Business cycles and future transport demand: how use of a leading indicator improves forecasts of rail passenger transport

Document Type

Conference Paper

Publication Date


Subject Area

mode - rail, place - europe, planning - travel demand management, ridership - demand, ridership - modelling


forecasting model, passenger transport demand, modelling, ridership demand


Whoever can predict the future with certainty has the world at his/her feet. After all, reliable forecasts are highly important to policy makers, investors and companies. Netherlands Railways (NS) employs various models to forecast future passenger transport demand, such as the so-called Q6 Plus model that plays an important role in short-term forecasts (up to two years in advance). This new Q6 Plus model combines trend analysis and extrapolation with so-called leading indicators: variables and sectors that are running ahead of business cycles. Forecasts derived from the Q6 Plus model are used to determine marketing policy and the deployment of rolling stock in particular. A more accurate prediction of the rolling stock requirement implies lower costs and increased customer satisfaction, which has a positive effect on revenues. The new forecasting model uses three different regression models, each with their own speciality. The first model makes short-term forecasts of passenger kilometres (six months in advance). The second model provides predictions for the somewhat longer term (up to two years in advance). The third model, finally, is specialized in predicting turning points in passenger kilometres for the entire prediction period. The Q6 Plus model successfully combines the strong points of these three regression models: the Q6 Plus model significantly lowered the prediction error in comparison with the existing trend extrapolation model.


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