Lagged variables are past values of a variable used in statistical models to analyze relationships over time. For example, in a study examining the impact of economic growth on unemployment rates, researchers might include the unemployment rate from the previous year as a lagged variable. This helps to capture the effect of past conditions on current outcomes. Using lagged variables can improve the accuracy of predictions and provide insights into trends. They are commonly used in time series analysis, where understanding how past events influence present behavior is crucial. This approach is valuable in fields like economics, finance, and social sciences.