- Modified: Sep 20th, 2022

The Assumption is that the data can be decomposed like so:

$\text{data} = \text{trend} + \text{seasonal} + \text{cyclical}$
• Trend = smoothed out so we only see long-term patterns
• Seasonal component = predictable fluctations that happen on a yearly cycle
• Examples:
• Farming: weather affects output of crops (harvest) and determines when you want to hire labor to work on those fields
• Holidays: People consume more at Christmas time, they consume more travel services if everyone is visiting their family at the same time, etc.
• For annual data, seasonal adjustment doesn’t do anything.
• Cyclical component = The part of the data which can’t be explained by long-term patterns and which doesn’t follow some consistent predictable pattern.

## ¶ The Boom and Bust Cycle

Peak
Economic activity reaches a high point and begins to decline.
Trough
Economic activity reaches a low point and begins to increase again.
Recession
Going from a Peak to a Trough. A significant drop in economic activity that affects the entire economy.
Boom/Expansion
Going from a trough to a peak. Happens whenever there isn’t a recession.

Procyclical
If the cyclical component of a variable is positively correlated with the cyclical component of GDP, then we say that this variable is Procyclical
Countercyclical
If the cyclical component of a variable is negatively correlated with the cyclical component of GDP, then we say that this variable is Countercyclical
Acyclical
If no correlation between cyclical component of a variable and the cyclical component of GDP, then the variable is Acyclical
Lagging
Deviations from trend move with GDP but the peaks and troughs happen slightly after the peaks and troughs in GDP