Decomposition of intra-household disparity sensitive fuzzy multi-dimensional poverty index: A study of vulnerability through Shapley machine learning

The well accepted multi-dimensional measures have failed to properly project the vulnerability of human-beings towards poverty. Some of the reasons behind this inability may be the failure of the existing measures to consider the graduality within the concept of poverty and the disparities within the household in wealth distribution. So, this work wants to develop a measure to estimate the vulnerability of households in becoming poor through incorporating the intra-household disparities through the factors which suffer from graduality. The decomposition of the grade of vulnerability on the causal factors is also under the purview of this work. To that respect the idea of fuzzy logic and decomposition through artificial intelligence has been used to develop a mathematical framework. So, the idea of Shapley Value Decomposition method has been used extensively. This decomposition is implemented here with the help of Shapley Machine Learning. This decomposition will help the planners to locate the role of different dimensions behind the vulnerability of human beings to become poor more efficiently.