First-Difference Transformation is a technique used in time series and panel data analysis to eliminate unit roots and address non-stationarity by transforming the data into differences between consecutive observations. This method is particularly useful for reducing autocorrelation and revealing underlying trends or relationships by focusing on changes rather than absolute levels of the data.