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handle: 10419/76550 , 10419/20343
This paper considers the problems facing decision makers using econometric models in real time. It identifies the key stages involved and highlights the role of automated systems in reducing the effect of data snooping. It sets out many choices that researchers face in construction of automated systems and discusses some of the possible ways advanced in the literature for dealing with them. The role of feedbacks from the decision maker's actions to the data generating process is also discussed and highlighted through an example.
model selection, Statistical decision theory, Management decision making, including multiple objectives, Zeit, feedback effects, finance, Decision theory, cross-validation, C51, specification search, C52, Ökonometrie, C53, Applications of statistics to economics, ddc:330, model averaging, prediction, specification search, data snooping, recursive/sequential modelling, automated model selection, data snooping, recursive/sequential modelling, automated model selection; data snooping; recursive/sequential modelling; specification search, automated model selection, Theorie, Management-Informationssystem, jel: jel:C52, jel: jel:C53, jel: jel:C51
model selection, Statistical decision theory, Management decision making, including multiple objectives, Zeit, feedback effects, finance, Decision theory, cross-validation, C51, specification search, C52, Ökonometrie, C53, Applications of statistics to economics, ddc:330, model averaging, prediction, specification search, data snooping, recursive/sequential modelling, automated model selection, data snooping, recursive/sequential modelling, automated model selection; data snooping; recursive/sequential modelling; specification search, automated model selection, Theorie, Management-Informationssystem, jel: jel:C52, jel: jel:C53, jel: jel:C51
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 32 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |