Economic forecast is an essential tool for government officials, helping them decide what monetary and fiscal policies to implement. It can also help businesses make investment decisions. But, the more complex something is, the harder it’s to predict. This is one reason why people tend to look at forecasts with a healthy dose of skepticism.
For example, a financial series like stock market prices can be hard to forecast over short horizons because of their volatility. But, interest rates are easier to predict over short horizons because they’re fairly sticky. The same goes for the business cycle—the fluctuating levels of economic activity that mark the transition between recessions and expansions. This kind of cyclicality is easier to capture in longer time-series data, such as real gross domestic product (GDP) growth. GDP figures are released each quarter, but the initial estimates are often revised in subsequent releases. This process can be illustrated using the graph below, which shows the first, second and third estimates of GDP growth available in the St. Louis Fed’s archival database, ALFRED.
But, there’s another challenge to forecasting that may be more subtle. A forecaster’s own personal theory about how the economy works can shape their projections, McCracken said. This means that if a forecaster believes that business activity is determined by the supply of money, for instance, they might give more weight to indicators that reflect this belief. This can lead to subjective or biased forecasts.