On today's exercise, I performed a merge operation to detect which quarters of a particular year fall into recession periods using merge_asof().
I merged quarterly GDP values with recession start-end dates to automatically label each quarter as either recession or growth.
Then I plotted the GDP values, where red bars represent recession quarters and green bars represent normal growth periods.
This is a fundamental technique in economics and finance called period tagging.
From the graph, we see that:
The GDP is steadily rising over the years; that is normal for the US economy.
The red cluster in the middle shows the 1981–1982 recession.
During the red period, GDP growth slows down and some quarters flatten (stop growing) which makes the economy become unstable.
The perfect tool for time-based tagging is merge_asof(). Why?
Because GDP is quarterly (every 3 months) and recession dates are irregular (may start on any day). So merge_asof() provides the solution to the big question 👉 “For each GDP quarter, what was the latest known economic status at or before that date?”
merge_asof() prevents future leakage.
It also respects real world time order and it is EXACTLY how economists tag recession periods.
This reflects how professionals actually analyze the economy behind the scenes:
Identify when recessions happened
Tag economic indicators (GDP, inflation, unemployment) with recession periods
Compare how these indicators behave during recessions vs expansions
Build forecasting models for future downturns
Study how markets react during recessions
The exercise shows how powerful time-aware merging is, and why tools like merge_asof() are essential when working with real-world economic or financial datasets.
I hope you enjoyed reading this?! Have a wonderful weekend 😊
-SP
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