Impact of September 11 on Air Travel in the United States. The Research and Innovative Technology Administration’s Bureau of Transportation Statistics conducted a study to evaluate the impact of the September 11, 2001 terrorist attack on US transportation. The 2006 study report and the data can be found at https://www.bts.gov/archive/publications/estimated_impacts_of_9_11_on_us_travel/index. The goal of the study was stated as follows:

The purpose of this study is to provide a greater understanding of the passenger travel behavior patterns of persons making long distance trips before and after 9/11.

The report analyzes monthly passenger movement data between January 1990 and May 2004. Data on three monthly time series are given in file Sept11Travel.csv for this period: (1) actual airline revenue passenger miles (Air), (2) rail passenger miles (Rail), and (3) vehicle miles traveled (Car). To assess the impact of September 11, BTS took the following approach: using data before September 11, they forecasted future data (under the assumption of no terrorist attack). Then, they compared the forecasted series with the actual data to assess the impact of the event. Our first step, therefore, is to split each of the time series into two parts: pre- and post-September 11. We now concentrate only on the earlier time series.

a. Create a time plot for the pre-event AIR time series. What time series components appear from the plot? 

b. Figure 19 . 14 shows a time plot of the seasonally-adjusted pre-September-11 AIR series. Which of the following smoothing methods would be adequate for forecasting this seasonally-adjusted series?

• Moving average (with what window width?)

• Simple exponential smoothing

• Double exponential smoothing

• Holt-Winters exponential smoothing

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Seasonally adjusted air revenue passenger miles (Sbillions) Jan-90 Jan-91 Jan-92 Jan-93 Jan-941 Jan-95 Jan-96 Jan-97 Jan-98- Jan-99- Jan-00 Month Jan-01