The Bureau of Transportation Statistics (BTS) developed a model that allows for the forecast of the preliminary estimates for enplanements. The model develops an analysis and obtains a sense of the appropriateness of simpler linear regression, correlations were calculated between the national TSA inspection checks and the full, domestic, and international T100 market data.

Passenger enplanement numbers are collected monthly and published 3-4 months after the month ends. Transportation Security Administration (TSA) checkpoint screening is closely linked to passenger enplanement. TSA data is available a day after the month has ended, making it a suitable proxy for predicting enplanement numbers.

The simple linear regression model, with seasonality, was tested for all three T100 market datasets. For each data set, seasonality was assessed from the residuals of the simple linear regression model. Using this method, it identifies a strong correlation between TSA screen data and passenger enplanements which, identified a regression model would be a suitable modeling methodology.

The result of the model provides preliminary estimates for passenger enplanements, with high predictability and confidence in the estimates for 3 to 12 months in advance.

• T100 Segment: T100 Segment Preliminary Estimates | BTS Data Inventory T100 Market:
• T100 Market Preliminary Estimates | BTS Data Inventory