Introduction and Problem Statement

Why we need ‘people level’ data: People-level data that is representative of all India is hard to come by. Critiques and debates around the soundness of policy and the performance of policy makers and governments are typically based on ‘supply side’ actions and supply side outcomes of policy (e.g., kilometres of road built, number of students finishing high school) rather than what ‘people impact’ they had (e.g., resultant changes in income earning methods and amount earned). For example, we know from macro-economic data that the share of agriculture in India’s GDP and even in India’s rural economy is shrinking; but from this statistic alone, exactly what the extent and nature of financial dependency of rural households is on agriculture can only be conjectured - and often incorrectly is. This is far better understood from knowing how many households have what proportion of their income coming from farm and non-farm activity, how many households have exclusively non-farm income and is this non-farm income urban connected, agriculture connected or neither? PRICE’s data shows that there are 17% of rural households which exist solely on farm income and collectively have 18% share of all the income of rural Indian households; 39% of rural households have both farm and non-farm sources of income and 40% share of income, and 40% of rural households have only non-farm income (including labour that does not work in agriculture) and have 40% share of income. By our estimates, putting all this together, 35% of rural India’s household income is from farm activity at an all-India level, obviously varying from state to state.

But aren’t there already such data bases available?  There are of course the mega data bases of the Census and NSS that do provide the people-level view; but aside from their less-than-ideal frequency that does not permit a regular feedback loop to business and policy, they also do not have all the measures needed to provide a comprehensive and holistic understanding of what is happening to ‘People India’. To do this, we need data on income, expenditure, occupation, education, borrowings, savings, living conditions and access to public goods data to reside in the same data base from the same (or exactly comparable) respondents, so that linkages between them can be understood and used for, say, business opportunity mapping or for policy design. For example, in rural India, because of having an integrated data base, we see very different patterns of debt borrowing in households with different levels of farm and non-farm income - intuitive perhaps, but still needing numbers attached to them to understand performance of the financial services sector more concretely in serving rural India. We also see how much more income is possible as a result of every additional year or additional level of educational attainment, in cities, small towns and villages. Is it any wonder that people drop out of school! We know from the Census of India how many female-headed households there are and where they reside; what we additionally know from integrated data base analysis is how many they are by farm (by farm size) /non-farm (by type occupation) source of household income.

In recent times, it has been the only regular source of data on income, expenditure and saving in India. And among household surveys of its kind across the world, ICE 360° surveys hold a unique position on account of scientific and robust measurement of income, its massive sample size, range, and the depth of information it uncovers. Over the years, the survey has become the most credible source of information on Indian consumer market structures for decision makers in top marketing concerns, in public enterprises and Indian household economy in government.

Collecting data on income is an arduous and expensive task, complicated by the high propensity for intentional or unintentional respondents’ biases. While several surveys report income as claimed by respondents, PRICE has chosen a methodology which is more rigorous though more difficult to implement, using the Canberra City Group guidelines for income estimation. Canberra City Group Report has suggested a conceptual framework for income distribution analysis based on reconciliation of micro and macro approaches. It has identified a set of over hundred components of income to obtain reliable estimates for total income, of which 36 are considered essential. ICE 360 surveys considered about over 50 components of income to provide reliable estimates of total disposable household income. The major components of income covered in the surveys are income from regular salary/wages, income from self-employment in non-agriculture, income from wages (agricultural labour and casual labour), income from self-employment in agriculture (crop production, forestry, livestock, fisheries, etc), income from other sources such as rent (from leased out land and from providing accommodation and capital formation), interest dividends received, employer-based pensions. In addition, when paid in kind (example in grain), the value of that is also considered as income.

Income distribution: Another example of basic and crucial information not available in a robust and rigorous fashion is data pertaining to how the country’s household income is actually distributed among the almost 300 million households - at the most basic level, how much share of India’s income accrues to the poorest 20% and how much to the richest 20% and how much to those in between. Standardised models based on analogous countries can be applied to provide such distribution, but our primary data is often at variance and with good reason, with these estimates no matter how eminent the source of the estimation. According to ICE 360° survey (2016) data, 45% of India’s household income resides with the richest 20% of households, almost 8 percentage points down from 2004-05. The poorest 20% have a 7% share of India’s household income, up a little less than 2 percentage points from 2004-05. What is even more interesting to see is how this income is spread over different states and rural and urban town classes, different occupational and educational groups, different levels of infrastructure development and so on; and to study these not one at a time, but taken together.

Urbanization: The census tells us that census towns are increasing in number and hence they harbor an increasing population. However, what we do not know unless we have people-level information is what income people living in these towns have, and how they earn it. Business analysts talk of the increasing consumption importance of so called tier two and three towns but cannot say much about how much of India’s income lives there or how it has grown or what the nature of occupation or living conditions is of people who live here, and whether it is changing over time. It is such data that we strive to generate so that we can go beyond supply side data of how many crores of potato chips and cell phones people in each town class buy, or even the rate of urbanization, which by itself is of limited utility for business planning or urban planning policy. Finally, there is immense diversity in how the almost 300 million Indian families earn, spend, save, live, think and access public goods. God is found in the detail of the segmented sliced and diced analysis of all India data to uncover patterns and phenomena both known and new.

Employment: Indian households have come a long way in the post-reform period and as the Government is withdrawing, and in many cases abdicating, from its role in providing formal employment and social security providing basic public goods of quality to its citizens, the market economy is supposed to take over – in theory. However, there are many forms of inequality that are coming into play and many shades of public and private service providers have emerged. 94% of Indians are employed in the informal sector and there is no clear idea of how families earn and what form of job and livelihood security they have.

Subsidy management: During last five years, the Indian government has implemented several flagship welfare schemes in key areas such as financial inclusion, affordable housing, health, education and skill development, entrepreneurship, basic amenities, cooking fuel and transportation connectivity which has benefitted/impacted differently to various sections of society. These consume enormous resources but the effectiveness of them has not been comprehensively evaluated. For example, what services (economic, health, education, infrastructure, social and environment) are provided and to whom (individual demographics and characteristics - gender, income level, youth, aged persons, etc.)? What effect does the welfare schemes have on the various categories of beneficiaries?

For policy, it is essential that there is a proper understanding of the number and scale of, say, target beneficiaries of a developmental program, or socio-economic class or industry for whom a regulatory framework is being developed. But it is also equally important that there is an understanding of how, for example, target beneficiaries would become aware of, would access, would adopt, and would eventually benefit from a developmental program or a new policy. So the information provided should include both aspects – of scale and distribution, well as collateral information of how demographic, infrastructure, community, socio-cultural norms, media usage, may affect the phenomenon under study.

Inequality and inclusion: Inequality of access and opportunity also are a big concern and we need to broaden our understanding of inequality beyond income inequality. For example, poverty estimation in India can be informed with an alternative definition, and can be linked to various occupational, geographical, agro-climatic zones, educational and other characteristics, and policy can be formulated in a more specific manner enhancing its outcome effectiveness, and even in helping programmes reaching the right beneficiaries.

To summarize, there is a need to fill the gap: Today, more than ever before in India’s history, it is up to civil society, and media and parliament and the judiciary and those in Government of the right disposition to advocate for better quality public policy for which people-level, all India, rigorously collected properly analyzed information needs to be independently obtained and made available. No such data is available today in India, economic and public policy development and evaluation of its effectiveness is not based as much as it should be on rigorous information on the end beneficiaries of such policy – Indian people or households. Governments do put out some data, but it is usually ‘outlay’ data rather than ‘outcome data’; and household survey data put out by the government is either the Census of India which comes out once in ten years or the NSSO which limits its scope to expenditure and a few more indicators.  Program evaluation of social programs are done by the government and by private sector experts engaged by them or by other finding partners like multilateral agencies, but on a limited geographic scale and again, and not representative of the people of India.

The ICE 360° Survey: In this background, the current proposal is to rebuild on the widely acclaimed work already being done in this arena by PRICE, and to ensure its continuity on which much of the thinking about the Indian Consumer Economy and Citizens’ Environment rests – whether it be in the arena of government policy, business strategy or academic research, not just in India but globally.

To summarise, ICE 360° Surveys help in understanding how the pattern of distribution of well-being can be related to patterns of economic activity and the returns to labour, capital and land, and to the way in which societies are organised. The second reflects the concern of policy makers to determine the need for both universal and socially targeted actions on different socio-economic groups and to assess their impact. The third is an interest in how level of measures (low versus high) influence overall household well-being. Also, which groups in Indian society benefit from economic development and which, if any, are left out? With such knowledge policies can be formulated or reformulated to distribute or redistribute the fruits of the development efforts.

Also, as NOT-FOR PROFIT research entity, ICE 360° is having unique advantage to undertake dedicated research on India’s Citizen Environment as well as India’s Consumer Economy aiming to strengthen the quality of public policy by providing missing links of information and insight.