A new measure of multidimensional human deprivation index (MHDI) across 24 states (over 4 time points corresponding to NFHS 1, 2, 3 and 4) is suggested here using principal component analysis (PCA). We observe that our weighted MHDI is found to be consistent with the Human Poverty Index (HPI) and the Multidimensional Poverty Index (MPI) introduced by UNDP in 1997 and 2010, respectively. Though most of the states in India have been experiencing a decline of the incidence of MHDI, but club convergence clearly proves that five major states such as Rajasthan, Madhya Pradesh, Bihar, Uttar Pradesh and Odisha are found consistently to be stable in the higher group of MHDI. Lagged MHDI, human capital investments along with availability of infrastructure are the underlying factors of differential MHDI across states. Therefore, allocation of grants should consider these issues of chronic MHDI found in five major states in order to ensure regional balance, equity and social justice in our federal structure.

在这里，建议使用主成分分析（PCA）对24个州（在4个时间点对应于NFHS 1、2、3和4）上的多维人类剥夺指数（MHDI）进行新的测量。我们观察到，我们加权的MHDI被发现分别与开发计划署分别于1997年和2010年引入的人类贫困指数（HPI）和多维贫困指数（MPI）一致。尽管印度大多数州的MHDI发病率都在下降，但俱乐部趋同清楚地证明，拉贾斯坦邦，中央邦，比哈尔邦，北方邦和奥里萨邦等五个主要州在上层人群中一直保持稳定MHDI。落后的MHDI，人力资本投资以及基础设施的可用性是各州MHDI差异的根本因素。所以，