Identity enumeration and statistical systems

By Sukhadeo Thorat

The system of statistical data collection in India needs reform in order to meet actual requirements.
The use of individual-focussed policies for the economic empowerment of the poor, along with group-specific policies for discriminated groups such as the Scheduled Castes (SCs), Scheduled Tribes (STs), Other Backward Classes (OBCs), women and Muslims to reduce inter-personal and inter-group disparities in human development, has been the hallmark of India's pro-poor policies. However, demands for group-specific policies have been on the rise in recent times. These include demands for reservation by OBCs, SCs and STs in the private sector, and for women in Parliament. There have also been similar demands by Dalit Muslims and Christians, de-notified and nomadic tribes and the sub-castes among the SCs.

Given that only a limited amount of data is available on these groups from the Census and National Sample Survey (NSS) exercises, the government has sought to rely on committees, commissions and sponsored studies to deal with new demands for data and information. For instance, in the context of the demand for reservation in the private sector, the government sought information through sponsored studies. With respect to Muslims, the Sachar Committee used Census and NSS data on a selective basis. A National Commission was set up to put together information on de-notified, nomadic and semi-nomadic tribes. For sub-castes within the SCs, the Usha Mehra Committee was set up. The National Commission on Religious and Linguistic Minorities dealt with the issue of Dalit Muslims and Christians. These are some examples of the government dealing with data requirements with respect to various groups.

The instruments of committees and commissions, however, have their limitations. They cannot cover all the relevant aspects, and theirs being one-time exercises they have limitations in studying any changes. Therefore, notwithstanding the commendable work done by some committees and commissions, due to insufficient data the understanding of the problems with regard to social groups is inadequate, and this constrains the government's capacity to develop evidence-based policies. Comprehensive data systems on the relevant aspects of various groups enable the government to develop focussed policies. Therefore, the statistical system that currently comprises the population Census, the NSS, the National Family Health Survey (NFHS), the Economic Census and others needs reform, so that data are gathered on all aspects at regular intervals on the relevant castes, tribes, de-notified and semi-and nomadic tribes, religious minorities, women, and castes within the religious groups. This is essential to gauge the extent of inter-group inequities in terms of asset ownership, employment in the public sector and the private sector, education, housing, health, and other aspects.

Group-wise data on the relevant indicators help in two ways. First and foremost, disaggregated data provide insights into the problems of each group and help overcome group-specific constraints through appropriate policies. It helps governments to deal with unjustified demands for reservation, if the problems that the group face are of a general nature and do not arise from discrimination. Secondly it helps trace the impact of policies and enable decisions with regard to their continuation or discontinuation. A system of disaggregated data also enables governments to make decisions that are evidence-based, transparent, and open, and strengthen the government's capacity to deal with politically motivated demands.

Two concerns have been expressed about the generation of data that are disaggregated in terms of caste, religion and similar categories. The first is that caste-tribe-religion wise data may cause them to be used for political ends. The second concern is that they may consolidate rather than reduce consciousness around identity in terms of caste and religion. These fears are not borne out by experience; if anything, the experience is to the contrary.

First, we must know that the present statistical system comprising the population Census, the NSS, the NFHS and others generates data for SCs, STs, OBCs, religious groups and women on a selective basis. The government itself had put restrictions on the release of NSS data on SCs, STs, OBCs and religious groups. However, it took a bold decision in January 1999 to allow access to all of unit-level NSS data for research purposes. This decision indeed encouraged high-quality research which brought insights into existing patterns of inter-group inequities between low and high castes, minority and majority groups and tribal and non-tribal groups in terms of selected indicators. These insights helped governments to develop policies for Muslims and OBCs.

The findings have not resulted in any caste, ethnic or religious divide. Revelations made by the Sachar Committee about the status of Muslims have not induced any religious divide. On the contrary, they have helped develop a consensus for Muslim-focussed policies. Similarly, NSS data provided insights into the problems of the OBCs and Dalits among Christians and Muslims. Caste-wise census of OBCs by States including Tamil Nadu, Uttar Pradesh and Bihar has not induced any caste divide. Instead, these brought in transparency and helped governments to make unbiased policy decisions. It is a different matter that political parties hold different views about finding solutions to problems facing the OBCs and Muslims.

The second argument that disaggregated data in terms of caste and religion might be used for political ends is based on an inadequate understanding of the political decision-making process that exists in India. The scope for using caste and religious data for political ends is more if the boundaries of ignorance are wide. Data reduce the capacity of the party in power to take decisions that are contrary to facts. In fact, they strengthen the hands of the government to take evidence-based decisions and resist any unreasonable demands made by certain groups. In a democratic set-up, transparency in information enables political parties in power and in the Opposition to deal with policy issues with openness and to minimise the risk of data being used for wrong political ends.

Indian society is characterised by the presence of multiple deprived groups whose problems are common in some respects but different in many ways. In such a context, gathering relevant data disaggregated in terms of caste, ethnic and nomadic group, gender and religion is a basic step needed to ensure transparent policies, programme designing, effective targeting and programme evaluation. However, generating reliable data is something you have to be cautious about. Lessons from India and from other countries indicate that in order to avoid the pitfalls of self-reporting census data, combining it with more detailed information from household surveys on a sample basis can be employed to reduce biases and measurement errors. India has five-yearly NSS surveys to supplement data gathered from the Census operations, and Sample Registration System (SRS) data gathered on two-yearly basis. The NSS and the SRS can help bring about corrections in Census data, if necessary, for the relevant indicators. But this issue can be addressed separately. What is important is to reform the Indian statistical system in order to meet the data requirements on relevant castes, tribes, religious and other groups to frame necessary group-specific policies.

(Sukhadeo Thorat, a Professor at Jawaharlal Nehru University, New Delhi, is now the Chairman of the University Grants Commission.)



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