Poor in India: Region-wise estimates

Recently Professor YK Alagh wrote two opinion pieces on Posture-nomics and Models and Realities in The Indian Express where he referred to my work on poverty estimates. Some of these were not publicly available and are now put up in a working paper, Incidence of Poor and Poverty Risk in India across NSS Regions for Rural and Urban areas, 2004-05 and 2009-10.

Abstract

The paper provides an estimate of incidence of poor and poverty risk in India across NSS regions for 2004-05 and 2009-10 in rural and urban areas. It raises concern on increasing poverty risk and also incidence of poor in some regions. These are not necessarily among the relatively worse-off CABMOUJ (kab mouj, referring to Chhattisgarh, Assam, Bihar, Madhya Pradesh, Odisha, Uttar Pradesh and Jharkhand) states, but they also happen to be in some of the better performing states like Andhra Pradesh, Delhi, Gujarat, Haryana and Punjab.

Extracts

...

Our NSS region wise analysis shows that poverty risk being greater than unity has reduced from 33 regions in 2004-05 to 26 regions in 2009-10 for rural areas and has increased from 35 regions in 2004-05 to 36 regions in 2009-10 for urban areas. Further, from the 26 regions with poverty risk greater than unity in 2009-10 for rural areas, 18 regions indicated an increase in poverty risk when compared with 2004-05 and poverty risk also showed an increase in another 10 regions. However, from the 36 regions with poverty risk greater than unity in 2009-10 for urban areas, 20 regions indicated an increase in poverty risk when compared with 2004-05 and poverty risk also showed an increase in another 18 regions. Relatively speaking, this indicates a tendency towards convergence or greater concentration of poverty in some regions for rural areas while there is an increase in spread across regions for urban areas. This may also explain the effect on account of population shift or migration from urban to rural areas in our understanding of decomposing poverty change (Mishra 2014). 

The CABMOUJ states, the North-East states, other hilly and mountainous regions and some smaller entities in rural areas do give the impression of the increasing incidence of poor and poverty risk in largely rainfed and other vulnerable regions. That apart a matter of increasing concern is that there are regions in well-performing states where one not only observes an increase in poverty risk, but also an increase in the incidence of poor. They are both rural and urban areas of Plains Southern in Gujarat (the concerns raised by Alagh (2014a, b)), Northern Punjab and Central Plains in West Bengal, and urban areas of Coastal Andhra Pradesh, Delhi, Eastern Haryana, Himachal Pradesh, Mountainous and Jhelum Valley in Jammu & Kashmir, and Eastern Maharashtra among others.

Concluding Remarks

With reductions in poverty, the public policy focus should be among regions and sub-groups with relatively higher incidences and higher poverty risk. At the same time, it should also be a matter of concern that the incidence of poor is increasing among a sub-group of populations. At first glance, they seem to be among some CABMOUJ states, but a deeper probing indicates that this seems to be emerging in North-East states and also in some regions among the better-off states like Andhra Pradesh, Delhi, Gujarat, Haryana and Punjab. This should be an important concern for public policy.

Other recent related work

Mishra, S. (2014). Decomposing Poverty Change: Deciphering Change in Total Population and Beyond, Review of Income and Wealth, forthcoming.

Pathak DC, Mishra S. (2011). Poverty Estimates in India: Old and New Methods, 2004-05. Working Paper No. WP-2011-015. Indira Gandhi Institute of Development Research, Mumbai.

Pathak DC, Mishra S. (2013). Poverty in India and Its Decompositions: A Critical Appraisal of the New Method, in S. Mahendra Dev (ed.) India Development Report 2012-13, Oxford University Press, New Delhi, pp.209-223 and 414-417, see pre-print version.

The link to the current paper is Incidence of Poor and Poverty Risk in India across NSS Regions for Rural and Urban areas, 2004-05 and 2009-10.

Poverty Estimates in India

Poverty Estimates in India: Old and New Methods, 2004-05 is the title of a new working paper published from the Indira Gandhi Institute of Development Research (IGIDR), Mumbai. It has been co-authored by Durgesh C. Pathak, a post-doctoral fellow whom I have been mentoring for the last two years, and myself. This paper is dedicated to the memory of Late Professor Suresh D. Tendulkar who passed away recently on 21 June 2011. Below I give excerpts that draw from the two quotations  that the paper begins with, the abstract, introduction and concluding remarks.

The poor are a part of necessary furniture of the earth, a sort of perpetual gymnasium where the rich can practice virtue when they are so inclined. - Francesco Guicciardini (Discorsi Politici)

But I, being poor, have only my dreams;
I have spread my dreams beneath your feet;
Tread softly because you tread on my dreams...
- W. B. Yeats

Abstract

This paper provides estimates of poverty and inequality across states as also for different sub-groups of population for 2004-05 by using the old and new methods of the Planning Commission. The new method is critically evaluated with the help of some existing literature and its limitations discussed with regard to doing away with calorie norm, use of median expenditure as a norm for health and education when the distribution is positively skewed, difficulty in reproducing results for earlier rounds acting as a constraint on comparisons, and using urban poverty ration of the old method as a starting point to decide a consumption basket. More importantly, it discusses the implications on financial transfers across states if the share of poor is only taken into account without accounting for an increase in the total number of poor. Despite these limitations, on grounds of parsimony and prudence the state-specific poverty lines suggested in the new method, as also in the old method, are used to calculate incidence, depth (intensity) and severity (inequality among poor) estimates of poverty for different sub-groups of population, viz., NSS regions, social groups and occupation groups.

Introduction

In India, the quinquennial rounds of national sample survey (NSS) of consumption expenditure have been instrumental in providing us with an estimation of head count ratio. The Report of the Task Force on Projections of Minimum Needs and Effective Consumption Demands (Government of India, 1979) looked into the age, sex and activity specific nutritional requirements and arrived at a per capita norm of 2400 calorie for rural and 2100 calorie for urban and based on this a monthly per capita expenditure (MPCE) of Rs.49.09 in rural and Rs.56.64 in urban was identified as the poverty line for 1973-74. This was updated to accommodate price changes over time. The Report of the Expert Group on Estimation of Proportion and Number of Poor (Government of India, 1993) proposed the use of independent poverty lines for each state and updating them by looking into the state specific changes in prices. This formed the basis for official estimates of poverty provided by the Planning Commission till recently (hereafter, old method).

Some of the criticism of this approach is that the updated prices may not represent the calories norm that they were initially pegged to,  that the calorie norms should change because of demographic shifts in age and sex and change in occupational patterns, that basic requirements like health, education, sanitation and housing are not included in the calculation of poverty line, that a reference period of 30 days may not be appropriate for low frequency items of consumption expenditure among others. These have been partly addressed in the Report of the Expert Group to Review the Methodology for Estimation of Poverty (Government of India, 2009) leading to a new set of poverty estimates for the year 2004-05 that have now been accepted by the Planning Commission (hereafter, new method).

The current exercise focuses on three points. First, it discusses critically the new methodology in the light of a brief review of some recent literature by various scholars. Second, it analyses the change in shares of poverty across states and union territories (hereafter, states) that will occur due to this shift. It also tries to briefly hint the possible repercussions of these changes on poverty reduction efforts in states.  Third, it provides estimates of proportion of poor (head count ratio or incidence of poverty), depth (poverty gap or intensity) and the severity (poverty gap squared or inequality among the poor) at various levels of disaggregation like states, NSS regions, social groups and occupational categories.
...

Concluding Remarks

The Planning Commission accepted the suggestions by an Expert Group that it had constituted leading to a new method for estimating poverty in India using NSS's consumption expenditure data for 2004-05. The new method replaces the uniform recall of 30 days for all consumption items to a mixed recall where consumption of five low frequency items were collected for the last year (365 days) and appropriately adjusted to get a monthly per capita expenditure. It also takes into consideration health and education needs that the old method had not incorporated in its calorie norm. While doing these, it also opened up a number of other issues.

First, it did away with the benchmarking of a poverty line with a calorie norm that the old method was based on. They did not let the calorie norm go away totally. A reference is made to an FAO (Food and Agriculture Organization) calorie norm being achievable around its poverty line, but then this norm is for light and sedentary activities that may not adequately capture the energy needs of the poor who put in hard labour.  Second, while factoring in health and education expenditure is a positive step, using median expenditure as a norm for a positively skewed expenditure distribution may not represent the actual requirement of a poor person.  Third, having done away with a calorie norm, it begins with the poverty ratio for urban India from the old method as given. Using this ratio on the mixed recall it generates a consumption basket at the aggregate level for urban India and then uses this to generate a poverty line for states around this basket. This means that instead of using state estimates to compute a weighted all India average, it begins with the latter. A bottom-up method is replaced with a top-down approach. Fourth, the computation of consumption basket requires use of data from other rounds of NSS as also from other sources. The whole procedure is quite cumbersome and replicating it for earlier rounds or even for thin rounds is difficult and in many cases not possible. This will also have implications on the usage of time series poverty trends in macro modelling.

From a policy perspective, the new method will lead to change in share of poor. If financial transfers across states do not account for an increase in the number of poor or have a budget constraint then this means that the poorer states would end up getting less.

Despite these limitations, on account of pragmatic considerations as also for parsimony and prudence, the state-specific poverty lines have been used for computation of poverty at various sub-groups. This has been attempted in this paper for NSS regions, social groups and occupation groups for both the old and new methods. The relatively higher incidence of poverty among scheduled tribes in rural areas and scheduled castes in urban areas for social groups and that of agricultural labourers and other labourers in rural areas and casual labourers in urban areas for occupation groups have been discussed.

Though they do not play any active role in poverty estimation, yet the poor have maximum stake in poverty analysis as they are at the receiving end. Thus, a move towards a bottom-up approach where the poor get involved in the understanding of vulnerability, particularly in the implementation of policies (including on identification of poor and poverty alleviation) so as to bring in greater accountability and transparency is called for . In its absence, every attempt to define and measure poverty is like treading on the dreams of poor. If poverty measure chosen is going to help them, at least some of these dreams would become a reality. Otherwise they dry like leaves fallen from trees.

For details see the paper, Poverty Estimates in India: Old and New Methods, 2004-05.