fact, the study received such publicity
having gone counter to the grain of previous thinking that Prime Minister
Narendra Modi himself referred to it during his recent engagements with
industry. Basically, the authors used data from the following sources: the Employees
Provident Fund Organisation (EPFO) which comprises of 55 million subscribers from
companies with over 20 employees; the Employees State Insurance corporation
with 12 million subscribers from companies with over 10 employees; the
Government Provident Fund consisting of 20 million subscribers; and finally,
the New Pension Scheme (NPS[2]) with 0.5 million subscribers which mostly replaces GPF and applies
to Government employees that entered service after January 2004.
Messrs Ghosh & Ghosh concluded that the
formal sector payroll stock as of March 2017 was 90.2 million. New job
creations were 5.8 million in 2017 and about 7 million in 2018, on a gross
basis (i.e. without netting off retirements). The methodology they adopted was
conservative and rigorous to say the least. The analysis, based on assumptions that
contained a strong downward bias, ensured that the study could not be accused
of even the slightest over-estimation. Some of these were as follows. First,
only those in the age band of 18-25 making continuous contributions were
counted as additions to the workforce, minimising duplication due to shifts in
employment from the unorganised to the organised sector. Moreover, only
employees making continuous contributions and whose information was complete in
every sense, without a single data point/field missing, were counted as being
employed. Approximately 42 million records that did not satisfy these
conditions were precluded. Third, since the EPFO covers companies with 20+
employees, incremental data from ESIC was taken only for those with under 20
employees with a view to avoiding duplication in job creation. Finally, approximately
30 million formal sector workers were excluded from the study because they are
not covered by social security databases. These include professionals such as
chartered accountants, lawyers, doctors, architects and other consultants;
police forces; teachers and school staff. It would be logical to assume that
these numbers would also be rising and should add to both the national stock of
jobs as well as incremental employment.
From a statistical perspective the
methodology adopted by the Ghosh study appears conservative from every
benchmark. Most importantly, it is based on payroll data and therefore free of
estimation errors. It would be logical to assume that the robust trend
demonstrating rising employment within the formal sector would lead to a
consequential increase amongst the ranks of the self employed or indeed those
in more informal engagements.
Mudra
A constant gripe by small businesses is
their inability to gain access to credit. Whilst this applies to small and
medium enterprises, its impact is even more profound in the context of cottage
industries and micro enterprises. In order to fill the funding gap the
Government launched Mudra, a scheme to ensure higher flows of credit to small
and micro enterprises. Under the programme, lending is carried out banks, micro-finance
institutions and non banking finance companies. An individual with a sensible
business plan may avail of a Mudra loan up to Rs 10 lacs. Whilst the average
loan size is around Rs 50,000, total disbursements since launch in April 2015,
have exceeded Rs 3.2 trillion with approximately 75 million borrowers. Of
these, 22.4 million were first timers. More importantly, 45% of disbursements have
been in favour of women. The intent of this exercise was presumably to generate
economic activity and churn amongst a segment of the business community and
self employed individuals who were previously unable to access formal credit
markets. Quite obviously, the scheme has been successful and should therefore
have a consequential impact on employment generation, none of which has so far
reflected in official statistics. It is hard to estimate what this is but some
analysts believe new job creation could be as high as 20-30 million.
In conclusion, it would be reasonable to
assume that contrary to popular perception, employment in India has actually
been rising and at a pace much quicker than in previous years. Empirical
evidence, not only through a deeper scrutiny of survey findings but equally
from the outcome of Mudra, a rise in consumption together with indirect taxes,
supports this view.
Be that as it may, India still needs to
create jobs perhaps at a rate faster than what it is currently doing. Communal
agitations, for instance those in Haryana, Gujarat and Maharashtra, are testimony
to this. Current estimates suggest that 6-8 million qualified individuals enter
the workforce every year. Having obtained some level of formal education they
are no longer satisfied with traditional forms of work such as farming and wage
labour. If their aspirations are to be fulfilled the industrial economy needs
to grow at rates exceeding 10% per annum. This clearly requires massive
investments in manufacturing and a lesser reliance on imports. But that is
clearly a different subject, worthy of another research-based analysis.
[1] NREGS is a
Government-funded
programme that guarantees 100 days of employment to one adult member of every rural
household.
[2] The New Pension
Scheme is based on defined contributions, replacing GPF, which works on defined
benefits.
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