Title: Inequality and growth in France: A wavelet analysis
Authors: Alessandro Pietropaoli - Cote d\'Azur University (France) [presenting]
Abstract: The relationship between inequality and growth is a traditional, but still unsolved puzzle in economics. In particular, the time horizon at which the relation is investigated plays a crucial role in shaping the empirical results. We focus on the case of France, for which historical data (1915-2016) on several inequality measures, GDP growth rates and a set of important covariates are now accessible. The availability of time series that go sufficiently far back allows us to exploit continuous wavelet tools to shed light on the time scale relation between income distribution and growth. By performing spectral analysis as a function of time, wavelet techniques are very well-suited for examining time-varying relationships across frequencies. We show that the relationship is particularly strong in the medium and in the long term, while weaker and quite unstable in the short run. Further, the lead/lag relationship cannot be taken for granted, since the leading variable tends to change over time and across frequencies. Finally, in the long run, when the association is particularly strong and significant, we find that the impact of unequal income distribution on growth turns out to be negative.