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Volumn 23, Issue 7, 2004, Pages 479-496

Finding good predictors for inflation: A bayesian model averaging approach

Author keywords

Forecast; Markov chain monte carlo; Variable selection

Indexed keywords

INDUSTRIAL ECONOMICS; MARKOV PROCESSES; MONTE CARLO METHODS; PARAMETER ESTIMATION; PUBLIC POLICY; SELECTION; STANDARDIZATION;

EID: 9744265710     PISSN: 02776693     EISSN: None     Source Type: Journal    
DOI: 10.1002/for.924     Document Type: Article
Times cited : (28)

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    • Hoeting, J.A.1    Madigan, D.2    Raftery, A.E.3    Volinsky, C.T.4
  • 8
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    • Model selection and accounting for uncertainty in graphical models using Occam's window
    • Madigan D, Raftery AE. 1994. Model selection and accounting for uncertainty in graphical models using Occam's window. Journal of the American Statistical Association 89: 1535-1546.
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    • Madigan, D.1    Raftery, A.E.2
  • 9
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    • Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting and international growth rates
    • Min CK, Zellner A. 1993. Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting and international growth rates. Journal of Econometrics 56: 89-118.
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    • Nonparametric seemingly unrelated regression
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  • 13
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    • Inflation targeting as a monetary policy rule
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.