Sridhar Kundu : Sr. Research Analyst, Bharti Institute of Public Policy

  1. Context

How sensitive are you about the poor in our country? Can you give up one meal in a week? If yes, you can help more than 100 million people stuck below poverty line to rise above it. As India aims to achieve the Sustainable Development Goals (SDG 1 and SDG 10) of being a poverty-free nation with reduced inequality by 2030, it is essential for every citizen to contribute in whichever way possible. Even though economic growth is evident but the reduction in poverty rates is not in congruence and this is because the economic growth is still not ‘inclusive’. Average annual economic growth in India has gone above 6 per cent in the last 30 years, but on the poverty reduction front the country has not achieved its targets. Economic Survey 2020-21 highlighted the importance of economic growth on poverty reduction and of the development of social indicators for growth to reduce inequality. Budget 2021-22 emphasized upon V-shaped growth recovery through higher capital expenditure but spoke less about redistribution and inequality reduction.

This article  elucidates on a social mechanism of resource re-distribution and its consequent impact on poverty and inequality. Some studies explain various fiscal mechanisms such as taxation, subsidies and many government-run rural development and poverty alleviation programs, to help reduce poverty through redistribution of resources (Kundu and Cabrera, 2019). This article brings out the social and emotional aspect attached to voluntary resource transfer in the process of redistribution. People who have enough for their survival can help India become a poverty-free nation with their small voluntary sacrifices. This hypothesis is based on Rawl’s social justice principle of redistribution which aims at protecting the basic rights of the people.

II. Poverty and Income Distribution

In principle, transfer of resources is possible in a system when current state of distribution is not homogenous. As a result, resource flow can take place from higher concentration belt to the lower one. In India, income distribution is skewed and there is more concentration of resources in a few sections of the society (Oxfam, 2021). However, there is no income survey in India that provides a correct estimate of this skewed income distribution. The absence of an income survey leaves a way for household level consumption distribution to be used as a proxy to present this lopsidedness.

Poverty is estimated using the household-level consumption expenditure, information that is collected by the National Sample Survey Organisation (NSSO) in its various household consumption expenditure (HCE) surveys. Mostly large sample surveys are used for this purpose. The last large sample survey on household consumption expenditure was conducted by NSSO in its 68th round in the year 2011-12. Various government and non-government agencies, public policy institutions, independent researchers make their own estimates of India’s poverty ratio using this survey information. The most referred published document on poverty estimates is by the then Planning Commission, which shows that poverty ratio in India stands at 22 per cent; 14 per cent for urban and 25 per cent for rural. There is also significant variation in poverty ratio at state level.

Government sources show that inequality in India measured by Gini co-efficient stands at 0.37. Urban inequality is higher with Gini co-efficient of 0.39 compared to 0.31 for rural (Planning Commission, 2014). Estimation from NSSO HCE survey, 2011-12 household level data, also presents clear picture of skewed resource distribution. As estimated, about 30 per cent of total resources are concentrated in the 10th decile of consumption class. On the contrary, only 3.5 per cent of total resources is estimated to be possessed by the 1st income decile class (Figure 1). Total resources here refer to total amount of consumption by all individuals in the country. This disproportionate resource allocation suggests, while some people live in hunger and starvation, others enjoy a wealthy and resourceful life.

 

Source: Estimated from NSS 68th Round Household Consumption Expenditure Survey, 2011-12

Figure 1 also presents, that not only the first decile, but until the 7th decile, the resource allocation share is not proportionate to the population share. Thus, it can be said that 70 per cent of the population receive resources less than their proportionate share in total population.  The top three deciles own more resources and are in an advantageous position. This shows that there is a possibility of resource transfer from the top three deciles to the bottom deciles.

III. Direction of Resource Flow

As 22 per cent of India’s population lives below poverty line, they come under first three income deciles. Therefore, a certain amount of resource flow from top three deciles to the people living below poverty line would help improve their standard of living.  The question that arises here is about the nature and quantity of resource flow and how it could take place without any external forces. In this context, skipping a meal is a plausible way to generate some resources and its further flow to the bottom.

Average household consumption expenditure of the people in 10th decile class is about ten times higher than the people in the 1st  decile class (Table 1). Table1 also presents that the 10th decile income class is so rich that its average consumption expenditure is two times of the 9th decile class. The skewness of income distribution is rightly captured by the Lorenz Curve named ‘no-sacrifice’ in Figure 2.

Table1. Household consumption expenditure (Rs.) of the people under various classes

Consumption Class Average Monthly Expenditure Standard Deviation Total Population Average Expenditure on a Meal
1 650.4 106.7 202000000 6.3
2 881.3 51.8 160000000 8.4
3 1054.5 49.4 138000000 10.0
4 1228.8 52.1 118000000 11.6
5 1423.8 61.7 107000000 13.3
6 1658.3 74.4 96500000 15.3
7 1963.6 104.4 85700000 17.8
8 2413.7 159.3 76900000 21.5
9 3176.5 302.0 66600000 27.6
10 6337.2 4354.5 58000000 48.6

Source: Estimated from NSS 68th Round Household Consumption Expenditure Survey, 2011-12

Figure 2. Lorenz Curves for Consumption Distribution defined by process of redistribution.

 

Source: Estimated from NSS 68th Round Household Consumption Expenditure Survey, 2011-12

Figure 2 also provides a set of Lorenz Curves (LCs) presenting different Lorenz ratios for different consumption distributions. The LCs are generated based on consumption distributions addressed by various resource distributions. The LC farther from the line of equality i.e., the 45-degree straight line shows higher ratio and presents greater degree of inequality than the LC that lies relatively less farther.

IV. Resource Flow and its Impact

The pre-transfer situation presented by LC of no-sacrifice shows higher degree of inequality. But with the rate of rise in resource transfer from the top three income deciles to the people living below poverty line, the LCs start moving closer to the line of equality. LC for sacrifice of three  meals a week is far closer to the line of equality than the same stand for sacrifice of two  meals and one meal per week.

Figure 3. Changes in Poverty Level with possible resource transfers from top three decile classes

 

Source: Estimated from NSS 68th Round Household Consumption Expenditure Survey, 2011-12

Reduction of inequality is accompanied by reduction of poverty level by the resource transfer. As said above, poverty level during the pre-transfer situation was 22 per cent; 25.4 per cent for rural and 13.7 per cent for urban. Sacrifice of one meal a week by people,  who fall under top three income classes could help reducing total poverty by 7 per cent, which would enable more than  seven crore poor jump over the poverty line. In the rural areas, the poverty reduction rate is as high as 7 per cent compared to 3 per cent in urban areas.

With the rise in resource transfers through higher-order sacrifices from  well-off people, more and more benefits are accrued by the people within the poverty circle. Sacrifice of two meals a day could pull India’s poverty ratio down to 9 per cent. In this sacrifice, the rural poverty ratio could reach 10 per cent and urban at 6.8 per cent. Further, if people in the top three brackets could fast one day a week which is about three meals, that could feed about 17 crore people and help bring down poverty ratio to 5 per cent.

V. Importance in the present day

Over the years, governments at the Union and state level have been taking several policy measures in the direction of reducing poverty and inequality. As pointed out by Economic Survey 2020-21, social sector development is an important step in this direction. However, resource constraint moderates the pace of social sector development. The combined social sector spending of both Union and state governments stands at less than 8 per cent of India’s GDP (RBI, 2019).

As estimated and explained above, sacrificing one, two or three meals a week for reducing poverty in India is hypothetical. However, the exercise makes it clear that even a small sacrifice like foregoing food once in a week has great impact on poverty and inequality. The impact is higher  in rural sector as compared to urban.   Considering the fact that poverty is more concentrated in rural areas, any redistributive policy would certainly create a larger impact on India’s rural economy.

More importantly, when India is aiming to be a poverty-free nation by 2030, as a part of its commitment to achieve maximum progress on various indicators as per the (SDGs), marginal sacrifices by the rich can bring in a huge difference. At a time when rural, migrant labour force is braving the slowdown because of Covid-19 pandemic, this social mechanism of resource transfer could help strengthen the economy. What is needed is a little nudge and some awareness on how a small sacrifice can elevate the poor of this country.

Email: bipp@isb.edu; sridhar_kundu@isb.edu

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“The views expressed in this article are personal. Sridhar Kundu is  Sr. Research Analyst at the Indian School of
Business.”