The article investigates whether seasonal and non-seasonal changes in data are widespread or specific. By using a common factor model, the researchers can separate seasonal and non-seasonal changes in a series. They developed a method to accurately estimate the model without prior knowledge of the data's seasonal properties. Through simulations and real-world data on exchange rates and consumer prices, they were able to detect and distinguish the sources of non-stationarity in the data.