This thesis is about forecasting situations which involve econometric models and expert intuition. The first three chapters are about what it is that experts do when they adjust statistical model forecasts and what might improve that adjustment behavior. It is investigated how expert forecasts are related to model forecasts, how this potential relation is influenced by other factors and how it influences forecast accuracy, how feedback influences forecasting behavior and accuracy and which loss function is associated with experts’ forecasts. The final chapter focuses on how to make use in an optimal way of multiple forecasts produced by multiple experts for one and the same event. It is found that potential disagreement amongst forecasters can have predictive value, especially when used in Markov regime-switching models.

Additional Metadata
Keywords Bayesian analysis, Markov regime-switching models, asymmetry, cognitive process feedback, disagreement, econometric models, endogeneity, expert forecasts, judgmental adjustment, loss functions, model forecasts, outcome feedback, performance feedback, survey forecasts, task properties feedback, time series
Promotor Franses, Ph.H.B.F. (Philip Hans)
Publisher Erasmus University Rotterdam , Thela Thesis, Amsterdam
ISBN 9789036102919
Persistent URL hdl.handle.net/1765/32244
Note This book is no. 530 of the Tinbergen Institute Research Series
Citation
Legerstee, R.. (2012, May 10). Evaluating Econometric Models and Expert Intuition . Thela Thesis, Amsterdam. Retrieved from http://hdl.handle.net/1765/32244