The purpose of this study is to determine whether house prices and income share a stable, stationary relationship in the G-7 countries. This stable relationship has been clearly implied by theory but has been difficult to uncover empirically in previous studies.
The analysis entails using nonlinear tests for a stationary relationship between home prices and per-capita income for the G-7 countries, whereas most previous papers on the topic have used linear methods.
When the standard linear ADF test is used, no stationary relationship for home prices and income is found for any of the G-7 countries. When the more powerful (but still linear) Ng–Perron test is used, the USA, but no other G-7 country, exhibits a stable relationship between the two variables. When the nonlinear Enders–Granger test is used, stationarity between home prices and income is found for five of the remaining six G-7 states.
Previous research has shown that as house prices have risen far above the income, especially over bubble periods, income has done a poor job in predicting home values. The findings show that income has a clear long-run stationary relationship with home values. This implies income could be helpful in providing home price forecasts.
Where previous studies have failed to find a long-run relationship between home prices and income while using linear methods, results in this paper show this theoretical asset–pricing relationship holds once the adjustment process is allowed to exhibit nonlinearity.
Miles, W. (2019), "Home prices and fundamentals: solving the mystery for the G-7 by accounting for nonlinearities", International Journal of Housing Markets and Analysis, Vol. 13 No. 2, pp. 299-315. https://doi.org/10.1108/IJHMA-03-2019-0029Download as .RIS
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