Arbeitspapier

Importance Assessment of Correlated Predictors in Business Cycles Classification

When trying to interpret estimated parameters the researcher is interested in the (relative) importance of the individual predictors. However, if the predictors are highly correlated, the interpretation of coefficients, e.g. as economic ?multipliers?, is not applicable in standard regression or classification models. The goal of this paper is to develop a procedure to obtain such measures of importance for classification methods and to apply them to models for the classification of german business cycle phases.

Language
Englisch

Bibliographic citation
Series: Technical Report ; No. 2004,66

Subject
Konjunkturprognose
Prognoseverfahren
Korrelation
Klassifikation
Theorie

Event
Geistige Schöpfung
(who)
Enache, Daniel
Weihs, Claus
Event
Veröffentlichung
(who)
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
(where)
Dortmund
(when)
2004

Handle
Last update
10.03.2025, 11:47 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Enache, Daniel
  • Weihs, Claus
  • Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

Time of origin

  • 2004

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