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~subject:"vector autoregressive process"
~person:"Lütkepohl, Helmut"
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vector autoregressive process
impulse responses
22
Impulse responses
20
VAR-Modell
18
VAR model
17
Estimation theory
16
Schätztheorie
16
Time series analysis
12
Zeitreihenanalyse
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Vector autoregressive process
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bootstrap
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joint confidence bands
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Bayesian error bands
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Wald statistic
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confidence band
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frequentist confidence bands
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highest density region
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Bayes-Statistik
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Geldpolitik
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Monetary policy
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instrumental variable
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Bayesian estimation
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Cointegration
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Schock
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Shock
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Structural vector autoregression
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structural vector autoregression
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vector autoregressive model
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Bootstrap
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Bootstrap inference
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EM algorithm
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Instrumental variable
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Kointegration
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Markov process
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Theorie
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Vector autoregressive model
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dynamic econometric models
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Lütkepohl, Helmut
Staszewska-Bystrova, Anna
17
Winker, Peter
17
Luetkepohl, Helmut
7
Lanne, Markku
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DIW Berlin (Deutsches Institut für Wirtschaftsforschung)
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Sonderforschungsbereich 649: Ökonomisches Risiko, Wirtschaftswissenschaftliche Fakultät
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Joint discussion paper series in economics : publ. by the Universities of Aachen, Gießen, Göttingen, Kassel, Marburg, Siegen
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ECONIS (ZBW)
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1
Calculating joint confidence bands for impulse response functions using highest density regions
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2016
This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A...
Persistent link: https://www.econbiz.de/10011449884
Saved in:
2
Calculating joint confidence bands for impulse response functions using highest density regions
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2016
This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A...
Persistent link: https://www.econbiz.de/10011516886
Saved in:
3
Calculating joint confidence bands for impulse response functions using highest density regions
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2016
This paper proposes a new non-parametric method of constructing joint con- dence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A...
Persistent link: https://www.econbiz.de/10011531893
Saved in:
4
Calculating joint confidence bands for impulse response functions using highest density regions
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2016
This paper proposes a new non-parametric method of constructing joint con- dence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A...
Persistent link: https://www.econbiz.de/10011452908
Saved in:
5
Calculating joint confidence bands for impulse response functions using highest density regions
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2016
This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A...
Persistent link: https://www.econbiz.de/10011442327
Saved in:
6
Calculating joint confidence bands for impulse response functions using highest density regions
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2016
This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models. The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A...
Persistent link: https://www.econbiz.de/10011446084
Saved in:
7
Confidence Bands for
Impulse
Responses
: Bonferroni versus Wald
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
Sonderforschungsbereich 649: Ökonomisches Risiko, …
-
2014
these considerations are equally important for constructing forecast bands, we focus on the case of
impulse
responses
in …
Persistent link: https://www.econbiz.de/10010734527
Saved in:
8
Confidence Bands for
Impulse
Responses
: Bonferroni versus Wald
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
DIW Berlin (Deutsches Institut für Wirtschaftsforschung)
-
2014
these considerations are equally important for constructing forecast bands, we focus on the case of
impulse
responses
in …
Persistent link: https://www.econbiz.de/10011128842
Saved in:
9
Confidence bands for
impulse
responses
: Bonferroni versus Wald
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2014
these considerations are equally important for constructing forecast bands, we focus on the case of
impulse
responses
in …
Persistent link: https://www.econbiz.de/10010330387
Saved in:
10
Confidence bands for
impulse
responses
: Bonferroni versus Wald
Lütkepohl, Helmut
;
Staszewska-Bystrova, Anna
;
Winker, Peter
-
2014
these considerations are equally important for constructing forecast bands, we focus on the case of
impulse
responses
in …
Persistent link: https://www.econbiz.de/10010331128
Saved in:
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