The article introduces a new way to analyze relationships between economic variables using quantile cross-spectral analysis. This method helps uncover hidden connections that traditional analysis methods miss. By studying how variables interact at different levels and frequencies, researchers can better understand the complex nature of economic time series. The study presents new estimators to capture these relationships, discusses their properties, and shows how they can be applied to real-world data, like stock market returns.