The aim of this article is to estimate the marginal rates of return to various levels of education in India, across the entire wage distribution. For this purpose, unit level data from the 68th round of the National Sample Survey Organisation (India) for the year 2011-2012 have been used, and the technique of quantile regression has been applied. Average estimates were ignored, and the heterogeneity in rates of return was captured across the following disaggregations: (a) all India, public and private sectors, (b) gender, and caste groups (scheduled tribes [STs], scheduled castes [SCs], other backward classes, and others). The findings showcase that the rates of return increased with consecutive higher levels of education. However, this impact varies across the disaggregations examined. The returns are the least for STs and SCs as compared with others (the unreserved category), with the differences in the rates of return being maximum in the private sector. Additionally, women experience a higher rate of return than men. These findings have important policy implications with respect to strengthening the public funding of higher education and encouraging participation from the marginalised segments (STs, SCs), which is otherwise dismal. ---This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

The central idea of the present study is to re-establish the importance of human capital variables (education and experience) at all India level and also at the disaggregated level of gender (male/female) across regular and casual workers using NSS 68th round. This is the latest employment-unemployment unit-level records pertaining to year 2011-2012. The paper examines the impact of human capital variables, household factors, job-related factors, individual characteristics and locational factors on earnings of an individual. Separate augmented Mincerian equations have been used for regular and casual workers, further subdivided at the level of male and female. The method of quantile regression has been used to estimate the augmented Mincerian equation at the abovementioned disaggregated levels. The present study showcases that human capital variables, household factors, job-related factors, individual characteristics and locational factors impact regular and casual workers differently, the variation being further pronounced when disaggregated at the level of gender. Interestingly, human capital variables impact the earnings of regular workers (male and female) and casual (male and female) workers positively. Factoring the growing informalisation (not being entitled to social security benefits) in the regular form of employment, the study showcases a wide disparity within the regular workers. Thus, an attempt has been made to unfold primarily the interplay between education and earnings at various disaggregated levels.

This article is an attempt to build an empirical ground for supporting the increased role of public funding in higher education. The rationale for the same becomes pertinent in the current scenario when ‘public good’ nature of higher education is rapidly eroding. Various measures like the proportion of GDP/GSDP spent and the trend of per capita public expenditure on higher education have been calculated from 1990–1991 to 2009–2010 using 2004–2005 constant price.1 The calculations are done at an all India level and also across the 15 major states.2 The study also measures the distribution of subsidy in higher education to assess if it is progressive/regressive among five quintile groups,3 across 15 major states, and at an all India level, using National Sample Survey 64th round (2007–2008) unit level records. The tool of benefit incidence analysis has been used to arrive at the results for the same. Suits index and concentration curves have been used to supplement the results. Although the results at an all India level show a pro-rich distribution of subsidy at the higher level of education, a state-wise analysis showcases varied results, on several occasions breaking the India level norm which warrants appropriate reflections on policy implications.

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