Identifying short‐term leading indicators for real estate rental performance

Abstract

This paper looks at the application of economic and financial series in forecasting IPD monthly rental series. The approach follows that employed in classical business cycle work that seeks to decompose series into trend, cyclical and noise components and is the first time that it has been applied to IPD monthly data. Trend extraction is obtained by means of the Hodrick‐Prescott filter. Several potential indicator series are investigated together with their lead characteristics. The short‐term forecasts of these series are compared with naïve methods and a composite indicator. The results show the naïve methods, especially the Holt‐Winters method, and certain leading indicator series produce satisfactory short‐term forecasts, but the success is both sector and time‐dependent. This suggests that it is a worthwhile endeavour in identifying potential leading indicator series. The methodology presented in this paper should be seen as complementing existing approaches that employ standard econometric procedures in modelling rental growth.

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