Forecasts of growth in US residential investment: accuracy gains from consumer home-buying attitudes and expectations

Hamid Baghestani

Applied Economics, 2021, vol. 53, issue 32, 3744-3758

Abstract: This study focuses on the Federal Reserve and private forecasts of growth in real residential investment. The aim is to improve predictive accuracy by first evaluating these forecasts. The results for 1984–2015 reveal that the Federal Reserve and private forecasts are generally free of systematic bias, superior to the naïve benchmark, and predict directional change with high accuracy rates. However, these forecasts do not contain detailed information in consumer home-buying attitudes and expectations. Using a subset of such information and real-time data on residential investment, a knowledge model (KM) is constructed to produce comparable forecasts. The test results indicate that the KM forecasts of growth in residential investment contain distinct and useful predictive information, and the combined Federal Reserve, private, and KM forecasts show reductions in forecast errors that are more significant at longer horizons. As such, we conclude that consumer survey responses help improve forecast accuracy. Given that accurate forecasts contribute to the success of policy, more transparency in Federal Reserve Open Market Committee (FOMC) decisions is encouraged. With more transparency and clear communication, consumers are able to provide more informative responses, which can then be employed to produce more accurate forecasts of growth in residential investment.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2021.1885613 (text/html)
Access to full text is restricted to subscribers.

Related works:
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:taf:applec:v:53:y:2021:i:32:p:3744-3758

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2021.1885613

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().