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Some countries, in some periods, experience economic growth without increasing happiness. The Easterlin paradox is a finding in happiness economics formulated in 1974 by Richard Easterlin, then professor of economics at the University of Pennsylvania, and the first economist to study happiness data. [1]
The economics of happiness or happiness economics is the theoretical, qualitative and quantitative study of happiness and quality of life, including positive and negative affects, well-being, [1] life satisfaction and related concepts – typically tying economics more closely than usual with other social sciences, like sociology and psychology, as well as physical health.
Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
Much criticism of the index has been due to commentators incorrectly understanding it to be a measure of personal happiness, when it is in fact a measure of the "happiness" of the planet. In other words, it is a measure of the ecological efficiency at supporting well-being.
Third, a zero Pearson product-moment correlation coefficient does not necessarily mean independence, because only the two first moments are considered. For example, = (y ≠ 0) will lead to Pearson correlation coefficient of zero, which is arguably misleading. [2]
A version of this story appeared in CNN Business’ Nightcap newsletter. To get it in your inbox, sign up for free, here. Money can’t buy happiness, of course. Of course. But it can really ...
Free add-on to STATA to compute inequality and poverty measures; Free Online Software (Calculator) computes the Gini Coefficient, plots the Lorenz curve, and computes many other measures of concentration for any dataset; Free Calculator: Online and downloadable scripts (Python and Lua) for Atkinson, Gini, and Hoover inequalities
Coefficient of variation (CV) used as a measure of income inequality is conducted by dividing the standard deviation of the income (square root of the variance of the incomes) by the mean of income. Coefficient of variation will be therefore lower in countries with smaller standard deviations implying more equal income distribution.