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# **5. Demand forecasting in practice**

This section describes some case studies to illustrate the ways in which regulators, privatizers or planners have used the various demand forecasting described in the annex. It covers examples in which demand forecasting is used in activities which were privatizes as is the case for the Mexican suburban rail and the French toll roads. It also presents cases in which the public sector is still very much a key players as for the Spanish airports and the Belgian ports. In some instances, the experience with the use of modem demand forecatsing techniques is too recent to be able to do _a post-mortem_ comparing forecast and realized but since to the extent that they signal a trend characteristic of their specific sector, the exemples are quite informative. To the extent possible, the process and the degree of use of the information generating by the forecasting teams is discussed to illustrate the importance of the political decision to use the information for its relevance in the regulatory process.

# **_5.1 Mexico_** _City_ **_Commuter Train Project'_**<sup>**_9_**</sup>

This case is a textbook approach to demand forecasting.<sup>20</sup> It involves a decision in 1998 to invest in a commuter rail line to reduce pollution and congestion in Mexico city. Over 70 percent of the Mexico city transportation market traveled exclusively by road in 1994 when out of 20.5 million total weekday trips, buses accounted for 48%, cars 24% and metro 2%. Two or more public modes were used by 22% of the travelers. The main concern was to forecast how effective the commuter rail would be in capturing a sufficient share of this market. The demand projections would be used to increases the transparency of the prospects to any potential private investor but also to develop the capital and operating program for the commuter service, the financial analysis which would eventually be used by the regulator to estimate the requirements of financial support by the government.

The data available was reasonable although not perfect. The forecasters could rely on a 1994 survey of trips origin and destinations in Mexico city conducted by the Mexican National Institute of Statistics. They also has estimated trip growth rates to allow an update of the matrix. These growth rates (1.2% average annual from 1994-2030) is based on population growth estimates and land use trends. Data on the characteristics (trip time, costs, frequency, reliability...) of bus, commuter rail and metro travel in Mexico collected by a local consulting firm and a couple of traffic counts at key locations in the corridor. The forecaster then conducted a stated preference survey of potential commuter rail users to estimate users preferences for alternative public transportation modes. The demand is based on diversion from other modes of public transportation only (buses and metro). It excludes diversion from cars (to get a lower bound) and ignores induced demand as well. The results are then introduced into a model generating trip volumes for the commuter rail. It includes up to 2030 estimates of annual passenger demand, annual passenger-kms, demand on weekdays and weekends and boarding and Based on: Mercer Management Consulting (1998), "Commuter Rail Demand Study for the Buenavista-Huehuetoca Line", prepared for the Mexican Communications and Transport Secretariat

> **20** Another, less 'textbooks", set of very relevant illustrations is provided by D. Pearmain (2000), "The measurement of users' willingness to pay for improved rail facilities", in Ortuzar (2000), op. Cit.. It includes a brief survey of the UK experience with WTP methods and a couple of examples illustrating some of the implementation difficulties of the stated preference method in the context of a variety of decisions potentially important to regulators such as the extent which investment decisions in facilities impact on revenues.