Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/107305 
Erscheinungsjahr: 
2015
Schriftenreihe/Nr.: 
CESifo Working Paper No. 5175
Verlag: 
Center for Economic Studies and ifo Institute (CESifo), Munich
Zusammenfassung: 
We develop a non-linear forecast combination rule based on copulas that incorporate the dynamic interaction between individual predictors. This approach is optimal in the sense that the resulting combined forecast produces the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. Under additional assumptions, this rule is shown to be equivalent to the quintessential linear combination scheme. To illustrate its usefulness, we apply this methodology to optimally aggregate two currently used leading indicators—the ISM new order diffusion index and the yield curve spread—to predict economic recessions in the United States. We also examine the sources of forecasting gains using a counterfactual experimental set up.
Schlagwörter: 
receiver operating characteristic curve
Copula
Bayesian methods
Markov chain Monte Carlo
yield spread
ISM diffusion index
JEL: 
C11
C15
C38
C53
E37
Dokumentart: 
Working Paper
Erscheint in der Sammlung:

Datei(en):
Datei
Größe
765.37 kB





Publikationen in EconStor sind urheberrechtlich geschützt.