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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).

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.

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.

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.

The primary focus of this study is to examine the distributional consequences of the widespread increase in prices. The fundamental question the study aims to address is whether the dynamics of income distribution due to higher inflation differ in the short term compared to the long run.

The authors estimated a panel-data model (fixed effects) using inequality and inflation data available at a high frequency, i.e. on a quarterly basis for over 30 years, and found evidence that inflation causes rapid swings in income distribution.

The authors’ contribution to the literature lies in providing evidence that inflation rapidly causes swings in income distribution, even after controlling for the state of the economy. The authors also demonstrate that the magnitude and direction of the effect of inflation on income inequality depend on whether the initial inflation rate is below or above the Federal Reserve’s target of 2%.

To the best of the authors’ knowledge, the authors are the first to emphasize that the targets set by central banks can drive the strength and direction of the relationship between inflation and income inequality.