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Can the consumption-wealth ratio predict housing returns? Evidence from OECD countries

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posted on 2017-08-15, 13:27 authored by Guglielmo Maria Caporale, Ricardo M. Sousa, Mark Wohar
©2016 American Real Estate and Urban Economics Association We use a representative consumer model to analyze the relation between the transitory deviations of consumption from its common trend with aggregate wealth and labor income, cay, and the housing risk premium. The evidence based on data for 15 OECD countries shows that, if financial and housing assets are seen as complements, investors will temporarily allow consumption to rise when they expect a rise in future housing returns. By contrast, if housing assets are treated as substitutes for financial assets, consumption will be reduced.

History

School

  • Business and Economics

Department

  • Business

Published in

Real Estate Economics

Volume

47

Issue

7

Pages

935-976

Citation

CAPORALE, G.M., SOUSA, R.M. and WOHAR, M.E., 2016. Can the consumption-wealth ratio predict housing returns? Evidence from OECD countries. Real Estate Economics, 47(4), pp. 935-976.

Publisher

© American Real Estate and Urban Economics Association. Published by Wiley

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/

Acceptance date

2015-01-31

Publication date

2016-02-01

Copyright date

2019

Notes

This is the peer reviewed version of the following article: CAPORALE, G.M., SOUSA, R.M. and WOHAR, M.E., 2016. Can the consumption-wealth ratio predict housing returns? Evidence from OECD countries. Real Estate Economics, 47(4), pp. 935-976 which has been published in final form at http://dx.doi.org/10.1111/1540-6229.12135. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

ISSN

1080-8620

eISSN

1540-6229

Language

  • en

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