Quantile regression and quantile treatment effect methods are valuable tools in econometrics for analyzing the economic impact of events and variables. These methods examine the effects of independent variables on continuous dependent variables. In economic history research, researchers commonly study measures such as human height, demographic data, economic growth, earnings, wages, and crop production. This paper reviews recent literature that utilizes quantile regression methods and provides an example based on height data from the 19th and 20th centuries.