In 2008, the world entered the worst recession since the Great Depression of the 1930s. Of course, many people lost their jobs and houses while…

In 2008, the world entered the worst recession since the Great Depression of the 1930s. Of course, many people lost their jobs and houses while others became uncertain about their financial future. Use the theory of supply and demand to predict the effect the recession would have on airline demand (the willingness and ability of people to purchase airline tickets), supply (the willingness and ability of airlines to provide flights), and price (the average price of an airline ticket).

Data Source

The federal government collects and makes an immense amount of data on the US economy available to the public, including large airline datasets. Having made your predictions or hypotheses, use the US airline industry data from the US Bureau of Transportation Statistics (BTS) to see if the industry reacted as you expected.

To obtain the data to test your predictions (hypotheses), find a BTS customizable data table following these steps: 1) Google “Bureau of Transportation Statistics”, 2) use the search box for “Air Traffic”, 3) select “U.S. Air Carrier Traffic Statistics” which will return a customizable table. (Note: The BTS occasionally changes the presentation of the data which affects the steps needed to find data. It may be necessary to modify this search slightly.)

Customize your data by selecting:

  1. From 2007 until the end of the recession or to an endpoint of your interest
  2. Domestic
  3. Scheduled
  4. Passengers, then select the statistics of interest (scroll to the bottom for selection criteria).

Prices

Prices are, of course, another piece of this puzzle. BTS provides a table of national fares. To find these data, use the BTS search box for Air Fares. Locate National Level Fares Since 1995. Again, the BTS occasionally changes the database names and files, so you may need to modify this search.

Discussion

Post your findings and explain your initial predictions.

  • Would either the supply and/or demand curves shift?
  • What is the predicted effect on quantity supply and demanded and on average price?
  • Although not required, a graphical depiction would be helpful. Then discuss whether the data support your predictions. Graphs of the data are easily prepared in a spreadsheet. Again, these are not required but would be helpful.
  • A few airline terms will be helpful.
  • Airline supply is usually measured in Available Seat Miles (ASM).
  • Measures of demand are Revenue Passenger Miles (RPM) and Enplanements.
  • Passenger Load Factor is yet another indication of demand.
  • Should you ever wish to do more research, perhaps for the GCP, the BTS has all the airline statistics you will probably ever need.

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