Long-Run Trends and Cycles in US House Prices
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 b...
| Authors: | , |
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| Format: | article |
| Publication Date: | 2025 |
| Country: | España |
| Institution: | Universidad de Málaga |
| Repository: | DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria |
| Language: | English |
| OAI Identifier: | oai:ddfv.ufv.es:10641/6951 |
| Online Access: | https://hdl.handle.net/10641/6951 |
| Access Level: | Open access |
| Keyword: | Cycles Fractional integration Long memory Persistence Trends US house prices Economics, Econometrics and Finance (miscellaneous) Computer Science Applications Yes yes |
| Summary: | 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. |
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