As has been witnessed in other European cities, the recent experience of the Madrid Metropolitan Area shows that it is possible to reverse declining historical trends in public transport ridership. This was achieved through an integrated fare scheme based on low-cost travel tickets and improve- ments in the quality of service. Therefore, adequate planning of futurepublic transport facilities requires two basic inputs: (a) reliable predictions of transport demand, and (b) efficient estimation of the users’ response to changes in prices and the characteristics of the service. This paper aims at providing these two inputs for the public transport system of the Madrid Metropolitan Area. Using recent monthly data, we address the problem of elasticities estimation and forecasting for a large number of tickets that are subject to the types of multiple, complex calendar effects, and superimposition of outliers, changing supply service, and changing seasonality. Two different approaches have been used to deal with these issues. The first one is a causal model based on a transfer function dynamic model that allows the incorporation of intervention and exogenous vari- ables in a flexible way. The other is the Dynamic Harmonic Regression model, a new variant of unobserved component models with time varying parameters that allows the adaptability of the trend and the seasonal com- ponents as soon as the new information becomes available.
Both methodologies are capable of dealing with the nonstationarity and strong seasonality features that characterise the database. Additionally, all series exhibit the presence of important outliers which considerably compli- cates the forecasting exercise. The estimation results indicate that the effects of these input variables have the expected signs and are highly significant from a quantitative point of view. However, their effects change consider- ably among different type of tickets and transport modes.
The historical public transport fares scheme of the Madrid Metropolitan Area provides considerable help when designing a causal scheme of expected price- and cross-elasticities among different type of tickets. With the exception of travel cards, the remaining tickets show significant negative own-price elasticities. The range of estimated values, however, indicates large differences among estimates with the 10-trip metro tickets showing the highest sensitivity to price increases. We have also found evidence of moderate estimated cross-elasticities, in particular between bus and Metro 10-trip tickets and travel cards. Nevertheless, the high subsidies that charac- terise the Madrid public transport system make these results discouraging for the prospects of achieving optimal pricing of public transport. In spite of this, however, our empirical results indicate that there is room for an alternative pricing policy (based on moderate price increases of travel cards while main- taining single- and 10-ride prices nearly constant) aimed at having positive effects on demand while minimising the negative effects on revenues.
As regards forecasting results, we have obtained two sets of twelve periods’ ahead forecasts for the six transport variables analysed in this paper for 2000 and 2001. The forecasting period is particularly difficult given the important increase of the Metro supply services just before this period. This meant a mixture of effects that affected not only totaldemand but also temporary passenger shifts between different modes. To avoid evaluation of different forecasting techniques depending upon the choice of a particular accuracy measure, the models’ forecasting perfor- mance has been appraised according to several accuracy criteria. Although no model entirely dominates the other for all the variables and forecasting horizons, the general predictive results indicate that both models are good alternatives in providing reliable forecasts. However, analysing the changes in seasonal patterns as well as exploring forecast combinations should be areas of important future research.