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Booms, busts, and normal times in the housing market

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posted on 2017-05-17, 08:53 authored by Luca Agnello, Vitor CastroVitor Castro, Ricardo M. Sousa
We assess the existence of duration dependence in the likelihood of an end in housing booms, busts, and normal times. Using data for 20 industrial countries and a continuous-time Weibull duration model, we find evidence of positive duration dependence suggesting that housing market cycles have become longer over the last decades. Then, we extend the baseline Weibull model and allow for the presence of a change-point in the duration dependence parameter. We show that positive duration dependence is present in booms and busts that last less than 26 quarters, but that does not seem to be the case for longer phases of the housing market cycle. For normal times, no evidence of change-points is found. Finally, the empirical findings uncover positive duration dependence in housing market booms of European and non-European countries and housing busts of European countries. In addition, they reveal that while housing booms have similar length in European and non-European countries, housing busts are typically shorter in European countries.

Funding

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)”.

History

School

  • Business and Economics

Department

  • Economics

Published in

Journal of Business and Economic Statistics

Volume

33

Issue

1

Pages

25 - 45

Citation

AGNELLO, L., CASTRO, V. and SOUSA, R.M., 2015. Booms, busts, and normal times in the housing market. Journal of Business and Economic Statistics, 33 (1), pp. 25-45.

Publisher

Taylor & Francis © American Statistical Association

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015-01-26

Notes

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Business and Economic Statistics on 26th January 2015, available online: http://www.tandfonline.com/10.1080/07350015.2014.918545.

ISSN

0735-0015

eISSN

1537-2707

Language

  • en

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