The Google Insights data are a collection of recorded Internet searches for a huge number of the keywords, which are … consumption based on both the conventional consumer confidence indicators and the Google indicators. The latter are extracted from … the Google searches using the principal component analysis. It is shown that the Google indicators are especially …

In this paper, we evaluate the forecasting ability of 115 indicators to predict the housing prices and rents in 71 … tested in a framework of a quasi out-of-sample forecasting. Its results are quite heterogeneous. No single indicator appears …

even more pronounced at longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared … spatial dependence structure into regional forecasting models, especially, when long-term forecasts are made. …

This paper considers the issue of forecasting financial fragility of banks and insurances using a panel data set of …

shown that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast …

-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the … for GDP forecasting although their ranking depends on the underlying transformation of monthly indicators from which the …

-of-sample forecasting exercise, we find that both pooling and accounting for spatial effects helps to substantially improve the forecast …-of-sample forecasting of the growth rates of flats' prices and rents for the next six months is done. It shows that in most cities both …

We extend the analysis of Christoffersen and Diebold (1998) on long-run forecasting in cointegrated systems to …, this new loss function entails high and increasing forecasting gains compared to both the standard MSFE criterion and …