Strata-based Quantification of Distributional Uncertainty in Socio-Economic Indicators: A Comparative Study of Indian States

TL;DR

This study analyzes distributional uncertainty in Indian states' socio-economic indicators over a decade, using the DGB distribution to model data and introducing an uncertainty percentage to track changes and gender-based differences.

Contribution

It applies the DGB distribution to model socio-economic data across Indian states and introduces an uncertainty measure to analyze temporal and gender-based variations.

Findings

DGB distribution fits well to district-wise data for population, literacy, and work participation rates.

Uncertainty percentage reveals dynamics of socio-economic indicators over time.

Literacy and work participation rates are independent of population distribution.

Abstract

This paper reports a comprehensive study of distributional uncertainty in a few socio-economic indicators across the various states of India over the years 2001-2011. We show that the DGB distribution, a typical rank order distribution, provide excellent fits to the district-wise empirical data for the population size, literacy rate (LR) and work participation rate (WPR) within every states in India, through its two distributional parameters. Moreover, taking resort to the entropy formulation of the DGB distribution, a proposed uncertainty percentage (UP) unveils the dynamics of the uncertainty of LR and WPR in all states of India. We have also commented on the changes in the estimated parameters and the UP values from the years 2001 to 2011. Additionally, a gender based analysis of the distribution of these important socio-economic variables within different states of India has also been discussed. Interestingly, it has been observed that, although the distributions of the numbers of literate and working people has a direct (linear) correspondence with that of the population size, the literacy and work-participation rates are distributed independently of the population distributions.