We use the gradient boosting estimation technique and the ROC curveto non-parametrically measure and exploit the maximal predictive powerof leading indicators for the future state of the business cycle. We de-velop novel procedures for finding the best performing transformationsof individual...

Evaluation methodologies for rare events from meteorology, psychology and medical diagnosis are used to examine the value of probabilistic forecasts of real GDP declines during the current quarter (Q0) and each of the next four quarters (Q1–Q4) using data from the Survey of Professional...

Bootstrap aggregating or Bagging, introduced by Breiman (1996a), has been proved to be effective to improve on unstable forecast. Theoretical and empirical works using classification, regression trees, variable selection in linear and non-linear regression have shown that bagging can generate...

Stochastic neural network is a hierarchical network of stochastic neurons which emit 0 or 1 with the probability determined by the values of inputs. We have developed an efficient training algorithm so as to maximize the likelihood of such a neural network. This algorithm enables us to apply the...