Identification of backward district in India by applying the principal component analysis and fuzzy approach: A census based study. (December 2020) - Basu, Tirthankar; Das, Arijit
Abstract: India is a large country with several axes of inequality. Among the various axes of inequality, the regional disparity is the prominent one. This study aims to find out the most backward districts in India with the help of the latest available statistics data. For this purpose, 25 indicators are selected and these are further categorized into six dimensions based on their characteristics. The principal component analysis is applied in R Studio for the data dimension reduction and the calculation of weight. Later on, the fuzzy approach is taken into consideration for integration purposes. The final output shows that 80 districts that are located mainly in Madhya Pradesh, Jharkhand, Odisha, and Bihar are the most backward. Contrary to this, 73 districts that are located mainly in the western coastal plain and north-west India are the least backward. Besides, this study also observes that development patterns in India are not uniform in character. Most of the developed districts are concentrated in few pockets. The suitability of this study is analyzed in comparison to other studies. The result shows comparatively better acceptability of this model in comparison to other studies. Highlights: This study has tried to identify the backward districts in India. 25 indicators are selected for this purpose. PCA and the Fuzzy approach are applied for the final output generation. 80 districts mainly from central India has emerged out as very high backward. 73 districts from the north-west and south-west part show least backwardness.