This study has been prepared within the UNU-WIDER project on 'The politics of group-based inequality-measurement, implications, and possibilities for change', which part of a larger research project on 'Disadvantaged groups and social mobility'.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This study has been prepared within the UNU-WIDER project on 'The politics of group-based inequality-measurement, implications, and possibilities for change', which part of a larger research project on 'Disadvantaged groups and social mobility'. Terms of use: Documents in Copyright © UNU-WIDER 2016Information and requests: publications@wider.unu.edu ISSN 1798-7237 ISBN 978-92-9256-149-9 Typescript prepared by Lesley Ellen.The United Nations University World Institute for Development Economics Research provides economic analysis and policy advice with the aim of promoting sustainable and equitable development. The Institute began operations in 1985 in Helsinki, Finland, as the first research and training centre of the United Nations University. Today it is a unique blend of think tank, research institute, and UN agency-providing a range of services from policy advice to governments as well as freely available original research.The Institute is funded through income from an endowment fund with additional contributions to its work programme from Denmark, Finland, Sweden, and the United Kingdom. Katajanokanlaituri 6 B, 00160 Helsinki, FinlandThe views expressed in this paper are those of the author(s), and do not necessarily reflect the views of the Institute or the United Nations University, nor the programme/project donors.Abstract: Using data from various rounds of the nationally representative NSSO survey between 1988 and 2012, we first construct national, state, and district-level figures for overall, within and between consumption inequality. We find an increase in inequality in India but only since 2004. We also document an increase in between group (or horizontal) inequality over the entire period. We then investigate the impact of ethnic fragmentation and public good provision on inequality. We hypothesize that by lowering the provision of public goods (specifically schools and health facilities), fragmentation will impact the incomes of the poorer sections more than those of the rich and thus increase inequality. Empirical results support this hypothesis. We find that the increase in overall inequality is lower in less fragmented districts, but there is no strong relationship between horizontal inequality and fragmentation or public good provision. This is because public good provision impacts within group inequality but not between group inequality.

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To review the performance of schools in India and to monitor policies targeted towards them, information on all the registered schools started to be maintained, from 1995, under the software named DISE. Since we rely on the DISE data for our empirical analysis, in this section, we address some of the concerns related with this dataset to make sure we are not picking up any bias in the data. DISE data has been envisioned to be the census of all the existing registered schools and it relies on self reported information on a range of school characteristics like the medium of instruction, year of establishment, whether the school is approachable by all weather roads, funds granted under government schemes, information on instruction hours, teachers, enrollment, school results among others. In other words, it is a detailed dataset on school particulars which is compiled at the district level. However, one of the concerns with the DISE data that has started getting recognition is regarding the coverage of schools in the DISE data. It is believed that DISE may not fully cover unrecognised schools. Additionally, schools which report information in the DISE data might be systematically different from the ones which do not report information.We perform two tests to address this concern. One, we reestimate equation 4 (main test of the paper) with the census 2011 data using information on number of schools reported in village and town directories. Note that 2011 census categorised schools into public (which includes state/central/local government schools) and private (which includes private unaided and aided) and does not provide finer classification of schools. Results reported in Table A.1 corroborate the findings observed with DISE data. Private schools are (weakly) negatively impacted by fragmentation whereas there is no impact on public schools. Thus the results of the paper do not seem to be a result of specific schools covered by DISE. Second, we check if the sample of schools covered under the DISE data is representative and there is no correlation of the under reporting of data with the fractionalisation index. We do that by constructing the difference between the number of schools covered by the census and the DISE. Positive difference would imply that census covers more schools than DISE and that divergence in reporting of schools between census and DISE is more. We regress this divergence on the fractionalisation index to check the correlation between

In this article, we document some empirical facts about vocational training in India. First, we show that the education levels and vocational training of the Indian labour force are low and have not changed between 2004-2005 and 2011-2012. Then, we show that in wage employment, regular wage and salary earners and casual labour, the returns to skilling are low while the returns to general education are significant, even within the same occupation and industry category. Using the enterprise surveys from the NSS, we also document that self-employment, which is the outside option for most unskilled, semiskilled and even skilled people, is very unproductive. We, thus, argue that the Indian labour market is stuck in an equilibrium where both the number of persons getting skilled and the returns to skilling are low.