This is my first write-up that would approach a technical subject to lay the ground for future critical works. Poverty is the ultimate issue that we have been combatting for the past 100 years at the very least. We understand what poverty is through our cultural and social perspectives, however there is a need to study poverty in an academic sense that would help us analyse and solve it at every possible level.
Amartya Sen in his paper, ‘Poverty: An Ordinal Approach to Measurement’ (Sen, 1976) explains the two important steps that must be taken in order to measure poverty namely,
- Identifying the poor within the total population
- Constructing a numerical measure of poverty
This has been the guideline with which poverty measurement frameworks are made, both unidimensional and multi-dimensional methods. In unidimensional poverty measurement the variable may only have ordinal significance. A unidimensional method ideally sets a line of poverty, a minimum level below which a person is considered to be poor (Poverty line at $1.25). An FGT index (Foster-Grer-Thorbecke Index) is a typical example of a unidimensional method of measuring poverty. The aggregation of different components and non-correlating variables in creating a composite would not truly represent if the aggregate component truly represent the resource distribution or achievement of people and the actual trade-off among the variables and hence posing a risk of improper selection of weights or of a proper functional form (Alkire and Foster, 2011). There arises a question on what could be done if the aggregated variable cannot be constructed due to the fact that there may be several important distinct dimensions?
We could use dimension specific line as the guideline in determining the people who are deprived and the nature of their deprivation (Bourguignon and Chakravarty, 2003) and create a cutoff – called deprivation cutoffs (Alkire and Foster, 2007). The identification can be done in this framework as follows (Bourguignon and Chakravarty, 2003):
- A person who is deprived in any one dimension is considered poor and this type of identification is called ‘Union Identification’
- A person who is deprived in all dimensions is considered a poor and this type of identification is called ‘Intersection Identification’
The problem with this type of classification was observed by a study on the population of India (Alkire and Seth, 2009), where 10 dimensions were used to study poverty. The union approach from that study determined that 97% of the Indian population is poor, whereas the intersection approach concluded that 0.1% of the population to be poor.
Another method as adopted in the creation of Human Development Index by Amartya Sen and Sudhir Anand (1997), where they calculate the achievement levels associated with a person in relation to the people’s achievement levels in a given dimension. This method is called marginal method and is based on the concept of marginal distribution. In this method, however, two people with the same marginal distribution would be considered to be in the same level of poverty. Sabina Alkire’s criticism of this method (Alkire and Foster, 2011) is that the multiple sourced marginal measures, while providing useful measurement of poverty, the anonymity (unlinked data) of the person makes it difficult to identify who is multidimensionally poor.
Sabina Alkire and Foster (2007, 2011) have developed a ‘dual cutoff’ method in identifying and describing poverty. The progression of the method closely relates to the unidimensional measurement method except for one distinctly different aspect, which is the identification step. First the data is analyzed to determine the depreciation cutoff and then the value is used to identify if that level of deprivation is considered poverty through the poverty cutoff. Multidimensional Poverty Index is developed as a criticism towards the conventional method of determining poverty through income, expenditure or consumption and to measure deprivation through non-monetary factors that contributes towards well-being. It uses health, education and standard of living indicators as a measure of poverty with a particular focus on linked data to identify who the poor is and thereby helping to create policies that caters to the deprived population (Oxford Poverty & Human Development Initiative). The Global Multidimensional Poverty Index (Global MPI) has effectively replaced the Human Development Index that has been used earlier in measuring the multidimensional poverty and development. Though there are pre-defined measures, weights and indicators, the MPI gives the user the flexibility to consider dimensions and factors that is tailored to the study specifically.
I understand that this particular article is more technical than what I usually post, however I also feel it is essential to set the ground for my future articles that would be critical of poverty measurement and policies. If you would like further clarification of any part of this article please do drop a comment or reach out to me through e-mail. Hopefully I could could simplify the concepts and details in upcoming works.