This paper proposes and tests a new framework for weighting recursive out-of-sample prediction errors in accordance with their corresponding in-sample estimation uncertainty. In essence, we show how as much information from the sample as possible can be used in the evaluation of prediction...

This paper employs a probit model and a Markov switching model using information from the Conference Board Leading Indicator series to detect the turning points in four key US commercial rents series. We find that both the approaches based on the leading indicator have considerable power to...