Arbeitspapier
Likelihood-preserving normalization in multiple equation models
Causal analysis in multiple equation models often revolves around the evaluation of the effects of an exogenous shift in a structural equation. When taking into account the uncertainty implied by the shape of the likelihood, we argue that how normalization is implemented matters for inferential conclusions around the maximum likelihood (ML) estimates of such effects. We develop a general method that eliminates the distortion of finite-sample inferences about these ML estimates after normalization. We show that our likelihood-preserving normalization always maintains coherent economic interpretations while an arbitrary implementation of normalization can lead to ill-determined inferential results.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2000-8
- Klassifikation
-
Wirtschaft
- Thema
-
Time-series analysis
Supply and demand
Demand for money
Money supply
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Waggoner, Daniel F.
Zha, Tao
- Ereignis
-
Veröffentlichung
- (wer)
-
Federal Reserve Bank of Atlanta
- (wo)
-
Atlanta, GA
- (wann)
-
2000
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Waggoner, Daniel F.
- Zha, Tao
- Federal Reserve Bank of Atlanta
Entstanden
- 2000
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