Reverse the thinking on identifying poverty
Instead of the government going to households, we should test the efficiency of the poorest in identifying themselves
For the last part of 2017 a number of us became experts in counting: the number of people in front when queuing at the bank or ATM machine; the number of new notes we have to get through the week; and some us were doing much bigger counts of the benefits and drawbacks of India’s currency reform.
Amidst all these numbers some stand out as transformative for our economy, the numbers of cashless Indians ready for the digital economy; and the millions of without-cash Indians who need targeted support to come out of extreme poverty. The government’s moves to expand India’s cashless digital society is being informed by counting those who are yet to have bank accounts and facilities for cashless transactions.
However, the government’s strategy to bring households out of extreme poverty perhaps doesn’t need more counting with door-to-door surveys. Instead, identifying the poorest most effectively could do with some reverse thinking: asking them to identify themselves and apply for benefits. Evidence from a randomised evaluation in Indonesia by J-PAL affiliated researchers found that, compared to door-to-door surveying, asking households to self-identify as poorest and apply for a cash transfer programme discouraged the rich households from seeking benefits, and more of the poorer households made applications.
Randomised control trials have become the bedrock for our trust in rigorously tested drugs, where one group receive the medicine, and another don’t, allowing a comparison of the treatment against life as it would have been. The same methodology of randomised evaluations is drawing light on understanding what can be effective to reduce extreme poverty. However, for policy-makers (and even more so for the poorest), the power of ascertaining impact compared to life as normal is not enough. To inform policy, researchers must be rigorous in study design and provide findings that can apply to introducing a new programme, or to improve an existing structure.
An area where research applies to policy is where we see the poorest not as passive recipients of programmes, but as decisionmakers who can be informed and equipped to make better decisions. The research in Indonesia tested three methods and found the typical methods, of visiting households to check if they are observably of the lowest income (e.g. without refrigerators or motorcycles), or asking members of the community to identify the poorest, were both inferior to self-targeting. The third method, self-targeting, which required the poorest to be active decision-makers, was found to be most efficient where more of the poorest, and fewer ineligible applicants signed up.
The first step for reducing a country’s poverty is to identify the poorest, and this is often by household surveys. India is a country not just with the greatest number of people to count, but with over 140 years of experience in household census surveys, and with the world’s largest number of poor. However, the existing methods to identify the poorest have been reported as problematic to implement.
The Below Poverty Line (BPL) ration cards are not in the hands of only the poorest, many of the wealthiest rural households were found to have BPL cards (NSSO). The 2011 Socio Economic Caste Census (SECC) was to solve the targeting problem through a national household survey observing deprivations, as in the Indonesia study. However, not all the SECC numbers have added up. For example, the SECC counted 2.57 crore rural households living in a one-room kaccha house, whereas the Census 2011 counted 6.6 crore rural households with oneroom. In addition to the accuracy problems, the cost of implementing a national census has approached that of national poverty reduction schemes.
The costs of the Census of India (2011) has been estimated at ₹2,200 crore, and the budget for the National Rural Livelihoods Mission (NRLM) in 2016-17 was ₹3,000 crore.
Knowing that targeting social assistance programmes for the poorest has not been effective, the findings from the study in Indonesia ask our policymakers to reverse their thinking for greater efficiency: instead of government going to households to count the poorest, it is time we tested in India the efficiency of the poorest identifying themselves as eligible for benefits.