Hansen's Method is a statistical approach used to estimate the parameters of a model based on observed data. It focuses on minimizing the difference between the observed values and the values predicted by the model. This method is particularly useful in fields like economics and engineering, where accurate predictions are essential for decision-making. The technique involves using iterative algorithms to refine the estimates until they converge on the best-fitting parameters. By applying Hansen's Method, researchers can improve the reliability of their models, leading to better insights and more informed conclusions in their respective studies.