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The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures
The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures
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The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures
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The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures
The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures

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The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures
The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures
Journal Article

The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures

2022
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Overview
Purpose The purpose of this paper is to examine the relationship between house price affordability (HPA) and rental price affordability (RPA) in New Zealand. The cointegration of HPA and RPA is of particular focus given rising house prices and rising rents. Design/methodology/approach The study examines the lead-lad correlation between HPA and RPA. The method uses a generalised least square technique and the development of an ordinary least squares model. Findings The study shows that there is an existence of cointegration and unidirectional statistical causality effects between HPA and RPA across 11 regions in New Zealand. Furthermore, Auckland, Wellington and Canterbury are the three regions in which the results detect the most extreme effects amongst HPA and RPA compared to other places in the country. Extended empirical work shows interesting results that there are lead-lag effects of HPA and RPA on each other and on mortgage rates at the national scale. These effects are consistent for both methods but are changed at individual lead-lag variables and amongst different regions. Originality/value The study empirically provides useful insight for both academia and practitioners. Particularly in examining the long-run effects, cointegration and forecasting of the volatile interactions between HPA and RPA.