Today, we’re planning to do clustering analysis to discover distinct phases within the economy. This is hard yet accessible approach will allow us to group similar periods in economic indicators, painting a clearer picture of our economic cycles.
Clustering is like grouping different moments in time based on their economic characteristics. Imagine categorizing years or months when the economy showed similar trends in unemployment, hotel occupancy, and housing prices. This method can help us identify periods of growth, stability, or recession in a more structured manner.
By applying clustering techniques to our dataset, we can uncover patterns that might not be immediately evident. It’s like finding hidden stories in the data – stories about when and how our economy thrived or faced challenges. This method goes beyond looking at individual indicators by revealing how they interact over time.
We plan to use a selection of key economic indicators for this analysis. The idea is to see how these indicators cluster together at different times, giving us insight into the economic conditions of those periods. We’ll be looking for correlations and patterns that define distinct economic phases.å