Business Cycles

- Modified: Jan 31st, 2023

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
Leading: Deviations from trend move with GDP but the peaks and troughs happen slightly before the peaks and troughs in GDP
Coincident: Deviations from trend move with GDP, but are neither leading nor lagging.