Unveiling Inequality: Mapping Asset Disparities in Azad Jammu and Kashmir (Pakistan) - Naveed, Tanveer Ahmed; Ullah, Sami; Mughal, Sundus Aijaz; Rizvi, Badar (iRASD Journal of Economics, 2024)
The main objectives of this study are to construct a valid and reliable asset index at the household level for 10 districts of Azad Jammu and Kashmir (AJK) by using Multiple Indicators Cluster Survey micro-data and to estimate economic disparities by calculating Gini-coefficient and Palma Ratio. The asset index is considered a better estimate than expenditures or current household income to gauge a household’s living standard and its potential resilience to deal with economic shocks. The dimensional structure of assets is assessed by applying Exploratory Factor Analysis (EFA) and Tetrachoric Principal Component Analysis (PCA). Further, this paper has applied Classical Test Theory (CTT) and Item Response Theory (IRT) to ensure the reliability of the household-based asset index. Furthermore, the Gini-coefficient and Palma ratios are estimated by using the composite household-based asset index to estimate economic disparities in all 10 districts of AJK. The dimensional structure of assets, reliability, and validity analysis suggest to use 21 assets (out of 30 items) to construct the household-based asset index. The nine items (assets) are excluded from the analysis to avoid systematic errors and random errors. The results show that districts Bhimber and Mirpur have achieved the highest average asset scores, which are 0.62 and 0.64 respectively. The score of the Gini-coefficient index and the Palma ratio analyses shows that the asset distribution in the districts Neelum and Haveli are highly unequal. The Gini-coefficient is highly responsive to midpoint distribution while the Palma ratio concentrates more on top and bottom distribution, and it ignores the middle 50 percent from the analysis. Interestingly, both approaches have produced similar district rank ordering because we have adopted a systematic process for construct validity and reliability to minimize measurement errors.