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Do quotas in public sector employment for disadvantaged groups enhance their welfare?

  • Blog Post Date 10 September, 2021
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Nishith Prakash

University of Connecticut

Affirmative action policies remain controversial with many arguing that benefits come at the expense of those excluded, and accrue disproportionately to the elite in disadvantaged groups. Analysing nationally representative data, this article shows that 1 percentage point increase in employment quota for Scheduled Castes (SCs) raises the likelihood of obtaining a salaried job by 0.6 percentage points for rural, SC men – with significant positive effects on their welfare.

Since India achieved independence, the Indian constitution has provided safeguards to Scheduled Castes (SCs) and Scheduled Tribes (STs) to ensure proportionate representation in higher education, politics, and public employment, in the form of reserved quotas. However, affirmative action policies for disadvantaged groups remain controversial with many arguing that they impose a trade-off between equity and efficiency, that is, these policies support disadvantaged groups at the expense of groups that are excluded from such policies. Moreover, the aims of such policies are undermined if they disproportionately benefit the elite within disadvantaged groups. 

Do quotas actually support their beneficiaries?

Theoretically however, it is not obvious that quotas will succeed in supporting their beneficiaries. Consider employment quotas: quotas in public sector employment, when filled, will have a direct positive impact on the beneficiaries. Additionally, there may be indirect positive effects on those who do not secure reserved jobs – those eligible for reserved seats might stay in school longer to meet the eligibility requirements of these jobs, and this may make them more competitive in the private sector labour market (Khanna 2014). However, the opposite may also be true: if quotas reduce the level of competition that one faces in the labour market of the public sector, then beneficiaries may reduce their educational attainment (beyond eligibility requirements). This can reduce both the quality of the labour pool of minority groups and their level of employment. Finally, if a large enough share of persons from disadvantaged groups who wish to apply for reserved jobs, do not meet the minimum requirements of eligibility, these seats might remain unfilled. 

Our study: Data and methods

Quotas in public sector employment are state-specific in India, and are equal to the population shares of SC/STs as per the most recently tabulated population census. This policy rule generates a plausibly ‘exogenous’ within-state, cross-time variation in the employment quota1. Further, bureaucratic requirements result in lags between current and census populations on the one hand, and quota shares on the other. 

Using data from the four rounds of the National Sample Survey (NSS) between 1983-84 and 1999-2000, I exploit the within-state variations in employment quota to estimate: (i) Whether job quotas for SC/STs increase their likelihood of securing a salaried job2, (ii) Whether these benefits are captured disproportionately by the educated elite among SC/STs, and (iii) Whether the impact on their employment also resulted in gains in welfare as measured by monthly per capita income for SC/ST communities (Prakash 2020).

Quotas, jobs, and welfare

Our main findings suggest that the employment quotas only benefitted SCs, and not STs. In particular, I find that a 1 percentage point increase in the employment quota for SCs increases the likelihood of obtaining a salaried job by 0.6 percentage points for SC men residing in rural areas. Moreover, when estimated by state characteristics, I find the impact of the employment quota to be more pronounced in the less economically developed BIMAROU (Bihar, Madhya Pradesh, Rajasthan, Odisha, and Uttar Pradesh) states, for women as well as men living in rural and urban areas. In contrast, the results for the effect of the policy on STs is unclear 

Importantly, I do not find that the benefits of the reservation policy are captured by the educational elite, contrary to the popular notion. The SC quotas, in fact, benefitted the least-educated SC workers – those with less than secondary school level of education. For this group a 1 percentage increase in the employment quota increased the likelihood of securing a salaried job by 0.7 percentage points. 

Consistent with the results on employment, I find that employment quotas have a positive and significant effect on monthly per capita consumption expenditure – a measure of welfare – particularly for SCs with less than secondary school education and residing in rural areas. Employment quotas only increase consumption for the poorest households3, among highly educated SC persons in rural areas, further dispelling the notion of elite capture. 

Policy implications and future research agenda

In India, affirmative action in the form of quotas have been the primary tool to address gaps in a number of socioeconomic indicators that exist between SC/ST communities and the rest of the population. I find that the SC employment quotas improved SC employment prospects and welfare, especially for men in rural areas where there are more public sector jobs – especially clerical and menial jobs with lower educational requirements. This, along with the lack of evidence on elite capture, suggests that the policy is working as intended. 

However, several other policy-relevant questions need to be considered. It is important to understand the impact of employment quotas on the quality of job matching and productivity. For instance, research shows that banning the use of racial preferences in the admissions process at public colleges in California improved graduation rates, in part because the ban led to a more efficient sorting of minority students (Arcidiacono et al. 2014). There are however other contexts where there is no evidence of inefficient matching. For instance, research on the Indian Railways shows that reserved jobs had no impact on productivity (Deshpande and Weisskopf 2015).  

Going forward, an important question in this regard is the long-run efficacy of quotas to meaningfully bridge outcome gaps between disadvantaged groups and the rest of the population, so that these communities will no longer require such benefits in the future. Although I find evidence that the policy is reaching its intended beneficiaries, it is more likely to achieve its aims if the process is more dynamic, and in line with evolving socioeconomic realities. Moreover, if these quotas are complemented with training programmes, any skill gaps that exist between the targetted population and the eligibility criteria for reserved jobs might also be reduced in the short run. In the long run, they may make the quota policy less relevant. 

This article was written with the assistance of Nikhilesh Prakash. 

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  1. Note that the variation is not based on all fluctuations in minority population shares, since this may affect minority outcomes though channels in addition to the employment quota. Instead, the empirical strategy to establish a causal impact between quotas and employment, takes advantage of the fact that there is a time lag between the setting of the quota (which happens every 10 years), and the population share in any given year (which changes yearly).
  2. The NSS data do not have a measure for public sector jobs specifically, and hence data on salaried jobs are used.
  3. Those within 10th percentile of monthly per capita consumption expenditure.

Further Reading

  • Arcidiacono, Peter, Esteban Aucejo, Patrick Coate and V Joseph Hotz (2014), “Affirmative Action and University Fit: Evidence from Proposition 209", IZA Journal of Labor Economics, 3(7).
  • Deshpande, A and TE Weisskopf (2015), ‘Does affirmative action reduce productivity? The case of Indian Railways’, Ideas for India, 21 January.
  • Khanna, G (2014), ‘Quotas and schooling decisions’, Ideas for India, 3 April.
  • Prakash, Nishith (2020), “The impact of employment quotas on the economic lives of disadvantaged minorities in India”, Journal of Economic Behavior and Organization, 180: 494-509. 
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