As table 2 shows, forecast accuracy scores for residential property prices show (MSSA using financial big data) significantly increase. A significant increase in the forecast accuracy of (MSSA) also is present for the credit to private non-financial sector time-series data. Still statistically significant but with lower forecast accuracy in relation to the (MSSA) forecasts for the residential property prices and credit to the private non-financial sector is the forecast accuracy for the credit share in the GDP. We can conclude that statistical tests for forecast accuracy show financial time series (financial cycle components) can be better forecast when using financial big data in the USA.
For Japan (see table 3), we can also observe that forecast accuracy for the financial cycle components increase if we use financial big data in the forecast process. Statistical test (forecast accuracy scores) show that we can make more accurate forecasts for residential property prices in Japan using financial big data. The same holds for the credit to private non-financial sector time series data with accuracy scores in favor of using (MSSA) for forecasting. We can notice a significant increase in the forecast accuracy for the credit share in the GDP time series data with residual errors being 2 to 3 times lower if we use financial big data and (MSSA) for forecasting.