Business Confidence and Forecasting of Housing Prices and Rents in Large German Cities


METADATA ONLY
Loading...

Date

2014

Publication Type

Working Paper

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

In 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 condence indicators can allow substantially improving the forecasts, given the local nature of the real-estate markets. The forecast accuracy of dierent 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 condence at the national level, consumer condence, 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 na ve model. In separate cases, however, the magnitude of improvement is about 50%.

Permanent link

Publication status

published

External links

Editor

Book title

Volume

2014

Pages / Article No.

1360

Publisher

Deutsches Institut für Wirtschaftsforschung

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Housing prices; Housing rents; Forecasting; Spatial dependence; German cities; Confidence indicators; Chambers of commerce and industry

Organisational unit

02525 - KOF Konjunkturforschungsstelle / KOF Swiss Economic Institute check_circle

Notes

Funding

Related publications and datasets