Forecasting is estimating what the future demand for transport will be. Usually economics predict 3 variants of forecast: low, high and average. This is because there are a lot of uncertainties because some assumptions of forecast are based on a wide range of data. The forecast can be based on GDP figures, imports figures and past trends,etc. They look at those figures because the government or certain companies need to plan future spending decisions or to set new transport policy. Also, people use forecasts because they want to help transport planners meet future needs.
However, there are a lot of problems which are caused by looking at these datas. The main problem with GDP is that we always have recessions and recoveries throughout the period. However, if we forecast mainly on these figures, the chances that we will be wrong are really high. For example, in 2008 no one expected to have crisis and a lot of transport projects were rejected to be brought in reality as economics estimated that there will be a huge increase in GDP and the economy would flourish, as a result they were wrong and current needs did not meet transport planners’ plans. While using imports data there are a lot of assumptions.
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Money will be wasted on nothing useful. Last but not least, we base our forecast only on the past trends which do not include : just changed tastes/ fashion, population growth, technology development and new legal restrictions in current time. Past trends were based also on current demand during that time which was obviously lower 20 years ago than now because people got higher incomes and the transport got cheaper in comparison to another years. Therefore , while we are making our forecasts on the base of past trends we are increasing our chances to be wrong. We can not predict what the future trend/fashion will be.
We can’t predict what the future technology would be. Even though those problems seem to be unsolvable, we can minimize them by making forecasts not for 20-100 years but for a shorter period of time. That would minimize our problems because the probability that economists will be wrong is reduced by a big amount. Also, in order to solve the black market problem we can use the Delphi technique of different universities. For example, the University of Chicago sent their student to collect the data of how many drugs, cigarettes are imported from another countries.
Of course there is another problem: the forecast might be out of date as every day figures changes. But they will be approximately correct and appropriate. It is better than do not use any alternatives to make the data more reliable. Also, we could use much more data in order to make the forecast even more accurate but we have to be sure that these datas are accurate and not out of date. Despite the many problems, it would be a bigger problem if we would not use methods mentioned above. By using wider range of data and predicting the future demand for a shorter demand, we rescue ourselves of being completely wrong.