SUMMARY AND CONCLUSIONS

This chapter focused on a wealth of new inequality data that has grown in detail, form, and importance since 2000. In addition to LIS, which was the bedrock of work by

⁹¹ This conclusion seems to differ from what was discussed in Chapter 7, where the focus on the long-run relationship between top shares and Gini coefficients does not allow the weakening of such a relationship to be identified for the first decade of the twenty-first century.

Gottschalk and Smeeding (2000), OECD, EU-SILC, and a series of country trend data, maintained in part by Atkinson and Morelli (2012, 2014) and Brandolini and Smeeding (2008, 2009), have made a tremendous difference in what we know about levels and trends in inequality and poverty over the past 30 years. Importantly, a whole new set of WTID data has proliferated and offers long-term trends in inequality for tax units at the top of the distribution. All of these new data come with new complications and caveats, which were discussed in the previous sections. Despite these caveats, these data do allow us to make a few overall summarizing observations about levels and trends in poverty and inequality over the past 30 years.

The modest conclusions we draw here include the following:

1. Of 28 rich and MIC nations in the late 2000s, 17 nations successfully reached single-digit poverty rates (where between 5% and 10% of the country’s population are poor by the half-median relative poverty measure). But the range of poverty rates in rich nations alone varies by a factor of almost 4 and, when adding MICs, by a factor of 5. Hence one experiences a wide range of relative poverty rates in these nations. Our trend data suggest that progress against poverty was uneven and rare in rich nations over the past 20-30 years. Other than Mexico, relative poverty rates did not consistently decrease over the past 15-20 years in any of the nations we examine here.

2. We conclude that while there was little progress in reducing relative poverty in almost all the rich countries examined here over the past two or three decades (up to 2010), real living standards for the poor have changed over this same period. Anchored pov­erty is an increasingly useful concept to establish how upward and downward changes in real median incomes affect poverty differently from a solely relative measure. Anchored poverty decreased in almost all rich nations from the 1990s to 2007 because of rising living standards in most of the rich world up to that point. However, since the GR, increases in anchored poverty up to 2010 reduced some of the progress in real living standards that low-income households experienced over the preceding 15 years.

3. Inequality increased (almost) everywhere over the 1970-2010 period, with some flat­tening during the GR, although the longer-term rising trend continued. Small changes year to year may produce strong trends over a 20-30-year period. Long-term increases in the Gini coefficients, P90/P10 ratios, and S80/S20 ratios are evident for DHI calculated using household surveys and with top income shares calculated with tax data.

4. The cyclicality of some measures of inequality—particularly for top income shares— is demonstrated clearly in the trends calculated with the WTID. Recessions have depressed the incomes of the rich especially, but these incomes bounced back even stronger after the recessions of the last decades of the twentieth century. Preliminary evidence suggests the same pattern will likely hold for the GR.

5. The 1950-1980 period stands out as the “golden age” for labor and decreasing or sta­ble inequality in the rich western nations. Several additional nations now show a U-shaped pattern of inequality, with inequality increasing even more since the last look at this phenomenon 14 years ago (Gottschalk and Smeeding, 1997, 2000; OECD, 2011). The longer time series of the WTID shows an even stronger U shape in inequality trends in these data.

6. Cross-national inequality rankings in the most recent data largely look similar to how they appeared 15 or even 30 years ago. The English-speaking countries (led by the United States and the United Kingdom) are the most unequal, by most measures, and the Nordic countries are the least unequal. There have been some important changes to note as well. New data allow us to add Israel and South Africa to the list of the most unequal. Also, the distance between the most and least unequal among rich countries has diminished as inequality growth surged in some of the least unequal.

7. Increasingly, one has to examine capital income as well as earned income. Increasing income from capital is more concentrated at the top of the distribution, as seen in the WTID in many nations since the 1990s and through the GR.

8. Broad-based distribution measures increased most in the 1970s, 1980s, or 1990s (depending on the country) but rose less, and were sometimes stable, in the 2000s. Using top income shares, however, inequality seems to still be rising and shows no sign of having “peaked.” How long this pattern can continue is an open question.

9. The relentless increase in top income shares poses new challenges to the informative content of different indicators of income inequality. On the one hand, intrinsic lim­itations of existing household surveys do not capture the entirety of income accruing to the top income brackets. This suggests that conventional measures such as the Gini coefficient may be increasingly missing the actual extent of the change in income inequality. On the other hand, there is evidence suggesting that the relationship between Gini and top shares became weaker over the past decade, pointing to greater prudence in extrapolating any results based on the analysis of top income shares directly to the overall income distribution.

The future research agenda for empirical studies of inequality and poverty is quite rich and may provide the answers to many questions that are not clear at this point.

ACKNOWLEDGMENTS

The authors thank their organizations for support of this work. In particular, the authors especially thank David Chancellor and Dawn Duren of IRP for their assistance with graphs and manuscript preparation and Peter Frase for research assistance. The authors also thank Tony Atkinson, Francois Bourguignon, Michael Forster, Andrew Leigh, Max Roser, Stephen Jenkins, and the editors for helpful comments on an earlier draft and Andrea Brandolini for providing helpful inequality trend data. The authors, not their organizations, are responsible for all opinions in this chapter, as well as all errors of omission and commission.

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