Residential investment and recession predictability

Knut Are Aastveit, Andre Anundsen () and Eyo Herstad

No 2017/24, Working Paper from Norges Bank

Abstract: We assess the importance of residential investment in predicting economic recessions for an unbalanced panel of 12 OECD countries over the period 1960Q1-2014Q4. Our approach is to estimate various probit models with different leading indicators and evaluate their relative prediction accuracy using the receiver operating characteristic curve. We document that residential investment contains information useful in predicting recessions both in-sample and out-of-sample. This result is robust to adding typical leading indicators, such as the term spread, stock prices, consumer confidence surveys and oil prices. It is shown that residential investment is particularly useful in predicting recessions for countries with high home-ownership rates. Finally, in a separate exercise for the US economy, we show that the predictive ability of residential investment is robust to employing real-time data.

Keywords: Recession predictability; Housing; Leading indicators; Real-time data (search for similar items in EconPapers)
JEL-codes: C33 C53 E32 E37 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2017-11-16
New Economics Papers: this item is included in nep-for and nep-mac
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.norges-bank.no/en/Published/Papers/Working-Papers/2017/242017/

Related works:
Journal Article: Residential investment and recession predictability (2019)
Working Paper: Residential investment and recession predictability (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bno:worpap:2017_24

Access Statistics for this paper

More papers in Working Paper from Norges Bank Contact information at EDIRC.
Bibliographic data for series maintained by ().