Long-Run Trends and Cycles in US House Prices
Abstract This paper analyses US nominal house prices at an annual frequency over the period from 1927 to 2022 by means of a very general time series model. This includes both a (linear and non-linear) deterministic and a stochastic component, with the latter allowing for fractional orders of integration at both the long-run and the cyclical frequencies. The results are heterogeneous depending on the model specification and on whether or not the series have been logged. Specifically, a linear model appears to be more appropriate for the logged data whilst a non-linear one appears to be a better fit for the original ones. Further, the order of integration at the zero or long-run frequency is much higher than at the cyclical one. The former is in fact around 1 in all specified models, which implies a high degree of persistence of this component. Finally, the order of integration of the cyclical structure implies that cycles have a periodicity of about 8 years, but it is almost insignificant in all cases.
Authors
- Luis A. Gil-Alaña (ORCID: https://orcid.org/0000-0002-5760-3123)
- Guglielmo Maria Caporale (ORCID: https://orcid.org/0000-0002-0144-4135)
Institutions
- University of London (GB)
- Universidad Francisco de Vitoria (ES)
- Brunel University of London (GB)
- Universidad de Navarra (ES)
Publication Details
- Journal
- Computational Economics
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1007/s10614-025-10882-8
- Primary Topic
- Housing Market and Economics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universidad Francisco de Vitoria
- Universidad de Navarra
- Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España
- European Regional Development Fund
- Agencia Estatal de Investigación