Abstract

In this paper, we construct a quality-adjusted rent index for the office market in Oslo. Commonly used rent indices are based on average developments or expert opinions. Such indices often suffer from compositional biases or low data coverage. Using detailed data from more than 16,000 rental contracts, we show that compositional biases can have a large impact on rental price developments. By adding building fixed effects to a standard hedonic regression model, we show that the explanatory power increases considerably. Furthermore, indices controlling for micro-location portray a different picture of rent developments than indices that do not take this into account. We also document a considerable rent premium for proximity to a metro station. Finally, we exploit information on contract signature date and find that a more timely detection of turning-points can be achieved by using the signature date instead of the more typically used start date of the lease. The financial system is heavily exposed towards the commercial real estate market and timely detection of turning-points is of major importance to policymakers.