Economics at your fingertips  

Forecasting housing investment

Carlos Cañizares Martínez, Gabe de Bondt and Arne Gieseck

Journal of Forecasting, 2023, vol. 42, issue 3, 543-565

Abstract: This study applies a model averaging approach to conditionally forecast housing investment in the largest Euro area countries and the Euro area. To account for substantial modeling uncertainty, it estimates a large and diverse number of vector error correction models using a wide set of long‐ and short‐run determinants and applies subset selection based on in‐sample and out‐of‐sample criteria. First, a pseudo out‐of‐sample forecast exercise shows that our model averaging approach consistently beats a battery of distinguished benchmark models, including BVARs, FAVARs, LASSO, and Ridge regressions. This evidences that model averaging provides more accurate forecasts also in the case of housing investment. Second, we find remarkable cross‐country heterogeneity in the drivers of housing investment. Overall, these findings guide forecasters and modelers on improving housing investment models and policymakers on implementing country‐specific housing market policies.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)

Related works:
Working Paper: Forecasting housing investment (2023) Downloads
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:

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

Page updated 2023-09-26
Handle: RePEc:wly:jforec:v:42:y:2023:i:3:p:543-565