Several statistical indicators exist for the measurement of economic inequality. They are mostly based on distribution moments or depend on few percentiles at the tails of the distribution, selected a priori. This work analyzes a recently proposed quantile-based income inequality indicator, the Quantile Ratio Index, which solely depends on quantiles and considers the whole distribution. A complete finite population estimation framework for this indicator is here proposed, that works for data collected with complex sampling design. In order to obtain a reliable measure, special attention is dedicated to the task of estimating quantiles, particularly when accounting for sampling weights. Simulations based on Italian EU-SILC 2017 data demonstrates that the proposed direct estimator has large accuracy, precision and robustness to outlying observations, if based on an appropriate choice of quantile estimator.