what is the major factor that would help in eliminating inequality
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Answer:
‘Natural’ causes of inequality
In an attempt to shed some light on which forces or conditions in the economy affect income inequality, we analyzed how a variety of socioeconomic variables affect the differences between each country’s Gini coefficient.
Initially we looked at how just one variable, age, affected the Gini of 30 countries. We expanded this to 53 relatively developed countries in various continents and 10 variables.
Our analysis showed that the median age of the population appears to have a significant influence on the differences in Gini coefficients, which varies inversely with the median age of the population. That is, older populations are less unequal (have a lower Gini) than younger ones, probably because as individuals age there is less disparity in their incomes. Retirement from productive endeavors is an obvious leveler of income differences. In addition, the incentive to pursue ever-higher incomes diminishes as workers approach retirement, producing the age-earnings curve.
Age is one of the ways income disparity can be attributed to a “natural” cause, thus representing a challenge to policy makers hoping to reduce inequality, and was the most significant variable in our analysis.
Similarly, our analysis shows that greater GDP growth and the percentage of the population employed in the agriculture sector are negatively related to the Gini. That is, countries with higher economic growth or a greater the share of its workers engaged in agriculture have less inequality.
For the most part, the measures identified above can generally be attributed to environmental forces and normal human behavior and are thereby not easily affected by short-term policy. They explain most of the variation among countries in the Gini coefficient. In other words, these findings suggest most inequality is more or less hardwired into our societies and only long-term trends (in policy, demographics, etc.) can affect them.
Where policy can play a role
Our analysis did find that some variables more directly linked to short-term policy choices played a role in explaining the Gini differences among countries.
Among these, the variable that influenced inequality the most was tax policy. In particular, the higher the overall tax rate in terms of revenues as a share of GDP, the lower the Gini. This may help explain why countries like Switzerland and France, which have high tax rates on the wealthy, suffer from less income inequality than the U.S., which has relatively low ones.
But taxation can be a double-edged sword, as taxes may act as a deterrent to productive (income and job creation) behavior. Fortunately, it’s possible to design tax policy that encourages economic growth in the short term while raising government revenue in the long term.
Another policy variable that affects the Gini coefficient is investment. Our analysis showed that increasing investment in productive assets leads to greater income inequality. This seemingly counterintuitive result arises because investment expenditures produce GDP growth at a lag while detracting from current consumption.
The last significant variable we considered is unemployment, which, as you’d expect, leads to more income equality. Although this finding is intuitive (as were our results on aging and growth), it is comforting to learn that statistical analysis confirms what common sense dictates.
Four variables we tested – inflation, years of schooling, GDP per capita and government deficits (as a percent of GDP) – had no measurable influence on income inequality.
Together, these factors explain roughly three-quarters of the differences in the Gini among the 53 countries in our review. In other words, variables we didn’t consider are responsible for a quarter of the deviation in income inequality in these countries. Understanding what those factors are will require further review.
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