ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846
-A A +A

Employment Scenario and the Reservation Policy

The author wishes to thank the anonymous referee for helpful suggestions.
Paaritosh Nath (paaritoshnath@gmail.com) is with the Aman Biradri Trust, New Delhi.

In its haste to placate the growing resentment amongst the unemployed youth, the Indian government has come up with an ill-informed and loose definition of who constitutes the “economically weak.” Some of the major arguments that have been levied against the 124th amendment to the Constitution are empirically substantiated in the light of the current state of employment generation, particularly in the public sector, as well as the performance of the state with respect to fulfilling the existing reservation policy.

It would be an understatement to say that the decision by the Narendra Modi govern­ment to introduce the 124th amendment to the Constitution has taken people by surprise. The proposed bill (now law) that sought to amend Articles 15 and 16 of the Constitution to provide for the advancement of “economically weaker sections” (EWS) was passed almost unanimously in both houses of Parliament without much debate. Introduced in the run-up to the general ­assembly elections of 2019, this “pro-poor” amendment provides for 10% reservation in jobs and educational institutions to economically backward sections in the general category (International Business Times 2019).

The element of surprise was owing to the fact that prior to the cabinet note, reservation for upper castes was not a major issue of debate. In 2010, the S R Sinho Commission had submitted a report to the government recommending the carving out of a cate­gory for those classified as Economically Backward Class (EBC). However, no further action was taken in that direction. While there have been caste-based agitations by different interest groups during the tenure of this government, much of these agitators demanded their inclusion within the groups that qualified for reservation in the existing 49.5% structure (Dangwal 2017). No independent commission or enquiry was set up by the Modi government that would shed more light on who exactly comprised these “economic­ally weak” persons and what the economic and social conditions that informed the lives of such persons were like.1 Since the bill was first announced, there have been varied reactions to this legislation. Some commentators have absolutely decried the move citing it “as the beginning of the end for social justice in the form of caste-based reservation” (Shinde 2019). ­Others have welcomed it, claiming it is a good initiative for the poor, the very first, in fact, that includes Muslims under its umbrella (Bhalla 2019). Some have gone to argue that if it were to be given at all, it “would have made more sense to have limited 10 per cent EWS reservation to those with farming or rural backgrounds” (Damodaran 2019).

Alongside the first set of reactions that criticise the amendment for going against the spirit of social justice, there have been three main grounds for objection. First is that this is an attempt by the government to mask its failure in job creation.2 Second, the government should first look at fulfilling the constitutionally mandated reservation policy of those hailing from deprived backgrounds. Third, that the criterion selected for identifying the poor is flawed.

However, none of the opposing voices have been able to substantiate their claims with solid numbers. This has mainly been due to the lack of any reliable data on employment that currently exists in the public domain. As Chandrasekhar (2019) notes, official employment figures for recent dates are proving to be difficult to come by, given the suspension of a number of statistical surveys relied on in the past to gauge trends in employment generation. The quinquennial Employment–Unemployment Surveys (euss) carried out by the National Sample Survey Office (NSSO), which up until 2011–12 were the most preferred source for estimating employment trends and patterns, were suspended on the grounds that a data set with a higher frequency interval was required for estimating employment figures in the economy.3 In its place, the Labour Bureau’s annual household surveys and the quarterly Quick Employment Surveys (QES) were used to estimate employment figures roughly covering the period from 2012 to 2017.

According to Abraham (2017), the picture that emerged from these data sources was that of an absolute decline of employment in India during this period, with much of it probably in the unorganised sector, while the organised sector witnessed a sharp decline in the growth of employment. The stagnation in employment was widespread, affecting ­almost all the sectors of the economy. Unfortunately, both these surveys have not come out with any new estimates since 2015–16 and October 2017, respectively.  

The only source of employment data that is available is the Consumer Pyramids Household Survey (CPHS) undertaken by the Centre for Monitoring Indian Economy (CMIE). As per the CMIE, around 1 crore people had lost their jobs in 2018 with the total employment falling to 39.69 crore in December 2018 (Financial Express 2019). Although the CMIE data set covers more households than both the quinquennial NSSO and Labour Bureau surveys, it is strictly not comparable to these data sets and thus, is of limited use when trying to establish long-term trends.4 Furthermore, with reference to the quota debate, information is needed for the employment generated in the public sector (that too on a caste-wise segregation basis), which is even more difficult to capture now with the suspension of the NSSO rounds. Given the above limit­ations and for the purpose of highlighting employment data, keeping the quota debate in mind, the available information from the annual reports brought out by different ministries such as the Ministry of Railways, India Post, Ministry of Personnel, Public Grievances and Pensions as well as various issues of the Public ­Enterprise Surveys is used. The Labour Bureau’s Fifth Annual EUs data carries information on the previous year for which comparable employment data is available for 2015–16, is also used.5 Even though the most recent trends are not available, a snapshot of the employment picture in 2015–16 would be useful to put into perspective some of the finer points surrounding the 10% reservation debate.

Where Are the Jobs?

Confirming Abraham’s (2017) assessment of the economy as a whole, worker participation rates (WPRs) of both males and females continued their downward slide since 2004–05, falling even further in 2015–16. Urban females in 2015–16 had the lowest WPR at 14.8% while the corresponding rate for their rural counterparts was 30.2% (Figure 1). It is to be noted that these figures were obtained on the basis of the “usual status” definition of employment which also takes into account the rather lenient subsidiary status understanding which considers as employed even those who were engaged in an economic activity for just a month in the past 12 months.

Consequently, during this period, we note a considerable rise in the unemployment rates across different social categories (Figure 2). For example, 34 out of 1,000 Scheduled Caste (SC) persons in 2015–16 were available for work but not employed as against 21 SCs in 2011–12. The corresponding unemployment rates for Other Backward Classes (OBCs), Scheduled Tribes (STs) and “Others” in 2015–16 was 2.4%, 3.9% and 4%, respectively. On the basis of the principal status definition (only those who were employed for six months or more being considered as employed), which is a far more stricter criterion of measuring unemployment, note that the unemployment rates of the SCs, STs, OBCs and “Others” become 4.4%, 5%, 5.2% and 5%, respectively. It is to be noted that the difference in the unemployment rates between “Others” and STs comes down to 0 when the principal status criterion is taken (as against 1.6%) implying that a far greater share of ST workers were employed in subsidiary forms of employment (usually of an extremely poor quality) when compared to the “Others” category counterparts.

What is even more worrying is that the unemployment rate amongst the youth (15–29 years) was higher in 2015–16 than it has been in the last 15 years. While only 54 youths out of 1,000 were unemployed in 1999–2000, 103 youths now found themselves to be unemployed in 2015–16. Unemployment rates were furthermore highest for the most educated youth with the rates for those educated up to “higher secondary” being 12.5% and for those having an education status of “grad­ua­tion and above” being a staggering 28.2% (Figure 3, p 57). It must also be noted that the unemployment rate of the educated youth are higher now than they have been since the turn of the century.

From the above analysis, the story of job creation in the last couple of years has been a dismal one with WPRs falling and unemployment rates rising across social categories. The share of unemployed youth, and more specifically, the educated unemployed youth is higher now than it has been in the recent past. There are not enough jobs being generated in the economy which would partly explain the recent agitations by the Jats and Maratha youth for being included in caste-based reservations for public ­sector jobs.

Public Sector Employment

As data, specifically for this sector, is difficult to obtain, reports of some of the major employers (in the public sector)are assessed. However, the available information from official reports does not present a very happy picture.

According to the Central Public Sector Enterprises (CPSEs), for example, the number of non-contractual employees has fallen from 16.1 lakh in 2006–07 to 11.3 lakh in 2016–17, which is a fall of 4.8 lakh workers during a period of 10 years (Figure 4, p 57). A 10% reservation in 2006–07 would have amounted to 1.6 lakh workers, that is, three times the proposed 10% have already been lost in the past 10 years due to cutbacks in government employment.

 

Indian Railways: One of the largest public sector employers also saw an absolute decline in employment during this period with the total number of employed falling by around 90,000 persons between 2007 and 2017. From Table 1, note that while there was an absolute increase in the number of Group A and C employees, a massive cutback took place with respect to Group D workers, which led to an overall fall in employment figures.

India Post: Data for those employed by India Post could be accessed only from 2012–13 onwards. Between 2012–13 and 2016–17, total number of employees fell for all the different worker categories with the number of gazette officers falling at a compound annual growth rate (CAGR) of 5.3% while the number of non-gazetted staff positions fell at a CAGR of -2.3%. In total, there was an absolute decline of more than 18,000 posts during this five-year period (Table 2).

State Bank of India, other nationa­lised banks and regional rural banks: The same five-year period saw a fall of around 60,000 persons, from 9.7 lakh in 2012–13 to 9.1 lakh in the State Bank of India (SBI), other nationalised banks and regi­onal rural banks (Figure 5). Much of this fall took place amongst the clerical staff that saw lay-offs of more than 90,000 persons during this period. Officers, on the other hand, have risen in number during the same time period by about 55,000 persons.

 

Public administration: Data on those who are engaged in “Public Administration” (NIC: 841) in total was obtained from the fifth Labour Bureau—EUS and the NSSO’s 68th Employment–Unemployment Round (Figure 6). It is to be noted that this could also include those engaged in various levels of administrative duties in any of the sectors. From the same, total employment fell by around 15 lakh persons during the five-year time period.

The fact of the matter is that in the last couple of years, employment has shrunk at an alarmingly rapid pace in this sector. Some of the major employers in this segment have in fact rescinded a far greater number of jobs than that which would have been covered under the 10% quota. The new reservations are thus going to be implemented in a scenario of ever decre­asing pool of jobs. As a result of this, fewer job opportunities are going to be available to all social categories, including the “poor upper castes” irrespective of whether or not they are entitled to reservation. A 10% reservation of an ever decreasing total would effectively leave the supposedly aggri­eved sections, on the whole, with a lower number of jobs than before. Facing an acute crisis of employment creation, it appears that the government has tried to placate the anger of the growing sections of the unemployed by appealing to a commonly held (yet rarely substantiated) notion amongst the upper-caste sections that reservations and not the growth tra­jectory adopted by the state is the prim­ary reason for their state of joblessness.

Employees in the Public Sector

According to a recent report published by a leading English news daily, SCs, STs and, especially OBCs are found to be under-represented in the higher echelons of the government—Groups A and B—and most of its institutions (Indian Express 2019). Detailing information received from government agencies via the use of the right to information (RTI) act the report goes on to describe the current state of reservations in different segments of the public sector. In central universities, RTI data shows that 95.2% of professors, 92.9% associate professors and 66.27% assistant professors are from the “Open” cate­gory.6 The share of “Open” category persons (in the total number of Groups A and B officers) in the Niti Aayog, Union Public Service Commission (UPSC), Com­ptroller and Auditor General of India (CAG) office and Cabinet Secretariat was found to be 73.84%, 64.76%, 66.79% and 80.25%, respectively. The OBC reservations seem to be the worst hit here with total OBC officers falling way short of the mandated 27%.

Data from the CPSE reports presents a similar story (Figure 7). While “Others” formed 53% of the total employees in these public sector enterprises in 2016–17, OBCs formed only 19% of the same. The highest level of employees, that is, the managers/executives saw the share of the non-reserved personnel shoot up to 63%, with both ST (6%) and OBC (16%) reservation falling short of the constitutional mandate, while SCs just about managing the same. With respect to Central Government Services (CGS), the total OBC personnel fell short of the 27% constitutional mandate (Figure 8). Confirming the trends, the majority of Class A (68%) and Class B (62%) officers belonged to the unreserved sections. It was only in the category of ­“safai karamcharis” that a much higher share (compared to their constitutional mandate) of SCs (45%) and a much smaller share of non-reserved category persons (33%) can be observed.

The situation of existing caste-wise representation may also be getting worse in certain major segments of India’s public sector. For example, in Indian Railways, between 2007 and 2017, the share of Group A officers who belong to the SC category has actually fallen from 15.12% to 13.48%. The situation is worse off in India Post where between 2012 and 2017, the overall share of SC employees has fallen from 17.38% to 16.84%. Similarly, comparing data obtained from the 68th NSSO Employment–Unemployment round and the fifth EUS in the ind­ustrial category “Public Administration” (NIC 841), the share of total SCs employed have fallen from 23.3% to 20.1%.7

It becomes not only clear that the public sector has been facing massive cutbacks in total job creation, but also that there exists severe lacunae with regard to implementing the prevailing reservation policy in the public sector. Open category personnel still constitute a majo­rity in the public sector workforce, particularly when it comes to Groups A and B (read best quality) jobs. In some the Indian Railways and India Post, the share of SC personnel has been falling with time. The OBC reservation woefully falls short of the prescribed levels across the key public sector enterprises.

Various caste-based interest groups and political parties have been vociferous of the major gaps in implementing the existing reservation policy, which has been raised time and again, and this should have ideally formed a crucial com­ponent of any debate revolving aro­und the “pro-poor” agenda of the state and its policies of affirmative action. What exists, however, is an incomplete reservation programme for the histori­cally disadvantaged social groups and a hasty, ill-informed amendment based on an upper-caste sentiment that seems to be exaggerated and lacking in terms of concrete empirical evidence.

‘Creamy Layer’

In order to identify the poor amongst the upper caste sections, a proposed cap of `8 lakh family income cap and a five acre land criterion was speculated to be adopted (News18 2019). However, the Constitutional (124th Amendment) Act, 2019 did not specify any criteria and explains that the phrase “economically weaker sections” as in the act may be notified by the state from time to time on the basis of family income and other indicators of economic disadvantage.8 This has prompted some to speculate that the cap may also be extended beyond the `8 lakh criterion (Nair 2019). All discussions on the implementation of the act, however, continue to revolve around this income figure which has most likely been taken from the current ceiling of `8 lakh family income that defines the creamy layer among the OBCs (Economic Times 2017).

However, this was met with vociferous criticism, the reasons for which are not too far to see. For one, to base an income criterion on the creamy layer baseline of another, marginalised section, tends to delegitimise the entire notion of “historical and social disadvantage.” The fear is that this move, in turn, would set a precedence that would change the manner in which the existing reservation policy is understood in the country. So while the amendment currently does not touch the existing reservation policy, it does tend to potentially disrupt the same in the long run. For an excellent exposition on the same, see Chatterjee’s (2019) take on this issue.

In bringing forth the amendment in haste in the current session of Parliament, the Government of India, unlike in the past has not constituted an independent committee or expert group that would have looked into the rather complicated question of who constitutes the poorest of the poor amongst the historically advantaged groups (rather than going for a creamy layer), let alone any discussion on the modalities surrounding the type of assistance that these people could have been provided for by the state. A vague and loose definition of what constitutes the EWS would have led to yardsticks that are ludicrous to say the least.

As per the last Labour Bureau—EUS in 2015–16, 96.3% of all families coming under the “Others” category earned less than `6 lakh per annum, that is, more than 7.7 crore families out of the 8.03 crore “Other” households would have been entitled for a quota which had a ceiling of `6 lakh per annum. A `8 lakh income criterion would include a higher share.9 These are ridiculously high figures which make a mockery of both the pro-poor argument put forth by the government as well as the spirit of social justice that informs the current reservation principle. If the new quota system was to follow the `8 lakh per annum definition, virtually most families falling under the unreserved status would be eligible for reservation, irrespective of their cultural, social, economic and educational backwardness (or otherwise).

This is not to argue that the state does not need to look after the interests of those outside the 49.5% reservation system. After all, as noted from Figure 10, 16.1% of all “other” households earn only up to `60,000 a year, that is, a sum of only `165 a day for an average family size of roughly 5.5 persons. In fact, 22% of all households that belong to the lowest earning group as per this data set belong to the non-reserved categories. The fact of the matter is that the growth trajectory followed by the Indian state has been such that it has left a fair share of persons behind; even those ­belonging to the historically well-off segments. As per the latest Global Inequality report produced by Oxfam, India’s top 10% holds 77.4% of the total national wealth (ndtv 2019). Anand and Thampi (2016) have shown how there has been a greater concentration of wealth with the top 10%, particularly after 2012. This, compounded with loss in job creation and crisis in the agricultural sector, has led to this growing discontent amongst sections of even the upper castes (Sood 2018). The government, in order to placate this resentment has brought forth this new amendment, in the process incorrectly positing reservations as an instrument for poverty alleviation rather than social justice. The resentment exhibited by certain sections might be founded on valid grievances but their own prognosis is ­severely misplaced and the state’s solution, that is, a quota of 10% in an ever decreasing pool of jobs applicable to more than 97% of all non-reserved families seems to make little or no sense. Universalisation of the public distribution system, implementation of the Swaminathan Committee recommendations, a comprehensive study identifying who needs greater state assistance and most importantly a greater impetus towards employment generation appear to be obvious starting points. ­Ultimately, to bring these sections back into the “mainstream,” the mainstream itself needs to be re-imagined.

Notes

1      Interestingly, the S R Sinho Commission had identified 13 parameters to define who would fall under this category—a recommendation not taken up by this government. See Sharma (2019).

2      It is interesting that this issue managed to set aside another highly contested debate that was going on in policy circles—on the quantum and nature of job creation that had taken place in the economy during the current regime. The two debates, I would argue here, feed into each other. In fact, as soon as the government came out with plans of a constitutional amendment, various leaders of the opposition fired back, stating that through the above the government was merely trying to divert attention away from the fact that it has failed to deliver in terms of its promise of employment growth. The latter, coupled with the massive agrarian distress in the past couple of years, it was argued, had forced the government to move for this amendment.

3      See the “Report on the Task Force on Improving Employment Data,” 2017 (NITI Aayog 2017).

4      A difference between the CPHS and the NSSO surveys is the reference period of the employment status of a respondent. While the NSSO tries to capture the status for an entire year and for a week, the CPHS captures the status as on the day of the survey. This could be as one of four factors: employed; unemployed willing to work and actively looking for a job; unemployed willing to work but not actively looking for a job, and unemployed but neither willing nor looking for a job. See Vyas (2019).

5      With that of the previous NSSO Employment– Unemployment rounds. In this study we have used data obtained from the 68th, 61st and 55th NSSO EUSs.

6      Reservations are applicable at the level of assistant professors. This may also include SCs, STs and OBCs who have not availed the benefits of reservation.

7      These figures would also include those who are employed as casual and certain categories of contractual workers for whom reservation might not be applicable.

8      It was later clarified by Social Justice and Empowerment Minister Thaawarchand Gehlot that no such cap was final.

9      There is the added confusion as to how this reservation will be implemented across different states having different criterion, income or ­otherwise.

References

Abraham, V (2017): “Stagnant Employment Growth: Last Three Years May Have Been the Worst,” Economic & Political Weekly, Vol 52, No 38, pp 13–17.

Anand, I and A Thampi (2016): “Recent Trends in Wealth Inequality in India,” Economic & Political Weekly, Vol 5, No 50, pp 59–67.

Bhalla, S S (2019): “10% for EWS Is a Good Initiative for Poor—And the Best Policy for Muslims,” ­Indian Express, 12 January, https://indianexpress.com/article/opinion/columns/quota-bill-10-per-cent-bjp-reservation-economically-weaker-sections-5534313/.

Chandrasekhar, C P (2019): “The Failed Promise of Employment,” 17 January, https://www.networkideas.org/news-analysis/2019/01/the-failed-promise-of-employment/.

Chatterjee, P (2019): “The 10% Reservation Is a Cynical Fraud on the Constitution,” Wire, 18 January, https://thewire.in/government/the-10-reservation-is-a-cynical-fraud-on-the-constitution.

Damodaran, H (2019): “A Quota for Farmers,” ­Indian Express, 14 January, https://indianexpress.com/article/opinion/columns/a-quota-for -farmers-job-education-reservation-ews-5536650/.

Dangwal, Sandhya (2017): “Jat Agitation: Stir Demanding OBC Category for Community to Resume in 19 Districts of Haryana Today,” 29 January, https://www.india.com/news/india/jat-agitation-stir-demanding-obc-category-for-co­mmunity-to-resume-in-19-districts-of-harya­na-today-1791951/.

Economic Times (2017): “Creamy Layer Income Cap for OBCs Raised to `8 Lakh per Annum,” 13 September, https://economictimes.indiatimes.com/news/politics-and-nation/creamy-layer-income-cap-for-obcs-raised-to-rs-8-lakh-per-annum/articleshow/60497593.cms.

Financial Express (2019): “1 Crore Jobs Lost in 2018: Unemployment Rate Hits 27-month High in
December, Says CMIE; Key Things to Know,” https://www.financialexpress.com/econ­om­y/­1­-cro­re-jobs-lost-in-2018-unemployment-rate-hi­ts-27-month-high-in-december-says-cmie-key-thi­ngs-to-know/1435748/, viewed on 21 January 2019.

International Business Times (2019): “Modi Government’s Pro-poor Move: 10% Quota Approved for Economically Backward Upper Caste,” https://www.ibtimes.co.in/modi-govts-pro-poor-move-10-quota-approved-economically-backward-upper-caste-789514, viewed on 9 January 2019.

Indian Express (2019): “Reservation Candidates Are Under-represented in Govt’s Upper Rungs,” Thursday, 9 May, viewed on 21st January 2018, https://indianexpress.com/article/educa
tion/reservation-candidates-are-under-represented-in-govts-upper-rungs-5540310/

Nair, Shalini (2019): 10% Quota for EWS: States Can Go Past `8 Lakh Annual Income Criteria,” Indian Express, 17 January, https://indianexpress.com/article/india/10-percent-quota-for-ews-states-can-go-past-rs-8-lakh-annual-income-criteria-5542072/.

ndtv (2019): “Davos 2019: Richest 1% Indians Hold 51% Wealth: Oxfam Boss Explains Why,” 21 January, YouTube video, https://www.youtube.com/watch? v=7SXktQTX88g.

Niti Aayog (2017): Report of the Task Force on Improving Employment Data (Draft Version), Government of India.

News18 (2019): “In Surprise Move before Polls, Cabinet Approves 10% Reservation for Economically Weaker Upper Castes,” 8 January, https://www.news18.com/news/india/months-before-polls-modi-cabinet-approves-10-reservation-for-economically-backward-upper-castes-1994275.html.

Sharma, Nidhi (2019): “Reservation Needs to Be on Socio-economic Criteria: Major General (Retd) S R Sinho,” 11 January, https://economictimes.indiatimes.com/news/politics-and-nation/reservation-needs-to-be-on-socio-economic-criteria-major-general-retd-sr-sinho/articleshow/67480343.cms.

Shinde, R (2019): “Three Reasons the 10% Quota Bill Is More Than an Election Gimmick,” 11 January, https://thewire.in/caste/upper-caste-reservation-more-than-election-gimmick.

Sood, Jyotika (2018): “India’s Deepening Farm Crisis: 76% Farmers Want to Give up Farming, Shows Study,” https://www.downtoearth.org.in/news/indias-deepening-farm-crisis-76-farmers-want-to-give-up-farming-shows-study-43728.

Vyas, Mahesh (2019): “Surveying India’s Unemployment Numbers,” Hindu, 9 February, https://www.thehindu.com/opinion/lead/surveying-indias-unemployment-numbers/article26218615.ece.

Updated On : 13th May, 2019

Comments

(-) Hide

EPW looks forward to your comments. Please note that comments are moderated as per our comments policy. They may take some time to appear. A comment, if suitable, may be selected for publication in the Letters pages of EPW.

Back to Top