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Poverty in India: Rediscovering Its Multidimensional Nature

Updated on December 5, 2013
Helpless Poor
Helpless Poor

India – The Largest Pocket of Global Poverty

India, the largest democracy of 1.25 billion people, is also the biggest center of poverty in the world – it is both widespread and intense. It occupies 2.4% of world’s land area but supports about 18% global population. At the rate of 1.33% its population is growing by about 17 million every year and is expected to surpass Chinese population before 2030 and reach 1.60 billion by 2050. Lack of development is the basic cause of rather high population and extreme poverty. In fact, at present the two are feeding each other. Currently, India is a poverty watchers’ delight and perhaps the biggest global laboratory of poverty researchers. The future of world poverty depends upon India’s performance to a large extent.

How the impressive economic growth of past two decades has failed to counter poverty is a well known fact and point to a wrong development model. People rightly wonder: Is India a Poor Country or an Emerging Superpower?

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Can you Help me?

Problem with Income Poverty Estimates

According to the government estimate of July 2013, 22% people live below the official poverty line, a fall of 15% since 2004-05. It meant a reduction in the number of poor from 407 million in 2004-05 to 269 million based in a survey done in 2011-12. So, in seven years about 140 million Indians cease to be poor and the poverty line used to get this miracle: daily per capita consumption of Rupees 28.65 in cities and Rupees 22.42 in rural areas. [1USD = Rs 63 - Rs 65] Of course, no one believed it particularly since just few months ago the estimate was 29.8% poverty based on 2009 data. After widespread criticism, a committee was appointed to revisit the poverty line philosophy; its report is due only next year – standard evasive procedure of governments! The World Bank’s $1.25-a-day benchmark of extreme poverty puts the figure at 42% and its $2 per day line makes 76% population poor.

The problem with all such single dimensional poverty measures based on money is that they can’t tell if people have access to what is useful and valuable for them. They are also blind to deprivations such as malnutrition, inadequate healthcare and education facilities, poor sanitation and housing, and so on. Income level cut-offs can’t say anything about people’s access to these essential things. In other words, income is just a means to lead good life but what is important is the ends, not means.

Poor people generally are undernourished, not in good health, lack education and skills for good jobs and more importantly they can’t just suddenly become capable of taking care of all such deprivations. From the practical angle, we actually want to know if a person has access to health services when he needs it, not whether he has the income to do so. We are interested in knowing if he can actually feed himself well, not if he has income to buy food.

If we know such information we know how they are poor, which things they are deprived of and figure out what they actually require. Such a multidimensional picture of deprivations is going to be of immense value to policymakers.

Income poverty line figures can’t reveal such information. For example, economic growth has been quite strong in India in the past decade, but the prevalence of child malnutrition stayed virtually constant at about 50%. This is among the highest in the world.

The Multidimensional Poverty Index (MPI)

A multidimensional approach to poverty recognizes that the poor experience several forms of deprivation – such as poor health, lack of education, inadequate living standard, lack of income (as one of several factors considered), social exclusion, disempowerment, poor quality of work and lack of security from exploitation and violence.

The Multidimensional Poverty Index (MPI) has the capacity to offer precisely such information on deprivations people face. It was launched in 2010 by Oxford Poverty and Human Development Initiative (OPHI) of Oxford University and the Human Development Report Office of the United Nations Development Program (UNDP). The MPI assesses three vital dimensions of poverty – education, health, and living standard – through ten indicators. It provides both the extent and nature of simultaneous deprivations people are facing.

The final MPI index number is the product of two numbers: the incidence or headcount ratio (H), (the percentage of people identified as poor) and the average intensity of deprivation deprivations each poor person experiences on average. So, MPI = H × A.

10 MPI Indicators
10 MPI Indicators | Source

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AN MPI Analysis of India during 1999 – 2006

Using the NFHS dataset of 1998/99 and 2005/06, a recently published MPI analysis in March 2013 reported that between 1999 and 2006, multidimensional poverty in India fell faster than income poverty. Significant reductions were made in all ten indicators, and the biggest absolute improvements were seen in access to electricity, housing conditions, access to safe drinking water, and improved sanitation facilities, rather than in education and health indicators.

However, India’s neighbors – Nepal and Bangladesh – are performing better and are reducing poverty faster (by 3 times) than India. India’s poverty reduction rate was about 1.2% per year compared with 4.1% of Nepal and 3.2% of Bangladesh which are economically behind India. Even India’s best-performing States — Kerala and Andhra Pradesh — progressed only about half as fast as Nepal or Bangladesh in reducing multidimensional poverty.

It appears strange but more recent dataset than 2006 is not available for India. So the most recent trends can’t be assessed. From 1999 to 2006, MPI poverty in India fell by 16%, from 0.300 to 0.251. This was mainly due to a statistically significant reduction in the percentage of people identified as poor (H); the reduction in the intensity of poverty (A) was smaller, but still statistically significant.

Trends by state

Poverty reduction varied widely across 25 states and 17 states achieved statistically significant reductions in MPI poverty. However, multidimensional poverty was reduced least in the poorest states such as Bihar, Madhya Pradesh, Rajasthan, Uttar Pradesh and West Bengal – where over 60% people were poor in 1999. They, however, reduced income poverty more than rich states, highlighting the need to measure and analyze both types of poverty.

Among the states in the south, the reduction in overall MPI poverty was largest for Andhra Pradesh, which not only reduced its headcount ratio by 15%, from 56.7% to 41.6%, but also reduced the average intensity of poverty experienced by each poor person by the equivalent of one standard-of-living indicator. Kerala also posted impressive performance and reduced the percentage of poor people from 32.6% to 9.5% in six years. Kerala made large improvements in all indicators except cooking fuel, with the most notable improvements taking place in sanitation, water and electricity. The other two southern states – Tamil Nadu and Karnataka – also gave good progress. Together the 4 states reduced the percentage of poor people by more than 13 percentage points each in absolute terms.

Despite this good news, even India’s best performing states – Kerala and Andhra Pradesh – progressed just over half as fast as Nepal or Bangladesh.

Trends by social group and household characteristics

Some poor groups, such as the Scheduled Castes in the rural areas, or those with only 1-5 years of education, experienced strong reductions in MPI poverty. Yet the poorest groups such as the Scheduled Tribes, Muslims, female-headed households, and households whose head had no education – saw slower reductions in MPI poverty.

The heartening news is that the deeply poor decreased from 26.4% of the population in 1999 to 19.3% in 2006. But there is still a long way to go: nearly a fifth of India’s population (250 million) was still deeply poor in 2006, and millions more remained acutely poor.

The MPI 2011 Summary

MPI Poverty Status in 2010/11

  1. The MPI 2011 showed that 53.7% of the Indian population is poor – deprived in 30% indicators. It is much higher than the official figure of 22%. About 37.5% population is poor in 40% indicators; 28.6% Indians are poor in 50% indicators, 18% people are deprived on 60% indicators, and 9% population is deprived on 70% of the 10 indicators. The bar chart below shows it.
  2. Three biggest contributors to the MPI 2011 in India were: Nutrition (23%) followed by Child Mortality (13%) and school attendance (12%)..
  3. About 51% population is deprived of cooking fuel, 48% people lack proper sanitation, and 38% are undernourished.
  4. In the 2010 analysis, there were more 'MPI poor' people (421 million) in just eight Indian states (Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and West Bengal) than in the 26 poorest African countries combined (410 million). Hope some improvement will be seen with fresh and current dataset when it becomes available.
  5. As reported in 2010, the MPI poverty analysis of castes and tribes revealed that the Scheduled Tribes (ST) are most poverty stricken: 81% ST population is poor, followed by 66% poor in the Scheduled Caste (SC) community and 58% poor among Other Backward Class (OBC). Among rest of the Hindus only 33% are MPI poor. The ST, SC and OBC community also shows high intensity of deprivation – between 52% to 59% of weighted indicators.

Conclusion

In 2013, the analysis of MPI has been done only with the dataset from 2005/06. So the picture may not reflect the current realities. However, it becomes apparent that there is reduction in poverty as suggested by both the income line and the multidimensional poverty analysis. Over 50% Indians are poor in terms of MPI and between one-quarter to one-third are deeply deprived. What is worrisome is the slow pace of poverty reduction in the poorest states which form a major part of the population. India should perhaps abandon its income poverty line in favor adopting the multidimensional approach as countries like Mexico, Columbia, Malaysia and Bhutan have done.

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