Regional Disparity and Convergence in Human Development in India

Abstract

India has been characterized by wide regional variation in the level of human development across states. By constructing a human development index (HDI) using Euclidean distance, this chapter makes an attempt to evaluate the trend and level of inequality in human development across the states of India with respect to 11 socioeconomic indicators. The test of convergence of composite human development index (CHDI) as well as its indicators reveals that the Indian states are converging in terms of the level of human development. Interestingly, polarization in the level of human development shows a tendency to increase along with reducing trend in inequality especially during the period 1981–2001. It is expected that a targeted level of human development can reduce the extent of polarization and thus, can bring out a balanced human development in Indian states.

Appendix

5A1: A note on Euclidean distance

The Euclidean distance is measured by the following index

$$ {\text{d}}({{\text{u,v}}}) = \sqrt {{{({{a_1}-{b_1}})}^2} + {{({{a_2}-{b_2}})}^2} + \ldots. + {{({{a_n}-{b_n}})}^2}}, $$

where ${\sigma_i}$ is the standard deviation of the ${x_i}$ over the sample set. The distance function in Euclidean space is defined as follows:

Let point u be the n tuple (a₁, a₂, …., a_n) and point v be the n tuple (b_1, b₂, …, b_n) then the Euclidean distance function is

$$ {\text{d}}({{\text{u,v}}}) = \sqrt {{{({{a_1}-{b_1}})}^2} + {{({{a_2}-{b_2}})}^2} + \ldots. + {{({{a_n}-{b_n}})}^2}}, $$

where the square root is taken to be positive (Chiang 2004).