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# _6.1 Before the study_

To begin with, it is generally useful to have look at the past trend of the type of trip the analyst is expected to forecast. Quite suprisingly, this can be a challenge as the quality of data available from transport ministries has tended to deteriorate over the years. Assuming that enough data can be collected, it it is generally not a good idea to stop there.It is worth finding out more about the economic context in which the transport project under regulatory scrutiny is operating. The national and international environment often have an impact of these projects. So do the development of alternative transport options which can be a complement or a substitute. This can help the regulator decide if a quick decision is necessary. In West Africa, Senegal, Mali, Ivory Coast and Guinee currently have a portfolio of competing rail and road projects for which the rate of return and hence the possibility of attracting private financing is directly related to the speed with which the governments willmake the decision. Demand will go and mostly be locked in the hands of the first movers. Many of the key decision makers have a hard time appreciating the importance of speed for the demand for their transport services because they are not paying enough attention to what their neighbourghs are doing. The surprising fact is that this information is relatively easily available to a regulator or a policymaker since most of these projects are generally government initiative and are quite widely publicized. Moreover, many of the transport service companies interested in these deals have at least preliminary forecast which can provide good insight on the real prospects of a proposed investment project. It may be worth for regulators to find out more of these and to have them audited independently. Finally, complementary industries such as aeronautic or car builders also make their own forecasts for obvious reasons. All these are useful in educating a regulator in an initial stage.

Once these indicators of trend or prospects are internalized, it is often useful to try to identify potential peak demand resulting from exceptional circumstances which may justify fast increases in capacity than these trends would require. A city trying to sell itself as an great host for conferences must have the supporting transport infrastructure to deal with associated peal demands. Tourists airports also face a strong seasonality in peak demand. How much of these peaks the government is willing to address through increases in capacity and how much by allowing occasional congestion is a local choice--and it may make sense for a government to live with occasional or even seasonal congestion problems rather than overinvesting under tight budget constraints. The fact is that the regulator must be aware of the relevance of these occasional demand shocks in its assessments of the performance of the operators. They will often have the option of considering the introduction congestion pricing. If demand is in fact very little sensitive to prices in peak periods, it may pay off not to adjust capacity and to rely on prices to deal with peak demand.

Next, the regulator must ensure that technology developments are not interfering with demand forecast. For instance, the appearance _offastferrys_ reduced the demand for conventional _ferrys_ and this could result in unexpected shifts in demand as well as in financial drama for the operators of conventional ferrys. In the crossing of the Channel bewteen France and the UK, the introduction of new fast boats has resulted in a loss of traffic for trains riding through the tunnel and contributed to the well publicized financial troubles encountered by the tunnel operators. Similarly, expansions in capacity can also influence demand. For instance, the introduction of _post panamax_ ships with a larger capacity to carry containers changed many investment decisions in ports since new technological constraints were appearing.

Finally, the regulator must look at its budget envelope. Most modern forecasting methods are quite expensive and to do a decent job, it is not uncommon to have to spend over $100,000