This study applies wavelet coherency analysis to examine the relationship between the U.S. per capita real GDP and six income inequality measures over the period 1917 to 2012. Wavelet analysis allows the simultaneous examination of correlation and causality between the two series in both the time and frequency domains. Our findings provide robust evidence of positive correlation between the growth and inequality across frequencies. Yet, directions of causality vary across frequencies and evolve with time. Evidence that inequality leads per capita real GDP at both high- and low-frequencies exists for the Top 1 and 10% measures of inequality with little evidence that real GDP per capita leads inequality. In the time-domain, the time-varying nature of long-run causalities implies structural changes in the two series. These findings provide a more thorough picture of the relationship between the U.S. per capita real GDP and inequality measures over time and frequency, suggesting important implications for policy makers.