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Normalization in econometrics
Hamilton, James D.; Waggoner, Daniel F.; Zha, Tao - In: Econometric reviews 26 (2007) 2, pp. 221-252
Persistent link: https://www.econbiz.de/10003509123
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Sign restrictions, structural vector autoregressions, and useful prior information
Baumeister, Christiane; Hamilton, James D. - In: Econometrica : journal of the Econometric Society, an … 83 (2015) 5, pp. 1963-1999
Persistent link: https://www.econbiz.de/10011417080
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Sign restrictions, structural vector autoregressions, and useful prior information
Baumeister, Christiane; Hamilton, James D. - 2014
Persistent link: https://www.econbiz.de/10010467592
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Normalization in econometrics
Hamilton, James D. (contributor);  … - 2004
Persistent link: https://www.econbiz.de/10002572254
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Structural vector autoregressions with imperfect identifying information
Baumeister, Christiane; Hamilton, James D. - In: AEA papers and proceedings 112 (2022), pp. 466-470
Persistent link: https://www.econbiz.de/10013254278
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Advances in structural vector autoregressions with imperfect identifying information
Baumeister, Christiane; Hamilton, James D. - 2020
Persistent link: https://www.econbiz.de/10012222153
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Inference in structural vector autoregressions when the identifying assumptions are not fully believed : re-evaluating the role of monetary policy in economic fluctuations
Baumeister, Christiane; Hamilton, James D. - In: Journal of monetary economics 100 (2018), pp. 48-65
Persistent link: https://www.econbiz.de/10012109069
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Structural interpretation of vector autoregressions with incomplete identification : revisiting the role of oil supply and demand shocks
Baumeister, Christiane; Hamilton, James D. - In: The American economic review 109 (2019) 5, pp. 1873-1910
Persistent link: https://www.econbiz.de/10012013583
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Inference in structural vector autoregressions when the identifying assumptions are not fully believed : reevaluating the role of monetary policy in economic fluctuations
Baumeister, Christiane; Hamilton, James D. - 2018 - Revised May 3, 2018
Reporting point estimates and error bands for structural vector autoregressions that are only set identified is a very common practice. However, unless the researcher is persuaded on the basis of prior information that some parameter values are more plausible than others, this common practice...
Persistent link: https://www.econbiz.de/10011847554