How can you interpret ACF and PACF plots in time series analysis?
Time series analysis is a powerful tool for understanding and forecasting the behavior of economic variables over time. However, to apply appropriate models and methods, you need to check the properties and patterns of your data. One way to do that is by using autocorrelation function (ACF) and partial autocorrelation function (PACF) plots. These plots can help you identify the degree and nature of dependence among observations, as well as the possible order and type of time series models that fit your data.