Elimination of Poverty by Measurement

Ashok Nag

[It would be nice if the poor were to get even half of the money that is spent in studying them.” — William E. Vaughn, Columnist]

Until recently, official estimates of the head-count ratio of poor in India relied on the Household Consumer Expenditure Survey conducted by the National Sample Survey Office (NSSO). The Planning Commission was tasked with calculating this ratio based on the NSSO's consumer expenditure survey and the prevailing Poverty Line (PL). In the Indian context, the Poverty Line is defined as the monetary value of a basket of goods sufficient to meet the "Basic Needs" of an adult individual. The last assessment of poverty using this measure based on the Poverty Line was conducted for the reference period of 2011-12.

Niti Aayog, the successor to the Planning Commission, has since developed a new measure of poverty called the Multidimensional Poverty Index (MPI), which is globally recognised. The baseline MPI for India was computed using data from the National Family Health Survey (NFHS-4) for the reference period of 2015-16. Subsequently, the second MPI, with a reference period of 2019-21 and using data from NFHS-5, was released in July 2023. This article raises certain concerns regarding the reliability of the MPI methodology as implemented in the Indian context. Additionally, it evaluates NitiAayog's assertion that "India has achieved a remarkable reduction in its MPI value and Headcount Ratio between 2015-16 and 2019-21, indicating the success of the country's commitment and action to address the multidimensional nature of poverty through its multisectoral approach."

Any effective poverty measure must address, at minimum, two key issues: (1) the identification of the poor and (2) the aggregation of poor. Until 2011-12, the poverty line (PL) served as the threshold for official poverty measures in India. Due to the absence of reliable income estimates, household consumer expenditure was utilised for identifying impoverished households. Over the years, the Planning Commission of India established five Expert Committees, spanning from 1962 to 2014 at intervals of 10 to 15 years, to review methodologies for poverty identification. However, these reviews remained within the framework of PL-based identification processes.For example, successive expert groups deliberated on issues such as whether a single poverty line should be used for rural and urban India, whether separate poverty lines should be established for each state, and the selection of consumption baskets. The most recent committee, led by Dr C Rangarajan, submitted its report in June 2014. However, with a change in the Union Government, the report was disregarded.

Regarding aggregation, the distribution of household consumer expenditure, as estimated by the National Sample Survey Office (NSSO) for various years, was employed to determine the percentage of households with monthly consumer expenditure below the relevant poverty line. The table below presents the headcount ratio of poverty for selected years, computed following the methodology prescribed by the Suresh Tendulkar committee of the former Planning Commission. Comparison with ratios from previous years is avoided due to the incompatibility of computation methods.

Table 1
 All-India Head Count Ratio (%) for Poverty Line based on Tendulkar Methodology
Area   2004-05   2009-10    2011-12
Rural          41.8           33.8           25.7
Urban        25.7           20.9           13.7

It may be seen that during first 7 years of Manmohan Singh government, the poverty declined by a compound rate of 6.7% in rural India and by 8.6% in urban India. If such a growth rate had persisted, by 2019-20, the rural poverty would have declined to 14.87%. Although it is not comparable with MPI, it is interesting to note that the All-India MPI Headcount ratio for 2019-20 has been estimated as 14.96%. In other words, the momentum of decline in poverty level has continued, abated in the post 2014-15 period, without any remarkable change in the pace of decline.

Measuring the level of poverty in a specific community using a PL is neither optimum nor logically consistent. It is not optimum because it ignores the income or expenditure distribution of population identified as poor. To give a stylized example, let us consider two scenarios with the same PL and poor headcount ratio-100 and 25% respectively. In one scenario 20% is having income between 90 and 100. In another one 20% is having income between 10 and 50. Obviously, the first scenario, from a social welfare perspective is much more desirable than the second one. The PL and Headcount based measure of poverty is logically inconsistent because expenditure or income is only one aspect of poverty and a household having been identified as non-poor in PL based identification process, may suffer from extreme deprivation in respect of many other basic requirements of life. In other words, the “quality of life” led by such a household is below a socially expected minimum.

Despite the numerous limitations inherent in poverty line (PL) based measurements, it is undeniable that the monetary value of expenditure for a poor household is much easier to quantify and compare across households than the ordinal measurement of many other dimensions of poverty. Once a poverty line is determined for a specific period and community, its implementation, calculation, and interpretation are unambiguous. Furthermore, even the distributional aspect can be addressed by assessing what is known as the "Poverty Gap," which measures the average monetary distance of all poor households from the poverty line. However, despite these advantages, the Multidimensional Poverty Index (MPI) has gained acceptance from international agencies, including the UN, because it provides a superior measure of a household's overall "well-being."

MPI is founded upon two core concepts: Deprivation and Dimension. Deprivation, represented as Boolean data (1 or 0), gauges whether a household qualifies as deprived based on its access to or availability of items essential for individual well-being—referred to as indicators. A household is deemed deprived if it fails to meet specific criteria. Take, for instance, the indicator "Years of schooling." A household is classified as deprived concerning this indicator if "Not even one member of the household aged 10 years or older has completed six years of schooling." The ultimate identification of a household as multidimensionally poor hinges on how deprivation statuses across each indicator are aggregated. However, this aspect of the MPI methodology is not addressed in this note.

The indicators are grouped into dimensions. The three dimensions mostly used are Health, Education and Cost of Living. Although UNDP uses 10 indicators, in India 12 indicators are used for identification of a deprived household in respect of a given indicator. All dimensions carry the same weight 1/3 for aggregation purpose. For example, the dimension “Standard of living “consists of the following indicators each with weight of 1/21: Cooking fuel, Sanitation,Drinking water, Housing, Electricity, Assets, and Bank Account. It is important to note that no monetary indicator has been included in the MPI.When considering various indicators, the identification of a household as deprived aims to target those that are most severely deprived. Below are some examples.

The Bank Account indicator returns a positive value (i.e. not poor) when at least one member of the household has a bank account or post office account. However, the indicator does not capture information regarding account usage frequency, average balance, or the purpose of opening the account. According to the NHFS 2019-21, only 4% of households are deemed deprived (i.e., poor) based on this indicator.

An investigation carried out by Indian Express has found that half of the Jan Dhan accounts, primarily held by less privileged people, maintain a zero balance.Data disclosed by the Finance Minister on the 9th anniversary of the Pradhan Mantri Jan DhanYojana (PMJDY) indicates that the average deposit amount in Jan Dhan accounts is merely INR 4000. For impoverished households, such accounts primarily serve as conduits for receiving government benefit payments and cannot be viewed as indicators of escaping poverty.
Moving on to the Electricity indicator, a household lacking access to electricity is categorized as deprived in relation to this measure. The estimated headcount ratio of poverty for this indicator stands at 3.27%. However, for this indicator to accurately reflect deprivation, it is crucial for surveyors to assess the average daily consumption of electricity rather than solely the presence or absence of an electricity connection.

It's worth noting that the all-India average per capita domestic electricity consumption was 224 kWh in the year 2019-20. For instance, one incandescent light bulb used for 4 hours a day would consume 12 kWh in 31 days, totaling 144 kWh annually. This means that if a household were to consume electricity at the average rate, it would be enough to power just two light bulbs for 4 hours each day. It becomes evident, without the need for extensive surveying, that Niti Aayog's measure of deprivation concerning electricity consumption grossly underestimates the actual deprivation experienced by households.

Regarding the Assets indicator, a household is considered deprived if it possesses no more than one of the following assets: a radio, TV, telephone, computer, animal cart, bicycle, motorbike, or refrigerator, and does not own a car or truck. Therefore, a household owning, for example, a 10-year-old radio and a 20-year-old bicycle would be classified as non-poor according to this criterion. The estimated percentage of poverty using this indicator was 10.16% in 2019-21.

In this context, it would be beneficial to combine data from the National Family Health Survey (NFHS) with asset ownership data obtained from the All-India Debt and Investment Survey-2019. According to this survey, the average value of assets was INR 41,000 in rural areas and only INR 2,000 in urban areas. Considering the types of assets held by households, it was found that 91% and 92% of households in rural areas owned land and buildings, respectively. Thus, the only assets of substantial value likely to be owned by poor households are small patches of land and thatched huts for shelter. The corresponding percentages in urban areas were 63.2% and 63.9%, respectively. Given this data, it may be argued that the ratio of deprived households in terms of asset ownership is significantly underestimated. In fact, for each of the indicators comprising the dimension of Standard of Living, the approach adopted by Niti Aayog to identify deprived households would only target the most impoverished individuals.

The current space constraints prevent the author from delving into all the issues regarding the reliability of each indicator in measuring the multidimensional poverty status of the Indian population, as well as its aggregation process. However, in essence, the MPI should serve as a supplement to PL-based measures of poverty rather than a substitute.

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Vol 56, No. 37, Mar 10 - 16, 2024