Having documented the rising trend of inequality in India, it is natural to ask why this matters. However, the pace of such increase inequality was probably not anticipated. Although the rising tide of growth has lifted boats for most, but it also caused the movement of society towards inequality in less than 10 years. Inequality has been ranked among the most serious socioeconomic problems in India.
First, the most publicized impact of rising inequality is on social cohesion and political stability. In a recent study, it has been found that migrants are becoming increasingly dissatisfied with local governments. This lack of confidence and trust is likely to breed crimes against urban residents and the public, and even render government policies ineffective. On the other hand, repeated reports of conflicts between property developers and dispossessed farmers, and between factory employers and their migrant workers reflect the uneasiness and anger of the deprived.
Second, rising inequality means those at the bottom of society cannot afford investment, whether financial or in human capital. Traditionally, gaining entry into universities represents a major avenue for many poor households to step out of poverty. Prohibitive fees for entering quality schools plus intensifying competition for entrance into colleges prevent many poor households from properly educating their children. This is detrimental not only to poverty reduction but also to national prosperity, as education and human capital formation are known to have spill over effects.
Third, and related to the second impact, rising inequality is found to adversely affect economic growth in India. Apart from the inability of the poor to invest, high inequality exerts pressure for redistribution, which might distort incentive mechanisms in the economy and comes with considerable transaction cost. High levels of inequality might also diminish growth when the wealthy can manage to tilt policies in their favor. To analyze the impact of
growth on inequality and vice versa, a polynomial was introduce in inverse-lag model in a system of equations framework, enabling simultaneous identification and measurement of these impacts, under any time horizon: short run, medium run or long-run. It was found that inequality is harmful to growth no matter what time horizon is considered and that the growth–inequality relationship is nonlinear.
Fourth, it is well-known that rising inequality hinders poverty reduction. On the one hand, the impact of growth on poverty reduction is smaller when inequality is high, even in the absence of worsening distribution. On the other hand, rising inequality offsets the poverty-reducing impacts of growth.