Household income survey to gauge earnings welcome, but challenging

The World Inequality Lab has estimated inequality declined in India between 1947 and the early 1980s, before reversing course and widening dramatically over the last 25 years

The Ministry of Statistics and Programme Implementation has announced a comprehensive household income survey, tentatively scheduled to kick off next year. The findings of an all-India income distribution survey could reveal critical structural shifts in the spending capacities of the economy’s most vital actors, and help derive critical metrics like poverty incidence, the extent of income inequality, and urban/rural households’ general well-being. Debates about whether economic growth is lifting all boats, or whether the trickle-down effect is evident, tend to be sharp and contentious but seldom based on credible data. Instead, proxies such as Household Consumption Expenditure Survey (HCES) numbers, or the data on tax filings, are relied on. The World Inequality Lab, which uses the latter along with national income and other surveys, has estimated inequality declined in India between 1947 and the early 1980s, before reversing course and widening dramatically over the last 25 years. By 2022-23, the Lab’s researchers reckoned, India’s top 10 per cent earners got close to 60 per cent of national income, while the bottom 50 per cent received only 15 per cent. However, they noted that the data quality was poor or simply absent, like the shelved results of the 2017-18 HCES. 

 

To be sure, this is not the first attempt at income surveys — with a handful of pilots since 1955 failing to take off. Receipts and disbursement numbers were sought in two household surveys between 1964 and 1970, only for that component to be subsequently scrapped. The reason was that it threw up income estimates that were lower than households’ combined consumption and savings estimates. The underlying challenge remains pertinent even today — individuals are not comfortable sharing their exact income details even with those they are acquainted with, leave alone a government enumerator. Most high-income earners tend to understate incomes, not in the least for fear of attracting tax sleuths. Surmounting this reluctance will be fundamental for the survey’s credibility and hence the National Sample Survey Office (NSSO) must address this foremost. In South Africa, which carries out a combined Income and Expenditure Survey, the response rate is lower for queries about living conditions, including income, than it is for spending-pattern posers, despite a legal compulsion for sampled households to participate. India’s surveyors would also need to ensure that the sample size and universe of selected households are representative of its 1.40 billion-plus population. Individuals with multiple-income sources, with some yielding seasonal inflows or “in kind” payments, could be difficult to canvas accurately, particularly in rural India. The evolving urban landscape poses a more serious obstacle — gated communities and rarefied urban enclaves are simply shutting the door on enumerators and refusing to respond to surveys such as the HCES. This compels surveyors to substitute them with other households, which changes the intended sample composition, distorts survey findings, and skews the insights that inform policymaking. Overcoming this blockade is, therefore, critical for all surveys.  

 

Apart from income levels, the ministry expects the survey to gauge the impact of technology adoption on household incomes. Such quantification may prove tricky even if not as tenuous as getting people to reveal their incomes. Yet, any insights gleaned on this aspect could guide policy intervention to balance the needs of a large young workforce with the broader industry tilt towards greater deployment of robotics and artificial intelligence. Policy could be repurposed to facilitate skilling transitions and welfare measures where reskilling options are limited.