Abstract
Purpose
This paper aims to examine asymmetries in the house price cycle and to understand the dynamic of housing prices, incorporating macroeconomic variables at regional and country level, namely, housing affordability, the unemployment rate, mortgage rate and inflation rate.
Design/methodology/approach
To highlight significant differences in the asymmetric patterns of house prices between regions, the STAR model is adopted.
Findings
The authors highlight significant differences in the asymmetric patterns of house prices between regions, in which some areas showed asymmetric response over the housing cycle; here the LSTAR model outperforms other models. In contrast, some regions (the South West and the North West) showed symmetric properties in the tails of the cycle; therefore, the ESTAR model was adopted in their case.
Practical implications
Being limited to a few fundamentals, this study opens an avenue for further research to investigate this dynamic using in addition such demand-supply factors as land supply, construction cost and loans made for housing. These findings can also be used to examine whether other models such as ARIMA, exponential smoothing or artificial neural networks can more accurately forecast housing prices.
Originality/value
The present paper aims to highlight housing affordability as a cause of asymmetric behaviour in house prices. Put differently, the authors seek to understand the dynamics of housing prices with other fundamentals incorporating macroeconomic variables in regions and country level data as a means of achieving a more concise result.
Subject
General Economics, Econometrics and Finance
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