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Poverty in all its faces -C Rangarajan & S Mahendra Dev
-The Indian Express

Growth can alleviate poverty but its definition needs to expand to make any tangible difference on the ground.

Amidst the din caused by the story of rising billionaires, the message on India’s poverty decline in the recent report of the Oxford Poverty and Human Development Initiative has been lost. UNDP and Oxford University released the report on Global Multidimensional Poverty Index (MPI) 2018. This report covers 105 countries. The MPI is based on 10 indicators: Health, child mortality, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, housing and assets. This report has specifically discussed the case of India. It is well worth quoting the opening paragraph on India: “India has made momentous progress in reducing multidimensional poverty. The incidence of multidimensional poverty was almost halved between 2005/6 and 2015/16, climbing down to 27.5 per cent. The global Multidimensional Poverty Index (MPI) was cut by half due to deeper progress among the poorest. Thus within ten years, the number of poor people in India fell by more than 271 million — a truly massive gain”. This is indeed high praise. The report also says that the poorest groups had the biggest reduction in MPI during the period 2005/6 to 2015/16, indicating they have been “catching up”.

Is the conclusion of global MPI a new revelation? No. The estimates of poverty-based on consumer expenditure and using the Tendulkar committee methodology show over a seven-year period between 2004-05 and 2011-12, the number of poor came down by 137 million despite an increase in population. According to the Rangarajan Committee methodology, the decline between 2009-10 and 2011-12 is 92 million, which is 46 million per annum. For a decade, it will be larger than that of global MPI.

The poverty ratios based on Tendulkar and Rangarajan Committee methodologies are lower than as estimated by global MPI. We have reservations on using multiple indicators as these multidimensional indicators/measures raise several issues regarding their measurability, aggregation across indicators, and, crucially, of databases that provide the requisite information at reasonably short intervals. These need to be considered and evaluated carefully. Aggregation is another problem. In principle, they should be independent. Access to safe drinking water, for example, cannot be aggregated with indicators like child mortality. Even in respect of independent indicators, analytically appropriate rules of aggregation require that all of them relate to the same household. More generally, this requirement poses several data constraints.

It may be noted that we are not against multidimensional poverty or deprivations. One can analyse the progress of non-income indicators like education, health, sanitation, drinking water, child mortality etc. over time with income or consumption poverty. But, converting all of them into an index poses several problems. Deaton and Dreze (2014) also indicate that “it is important to supplement expenditure-based poverty estimates with other indicators of living standards, relating for instance to nutrition, health, education and the quality of the environment”.

In the minds of most people, being rich or poor is associated with levels of income. The various non-income indicators of poverty are, in fact, reflections of inadequate income. Defining poverty in terms of income or — in the absence of such data — in terms of expenditure, seems more appropriate and it is this method which is followed in most countries. Of course, it can be supplemented with non-income indicators but without aggregating them into index.

In recent years, there has been a lot of discussion on increasing inequality. It is true that rising inequality has adverse economic and social consequences. The Gini coefficient or other measures of inequality are being used to examine trends in inequality. Income and wealth inequalities are much higher than consumption inequality. According to some estimates, Gini coefficient for consumption is 0.36 in 2011-12 in India. The Gini coefficient for consumption has shown only a small rise over a period of 10 to 12 years. Inequality in income for 2011-12 is high with a Gini coefficient of 0.55 while the Gini coefficient for wealth is 0.74 in 2011-12. Thus, the income Gini is 20 points higher than the consumption Gini, while the wealth Gini is nearly 40 points higher than the consumption Gini in India.

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