Long-Run Trends and Cycles in US House Prices

Guglielmo Maria Caporale and Luis Alberiko Gil-Alana ()
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Guglielmo Maria Caporale: Brunel University of London
Luis Alberiko Gil-Alana: University of Navarra, NCID, DATAI

Computational Economics, 2025, vol. 66, issue 6, No 20, 5017-5031

Abstract: 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.

Keywords: US house prices; Trends; Cycles; Persistence; Long memory; Fractional integration (search for similar items in EconPapers)
JEL-codes: C15 C22 E30 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-025-10882-8

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