An Early Warning System to Predict the House Price Bubbles

25 Pages Posted: 30 Jul 2011

See all articles by Christian Dreger

Christian Dreger

European University Viadrina Frankfurt (Oder); IZA Institute of Labor Economics; Chinese Academy of Social Sciences (CASS)

Konstantin A. Kholodilin

German Institute for Economic Research (DIW Berlin)

Date Written: July 2011

Abstract

In this paper, we construct the country-specific chronologies of the house price bubbles for 12 OECD countries over the period 1969:Q1 - 2010:Q2. These chronologies are obtained using a combination of a fundamental and a filter approaches. The resulting speculative bubble chronology is the one that provides the highest concordance between these two techniques. In addition, we suggest an early warning system based on three alternative approaches: signalling approach, logit and probit models. It is shown that the latter two models allow much more accurate predictions of the house price bubbles than the signalling approach. The prediction accuracy of the logit and probit models is high enough to make them useful in forecasting the future speculative bubbles in housing market. Thus, our method can be used by the policymakers in their attempts to timely detect the house price bubbles and attenuate their devastating effects on the domestic and world economy.

Keywords: House prices, early warning system, OECD countries

JEL Classification: C25, C33, E32, E37

Suggested Citation

Dreger, Christian and Kholodilin, Konstantin A., An Early Warning System to Predict the House Price Bubbles (July 2011). DIW Berlin Discussion Paper No. 1142, Available at SSRN: https://ssrn.com/abstract=1898561 or http://dx.doi.org/10.2139/ssrn.1898561

Christian Dreger (Contact Author)

European University Viadrina Frankfurt (Oder) ( email )

Frankfurt (Oder)
Germany

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Chinese Academy of Social Sciences (CASS) ( email )

Beijing, 100732
China

Konstantin A. Kholodilin

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstra├če 58
Berlin, 10117
Germany

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