On the predictive content of leading indicators: the case of U.S. real estate marketsTsolacos, S., Brooks, C. ORCID: https://orcid.org/0000-0002-2668-1153 and Nneji, O. (2014) On the predictive content of leading indicators: the case of U.S. real estate markets. Journal of Real Estate Research, 36 (4). pp. 541-573. ISSN 0896-5803 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Abstract/SummaryThis paper employs a probit and a Markov switching model using information from the Conference Board Leading Indicator and other predictor variables to forecast the signs of future rental growth in four key U.S. commercial rent series. We find that both approaches have considerable power to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a naïve model, especially for the warehouse and apartment sectors. We find that while the Markov switching model appears to be more successful, it lags behind actual turnarounds in market outcomes whereas the probit is able to detect whether rental growth will be positive or negative several quarters ahead.
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