Airport Activity as a Predictor of Regional Economic Development

Included are all the R-markdown files that were exported as Word documents.

Goal

I developed a model to predict a city’s economic growth given its airport’s activity.

Data

All of the airport-level datasets were sourced from the Government of Canada’s Open Data Portal and were structured. The economic-level datasets were sourced from a third-party and were unstructured.

• Total number of aircraft movements per city (monthly)

• Airport activity per city (yearly), i.e., the number of passengers departing and arriving at an airport

• Median income per city (yearly)

• Number of employed persons per city in thousands (yearly)

• GDP of Canadian Cities (yearly)

Method

1. Clean the datasets and select attributes in R.
2. Apply multiple linear regressions in R and check the strength of the model.
3. Visualize the results in R and Excel.

Results

It was determined that in major Canadian cities, with all else equal, a 10% increase in passenger activity produces a 1%-4% increase in individual median income and a 0.5%-1% increase in employment.