EXTERNKholodilin, Konstantin A.Siliverstovs, Boriss2014-05-202020-01-042022-11-262020-01-042022-11-262014https://orlis.difu.de/handle/difu/221766In this paper, we evaluate the forecasting ability of 115 indicators to predict the housing prices and rents in 71 German cities. Above all, we are interested in whether the local business confidence indicators can allow substantially improving the forecasts, given the local nature of the real-estate markets. The forecast accuracy of different predictors is tested in a framework of a quasi out-of-sample forecasting. Its results are quite heterogeneous. No single indicator appears to dominate all the others for all cities and market segments. However, there are several predictors that are especially useful, namely the business confidence at the national level, consumer confidence, and price-to-rent ratios. Given the short sample size, the combinations of individual forecast do not improve the forecast accuracy. On average, the forecast improvements attain about 20%, measured by reduction in RMSFE, compared to the naïve model. In separate cases, however, the magnitude of improvement is about 50 %.Graue Literatur10419/92316L0DAY16SDM14042486WohnungswesenWohnungsmarktGroßstadtPrognoseMietpreisPreisentwicklungBefragungEmpirische UntersuchungImmobilieImmobilienmarktImmobilienpreisGrundstücksmarkt