Time-series analysis of the air traffic on three European countries (Spain, Germany and Italy).
Our intention was to obtain highly-interpretable models to explain the dynamics of the air traffic on each country based on different explanatory variables such as the economic activity, the price fluctuations, the competition/interaction with the railway traffic, etc. The analysis, involved dealing with some aspects that are inherent to time-series such as seasonality and autocorrelation. Because of our interpretability focus, we used time-series linear regressions and a dynamic regressions with ARIMA errors instead of more complex or opaque alternatives. Our approach was effective in achieving well-fitting and understandable models.
This project was part of the Time-Series Analysis for Business, Economic and Financial Data course of my master's degree.