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The application of short‐term forecasting techniques to the prediction of commercial rental values generates valuable information about the dynamics of rent movements. It also captures short‐run trends more effectively than do other forecasting procedures. Makes use of ARIMA models to provide one‐step‐ahead predictions. The results show that ARIMA models perform better in the case of retail and office sectors. The forecasts for these sectors are satisfactory. Retail rents bear a relationship to their past values, whereas office rents are influenced by shocks in the market – demand or supply driven. The results of the present study are useful for incorporation in more general models of rent forecasting. Also presents a full methodology which facilitates its application.

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