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ECONOMIC ACTIVITY, CREDIT MARKET CONDITIONS, AND THE HOUSING MARKET

Published online by Cambridge University Press:  03 July 2017

Luca Agnello
Affiliation:
University of Palermo
Vitor Castro
Affiliation:
University of Coimbra and NIPE
Ricardo M. Sousa*
Affiliation:
University of Minho, NIPE, and London School of Economics
*
Address correspondence to: Ricardo M. Sousa, University of Minho, Department of Economics and Economic Policies Research Unit (NIPE), Campus of Gualtar, 4710-057 Braga, Portugal; e-mail: [email protected].

Abstract

In this paper, we assess the characteristics of the housing market and its main determinants. Using data for 20 industrial countries over the period 1970Q1–2012Q2 and a discrete-time Weibull duration model, we find that the likelihood of the end of a housing boom or a housing bust increases over time. Additionally, we show that the different phases of the housing market cycle are strongly dependent on the economic activity, but credit market conditions are particularly important in the case of housing booms. The empirical findings also indicate that although housing booms have similar lengths in European and non-European countries, housing busts are typically shorter in European countries. The use of a more flexible specification for the hazard function that is based on cubic splines suggests that it evolves in a nonlinear way. From a policy perspective, our study can be useful for predicting the timing and the length of housing boom–bust cycles. Moreover, it highlights the importance of monetary policy by influencing lending rates and affecting the likelihood of occurrence of housing booms.

Type
Articles
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

We are grateful to participants to the 2nd International Workshop on “Financial Markets and Nonlinear Dynamics” (FMND), organized in Paris on June 4–5, 2015 (http://www.fmnd.fr), the Guest Editor, Fredj Jawadi, and Philip Rothman for their constructive comments and suggestions that considerably improved this paper. Castro and Sousa acknowledge that this work has been financed by Operational Programme for Competitiveness Factors–COMPETE and by National Funds through the FCT–Portuguese Foundation for Science and Technology within the remit of the project “FCOMP-01-0124-FEDER-037268 (PEst-C/EGE/UI3182/2013)”. Castro also wishes to thank the financial support provided by FCT–Portuguese Foundation for Science and Technology under the research grant SFRH/BSAB/113588/2015 (partially funded by COMPTE, QREN and FEDER).

References

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