In this paper, we reassess the impact of inequality on growth, The majority of previous papers have employed (system) GMM estimation. However, recent simulation studies indicate that the problems of GMM when using non-stationary data such as GDP have been grossly underestimated in applied research. Concerning predetermined regressors such as inequality, GMM is outperformed by a simple least square dummy variable estimator. Additionally, new data have recently become available that not only double the sample size compared to most previous studies but that also address the substantial measurement issues that have plagued past research. Using these new data and an LSDV estimator, we provide an analysis that both accounts for the conditions where inequality is beneficial or detrimental to growth and distinguishes between market-driven inequality and redistribution. We show that there are situations where market inequality affects growth positively while redistribution is simultaneously beneficial.