Abstract
In this paper, we employ a probit model 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 and can be used to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a näive 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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