It is now an accepted stylised fact that increase in happiness level in any country is not commensurate with growth in income, a puzzle known as Easterlin Paradox. This paper analyses the income-happiness relationship in India and tries to explain the flat happiness response to income change in terms of rising income inequality. Income growth propels inequality and so also inequality in well-being. Empirically the effects of income inequality, absolute income, relative income, rank position and social capital indices are analysed using World Value Survey data for 12 states of India over 24 years from 1990 to 2014. As the variation in the 10-point scale measure of life satisfaction level is narrow, an recentered influence function (RIF) regression of variance and Gini of life satisfaction are estimated. The life satisfaction inequality is decomposed into composition and coefficients effects using Blinder–Oaxaca (B–O) decomposition method. The estimated RIF coefficients reveal significant effects on life satisfaction inequality of various income measures and social capital indices. The B–O decomposition shows that the functional relationship between material aspirations and life satisfaction, contribute significantly to rising life satisfaction inequality relative to changes over time in happiness influencing factors. Reducing income inequality and improving trust, sociability, health, education and employment over time and space could reduce life satisfaction inequality and improve happiness level in India.
Most often the social comparison or relative income hypothesis has been used as an explanation for the lack of systematic relationship between income and happiness, using the ordered probit regression method. The identification of relevant reference group and the estimation of the differential effects of comparison income have been controversial. To overcome these twin issues, this paper uses an ordinal comparison income approach based on rich/poor dichotomy and rank income. The rank income of an individual is defined as his relative position in the income distribution within the reference group and the average income of the reference group is used to define the rich/poor classification. The differential effects of ordinal incomes across life satisfaction distribution is estimated by the panel fixed effects ordered profit regression model using the WVS data for India. The estimated results show that ordinal income comparison, rather than cardinal average reference income, is a better predictor of life satisfaction levels. Raising income level is relatively important for less satisfied people while increasing rank status is important for highly satisfied people in India.
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