Recent history is filled with stories of companies and sometimes entire industries that have made costly strategic errors because of inaccurate economic forecasting. Some of the most famous inaccurate industry-wide forecasts include:
- In 1980 and 1981, a whopping $500 billion was invested in the petroleum industry because forecasters predicted oil prices would rise by 50%. Instead, demand fell, and prices collapsed. This caused huge losses throughout the petroleum industry.
- Between 1983 and 1984, 67 types of business personal computers were introduced to the U.S market. This was expected to create explosive growth, with one forecasting service predicting an installed base of 28 million units over the next three years. In fact, by 1986, only 15 million units had been shipped.
The inaccuracies showcased in these two examples did not stem from a lack of forecasting techniques. Instead, they failed to take into account the changing relationships driving demand for both products across the world. The forecasting companies did not foresee any change in end-user behaviour or understand how market saturation would impact their estimations.
Nowadays, economic forecasting is provided by a range of non-city and city forecasters and tends to be far more accurate than forecasting predictions in the 1980’s. It is important to remember that economic forecasting is not an exact science and even experienced forecasters can make some mistakes.
Indicators used in Economic Forecasting
Companies now use a range of economic indicators to help inform forecast reports. The different statistics they look into are usually the starting point, though more factors have to be considered as well. Some statistics and factors will have a more drastic impact on projections, which is why they will carry more weight in predictions.
Indicators include the consumer price index, as well as the gross domestic product. You can often track these figures on a daily basis, whereas other statistics will be released periodically. Now, you may be questioning the accuracy of economic forecasts. As time goes on, the error margin in forecasting is getting narrower and narrower and artificial intelligence can help to accurately plot trends.
Accurate Economic Forecasters
A recent study from www.etxcapital.co.uk analysed how accurate the top non-city and city forecasters were in predicting final figures from 2015 to 2017. Among the most accurate city forecasters were Commerzbank and Morgan Stanley. In fact, Morgan Stanley was particularly accurate in their prediction of both the GDP Growth Rate and CPI Inflation in 2016, with an average of just a 0.15 percentage point (PP) off actual figures, while the industry average was a 0.47 PP. Commerzbank was the closest of all forecasters, with an average of just a 0.33 PP off actual GDP and CPI figures over the three-year period.
It wasn’t just city forecasters that made accurate predictions concerning economic outlook between 2015 and 2017. ETX Capital’s report also highlighted three non-city organisations’ economists as being particularly precise in their predictions. The Centre for Economic and Business Research was an average of just a 0.45 PP off the CPI Inflation and GDP Growth figures, which is half the industry average.
Having the ability to closely predict future GDP Growth and CPI Inflation by comparing a number of different economic forecasts helps ensure that traders will have a much clearer idea of what is going on in the economy.
By Nina Mosely