Wealth Inequality

Structural Inequality

Inequality that results from laws and their application is known as structural inequality. Only by changing laws can structural inequality be changed. For example, in societies in which women are treated by law as the possession of men, structural gender-based inequality will exist so long as the laws do, and these will not be changed and effectively policed until there is a consensus in society to do so.

Statistics show that inequality rose through the 1990s and early years of the 21st century in a number of different countries, notably the United States. One important cause of this inequality has been the delinking of executive pay from corporate performance, which has led to very high and unjustifiable increases in executive compensation. At the same time, unskilled labor migration has been encouraged to a sufficient extent to depress wage rates at the lower end. Corporations have also used outsourcing for their own benefit, thereby increasing inequality.

In China, meanwhile, inequality has resulted from the growth of incomes for executives and businesspeople in the coastal areas, where economic growth is high, while change is very slow in rural areas. As in other countries, this has led to extensive amounts of internal migration that results in overcrowding of cities, in which public health and safety services are inadequate. Internal migration is associated with family breakdown, risk-taking behavior, and lower levels of educational achievement for the children of migrants.

Regional inequality may be addressed, therefore, through programs of regional economic development. A progressive taxation system helps to redistribute wealth to the less well-off sections of society and helps [Page 1160]to reduce inequality. Regressive tax systems or reductions in taxes for the wealthy increase inequality and can reduce the health of society as a whole.

The Gini Coefficient

There are various methods for calculating wealth inequality, and of these perhaps the most well-known and commonly used is the Gini coefficient, named after the Italian statistician Corrado Gini (1884–1965). The Gini coefficient ranges from 0, which would determine a theoretical state of perfect equality, to 1, which would represent a state of theoretical perfect inequality. Studies of Gini coefficients across states and through time suggest a positive correlation between inequality and civil war, poor health, or family breakdown, among other undesirable effects.

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