Data does not lie

• There is debate going on over Multi-dimensional Poverty (MPI) estimation and Covid impact on poverty.

Estimation of MPI

• Two set of estimates: As provided by the Oxford Poverty and Human Development Initiative (OPHI) that compiles these data across countries, primarily from Demographic and Health Surveys (DHS).
• Uncensored estimate: For individual indicators, which correspond to a simple question regarding whether a household is deprived (poor) in a given indicator for example, nutrition.
• Censored estimate: It helps shift the focus onto those who have been (multidimensionally) identified as poor.
  • A higher MPI suggests greater intensity of deprivation while a higher censored poverty rate is an important signal to policymakers to redirect policy focus.

Two stage process under censored estimates?

• Multidimensionally poor: The first stage estimates the population that is multidimensionally poor.
• Poor on each indicator: The second stage estimates the population that is poor in each indicator for the multi-dimensionally (MP) poor.
• E.g. During 2005-06, the MP poor were 55.1 per cent; uncensored nutritionally poor were 57.3 per cent; and 44.3 per cent were censored nutritionally poor.
• Poor in both categories: Close to 80% of the nutritionally deprived are also multidimensionally poor. For the DHS India survey years, censored estimates are used.

Advantage of using censored estimates

• No mismatch in absolute and indicator specific poor: Indicators such as assets, some households may be considered as deprived (poor) even as they are relatively better off in other areas such as nutrition, sanitation, etc.
• Interlinkages between poverty indicators: It allows the capture of interlinkages between several poverty indicators.
• For example, environmental enteropathy is known to have a key role in nutrition absorption in children.
• Therefore, investments made towards providing sanitation facilities and piped water connections will have an impact on nutritional absorption.

What latest data on MPI says?

• Annual improvement in health and education: Annual pace of improvement in the health, education and living standards indicators during 2005-15: 7.3, 10.0 and 9.6 per cent respectively.
• Efficient redistribution of resources: An efficient redistribution combined with direct fiscal resources targeted specifically to reduce deprivation across individual indicators.
• Inclusive growth: Period I would show a greater improvement because the dominant component of poverty decline, growth in per capita consumption, was about 0.8 percentage point higher in period I (annual 3.8 per cent increase vs. 3 per cent in period II).
• Faster poverty decline: The pace of MPI index decline was almost twice the pace in period II relative to period I.
• This result is strongly indicative of considerably more inclusive (and more efficient and less corrupt) growth in period II compared to period I.
• Poor performance on some indicators: For only four indicators is the rate of uncensored poverty decline lower in period II.
• Assets and school attendance are lower in period II for both uncensored and censored poverty.
• School attendance improvement is expected to be lower as one approaches 100 per cent enrolment, the pace of change from 20 to 25 per cent enrolment is 25 per cent versus a pace of only 1 per cent when enrolment increases from 95 to 96 per cent.

Conclusion

• Poverty estimation debate will continue among the experts.
• Government should solely focus on poverty reduction policies. Present priority should be reducing the Covid induced poverty.