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Purpose: Existing empirical evidence suggests that episodes of financial stress (crises) can act as driver of growth of inequality. Consequently, in this study, the authors explore the time-varying predictive power of an index of financial stress for growth in income (and consumption) inequality in the UK. The authors focus on the UK since income (and consumption) inequality data are available at a high frequency, i.e. on a quarterly basis for over 40 years (June, 1975 to March, 2016). Design/methodology/approach: The authors use Wang and Rossi's approach to analyze the time-varying impact of financial stress on inequality. Hence, the method provides a more appropriate inference of the effect rather than a constant parameter Granger causality method. Besides, understandably, the time-varying approach helps to depict the time-variation in the strength of predictability of financial stress on inequality. Findings: This study's findings point that financial distress correspond to subsequent increases in inequality, with the index of financial stress containing important information in predicting growth in income inequality for both in and out-of-sample periods. Interestingly, the strength of the in-sample predictive power is high post the period of the global financial crisis, as was observed in the early part of the sample. The authors believe these findings highlight an important role of financial stress for inequality – an area of investigation that has in general remained untouched. Originality/value: Accurate prediction of inequality at a higher frequency should be more relevant to policymakers in designing appropriate policies to circumvent the wide-ranging negative impacts of inequality, compared to when predictions are only available at the lower annual frequency. [ABSTRACT FROM AUTHOR]

In this paper, we analyze time-varying predictability of financial stress due to growth in income inequality of the United States (US) over the annual period of 1913 to 2016. In order to ensure that we remove the asset price effects on income inequality, and provide incorrect inferences regarding the impact on financial stress, we work with capital-gains excluded six alternative measures of top shares of pretax income and wages. We find that the top 10%, the top 10% to 5%, and the top 5% to 1% inequality growth rates tend to predict financial stress relatively better than the corresponding inequality growth rates associated with the top 1%, top 0.1%, and the top 0.01% of the income distribution. Moreover, all the six metrics of inequality growth is capable of predicting the heightened financial stress observed during the onset of the Great Depression and the same associated with the recent global financial crisis. Finally, our in-sample evidence of predictability tends to carry over to an out-of-sample forecasting exercise under four out of the six measures of inequality considered, and in particular for the broader measures of inequality – a result consistent with our in-sample analysis. [ABSTRACT FROM AUTHOR]

This paper uses OLS regressions to understand the relationship between household debt, income inequality, and economic growth in the United States. For robustness we use two different measures of income inequality. The results show that, for the period 2003–2012, there is statistical evidence that increases in household debt are associated with lower levels of economic growth and higher rates of unemployment. In addition, we uncover evidence that high growth rates in household debt are associated with negative growth in income inequality, likely because debt caused economic growth to slow, diminishing the returns of top earners. [ABSTRACT FROM AUTHOR]