Commercial Property Price Indexes: Problems of Sparse Data, Spatial Spillovers, and Weighting
IMF
Download Document| Date Published | 2014 |
| Version | |
| Primary Author | Mick Silver and Brian Graf |
| Other Authors | |
| Theme | House Price Indices |
| Country |
Abstract
Transaction-price residential (house) and commercial property price indexes (RPPIs and CPPIs) have inherent problems of sparse data on heterogeneous properties, more so CPPIs. In an attempt to control for heterogeneity, (repeat-sales and hedonic) panel data regression frameworks are typically used for estimating overall price change. We address the problem of sparse data, demonstrate the need to include spatial price spillovers to remove bias, and propose an innovative approach to effectively weight regional CPPIs along with improvements to higher-level weighting systems. The study uses spatial panel regressions on granular CPPIs for the United States (US).