Commercial Property Price Indexes: Problems of Sparse Data, Spatial Spillovers, and Weighting
May 1, 2014
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Summary
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).
Subject: Econometric analysis, Inflation, Land prices, Logit models, Price indexes, Prices, Spatial models
Keywords: Commercial Property Price Indexes, dummy variable, Errors in Measurement, House Price Indexes, Index Number Weights, Inflation, inflation estimate, Land prices, Logit models, math, Moody's aggregation process, Moody's CPPIs, Price indexes, price inflation, RCA building block index, RCA CPPI weight, Spatial Econometrics, Spatial models, Spatial Panel Regressions, transaction price, WP
Pages:
30
Volume:
2014
DOI:
Issue:
072
Series:
Working Paper No. 2014/072
Stock No:
WPIEA2014072
ISBN:
9781484364543
ISSN:
1018-5941
