Abstract

Key challenges of the compilation of quarterly price, rent and rental yield indices are illustrated by means of case studies using data available for the German commercial real estate (CRE) markets. The object types considered are office, retail and rental housing. Amongst the issues addressed are (i) the decision on the type-specific level of regional stratification, (ii) the selection, specification and estimation of hedonic regression models for quality adjustment of transaction data, and (iii) the construction of an inherently consistent family of Laspeyres-type price, rent and yield indices. On the one hand, the pros and cons of various solutions are discussed for each issue individually and evaluated on the basis of empirical evidence. On the other hand, as the challenges under review appear at different stages of the multi-step index compilation process, their linkages in methodological and practical terms are highlighted and potential dependencies between the various choices are figured out. In developing price, rent and rental yield indices for CRE markets, compilers are usually confronted with these issues against the backdrop of substantial data limitations at the granular level while targeting to construct high-quality indicators, which are fit for purpose in economic and macroprudential analyses.