Premium
Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions
Author(s) -
Bollerslev Tim,
Patton Andrew J.,
Wang Wenjing
Publication year - 2015
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2471
Subject(s) - heteroscedasticity , econometrics , autoregressive conditional heteroskedasticity , house price , economics , autocorrelation , index (typography) , price index , metropolitan area , asset (computer security) , residential property , multivariate statistics , financial economics , statistics , volatility (finance) , mathematics , computer science , geography , economic geography , computer security , archaeology , world wide web
Summary We construct daily house price indices for 10 major US metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat‐sales method that closely mimics the methodology of the popular monthly Case–Shiller house price indices. Our new daily house price indices exhibit dynamic features similar to those of other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity of the corresponding daily returns. A relatively simple multivariate time series model for the daily house price index returns, explicitly allowing for commonalities across cities and GARCH effects, produces forecasts of longer‐run monthly house price changes that are superior to various alternative forecast procedures based on lower‐frequency data. Copyright © 2015 John Wiley & Sons, Ltd.