1887

Divided We Stand

Why Inequality Keeps Rising

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In the three decades to the recent economic downturn, wage gaps widened and household income inequality  as measured by GINI increased in a large majority of OECD countries. This occurred even when countries were going through a period of sustained economic and employment growth. This report analyses the major underlying forces behind these developments. It examines to which extent economic globalisation, skill-biased technological progress and institutional and regulatory reforms have had an impact on the distribution of earnings. The report further provides evidence of how changes in family formation and household structures have altered household earnings and income inequality. And it documents how tax and benefit systems have changed in the ways they redistribute household incomes. The report discusses which policies are most promising to counter increases in inequalities and how the policy mix can be adjusted when public budgets are under strain.

"Analyses rely on simple statistical techniques that are accessible to a large readership... the graphic and charts are of great help to gain a quick visual grasp of the various issues addressed."

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Hours Worked, Self-Employment and Joblessness as Ingredients of Earnings Inequality

This chapter broadens the focus from wage inequality among full-time workers to earnings inequality among all workers. It accounts for the effects of adding parttime workers and the self-employed and includes both groups in analyses of levels of and trends in the distribution of earnings. The chapter first identifies the contribution of self-employment and its distributional patterns to inequality of annual earnings. It then examines whether trends in “prices”, i.e. trends in hourly wage rates, have a lesser or greater impact on levels of and changes in inequality than trends in “quantities”, i.e. trends in hours worked. In a second step, the chapter broadens the focus to the whole working-age population and analyses to what extent shifts in joblessness affect estimates of an “overall” earnings distribution, i.e. including workers and the jobless.

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