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作者

来源

REAL ESTATE ECONOMICS,Vol.46,Issue3,P.582-611

语言

英文

关键字

PARTIAL LEAST-SQUARES; DYNAMIC-FACTOR MODEL; LONG-RUN RELATIONSHIP; REAL-ESTATE; EQUITY PREMIUM; MARKETS; REGRESSION; PERFORMANCE; RETURNS; RENTS

作者单位

[Bork, Lasse] Aalborg Univ, Dept Business & Management, Fibigerstraede 2, DK-9220 Aalborg, Denmark. [Moller, Stig V.] Aarhus Univ, CREATES, Fuglesangs Alle 4, DK-8210 Aarhus, Denmark. Bork, L (reprint author), Aalborg Univ, Dept Business & Management, Fibigerstraede 2, DK-9220 Aalborg, Denmark. E-Mail: bork@business.aau.dk; svm@asb.dk

摘要

We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS) and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks and regression models based on small datasets.