Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Raffaella Giacomini"'
Publikováno v:
Journal of Econometrics. 231:188-212
“Rational inattention” is becoming increasingly prominent in economic modeling, but there is little empirical evidence for its central premise-that the choice of attention results from a cost-benefit optimization. Observational data typically do
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bda728a678f59d19bda7113982447142
https://doi.org/10.1016/j.jeconom.2020.06.010
https://doi.org/10.1016/j.jeconom.2020.06.010
Publikováno v:
Journal of Econometrics. 228:107-126
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cbd4722a41d259e468b36e0eb23314f
https://doi.org/10.1016/j.jeconom.2021.02.003
https://doi.org/10.1016/j.jeconom.2021.02.003
Publikováno v:
Quantitative Economics. 13:95-123
Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which can lead to a mix of po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c47796c3ebf87c3d2d0bc7672b44f600
https://doi.org/10.3982/qe1671
https://doi.org/10.3982/qe1671
Autor:
Raffaella Giacomini, Toru Kitagawa
Publikováno v:
Econometrica. 89:1519-1556
This paper reconciles the asymptotic disagreement between Bayesian and frequentist inference in set‐identified models by adopting a multiple‐prior (robust) Bayesian approach. We propose new tools for Bayesian inference in set‐identified models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6034c02515c129f40b991e0eff2ca473
https://doi.org/10.3982/ecta16773
https://doi.org/10.3982/ecta16773
Publikováno v:
American Economic Journal: Macroeconomics. 12:282-309
We formulate a theory of expectations updating that fits the dynamics of accuracy and disagreement in a new survey of professional forecasters. We document new stylized facts, including the puzzling persistence of disagreement as uncertainty resolves
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ca195d3ce66994b4b2a0ee098a09323
https://doi.org/10.1257/mac.20180235
https://doi.org/10.1257/mac.20180235
Publikováno v:
SSRN Electronic Journal.
We compare two approaches to using information about the signs of structural shocks at specific dates within a structural vector autoregression (SVAR): imposing "narrative restrictions" (NR) on the shock signs in an otherwise set-identified SVAR; and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::399778330087369c78a70657260ae9e7
https://doi.org/10.2139/ssrn.4078221
https://doi.org/10.2139/ssrn.4078221
We review the literature on robust Bayesian analysis as a tool for global sensitivity analysis and for statistical decision-making under ambiguity. We discuss the methods proposed in the literature, including the different ways of constructing the se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42fec2f26bdc41af722f6b8ba595c657
https://doi.org/10.21033/wp-2021-11
https://doi.org/10.21033/wp-2021-11
We develop methods for robust Bayesian inference in structural vector autoregressions (SVARs) where the parameters of interest are set-identified using external instruments, or ‘proxy SVARs’. Set-identification in these models typically occurs wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4411d95c824c01b243f3233c8a255009
https://doi.org/10.1920/wp.cem.2020.1320
https://doi.org/10.1920/wp.cem.2020.1320
Autor:
Raffaella Giacomini, Toru Kitagawa
This paper reconciles the asymptotic disagreement between Bayesian and frequentist inference in set‐identified models by adopting a multiple‐prior (robust) Bayesian approach. We propose new tools for Bayesian inference in set‐identified models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d8c8d74db07dcd0b8da12be11378f7a
https://doi.org/10.1920/wp.cem.2020.1220
https://doi.org/10.1920/wp.cem.2020.1220