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Identification and Inference Under Narrative Restrictions

Raffaella Giacomini, Toru Kitagawa, Matthew Read

arXiv 12 Feb 2021 · Econometrics · 10 citations (OpenAlex)

arXiv:2102.06456 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We consider structural vector autoregressions subject to 'narrative restrictions', which are inequality restrictions on functions of the structural shocks in specific periods. These restrictions raise novel problems related to identification and inference, and there is currently no frequentist procedure for conducting inference in these models. We propose a solution that is valid from both Bayesian and frequentist perspectives by: 1) formalizing the identification problem under narrative restrictions; 2) correcting a feature of the existing (single-prior) Bayesian approach that can distort inference; 3) proposing a robust (multiple-prior) Bayesian approach that is useful for assessing and eliminating the posterior sensitivity that arises in these models due to the likelihood having flat regions; and 4) showing that the robust Bayesian approach has asymptotic frequentist validity. We illustrate our methods by estimating the effects of US monetary policy under a variety of narrative restrictions.

Citation extraction

41
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Uhlig, H (2005) What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure1.00054100%
2Arias, J., J. Rubio-Ramírez, and D. Waggoner (2018) Inference Based on Structural Vector Autoregressions Identified with Sign and Zero Restrictions: Theory and Applications0.84333100%
3Giacomini, R., T. Kitagawa, and M. Read (2019) Robust Bayesian Inference in Proxy SVARs, cemmap Working Paper CWP23/19 self0.84333100%
4Romer, C. and D. Romer (1989) Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz, in0.73732100%
5Ben Zeev, N (2018) What Can We Learn About News Shocks from the Late 1990s and Early 2000s Boom-bust Period?0.64422100%
6Rubio-Ramírez, J., D. Waggoner, and T. Zha (2010) Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference0.64422100%
Plagborg-Moller_Wolf_2020aunmatched citation key Plagborg-Moller_Wolf_2020a0.5115220%
8Amir-Ahmadi, P. and T. Drautzburg (2021) Identification and Inference with Ranking Restrictions0.5113233%
9Mertens, K. and M. Ravn (2013) The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States, 103, 1212–470.5112250%
Plagborg-Moller_Wolf_2020bunmatched citation key Plagborg-Moller_Wolf_2020b0.5112250%

Showing the top 10 of 45 scored citations. 2 of these could not be matched to a bibliography entry, so only the citation key is shown.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions0.92843
2Large structural VARs with multiple linear shock and impact inequality restrictions0.73732
3Dynamic Causal Effects in a Nonlinear World: the Good, the Bad, and the Ugly0.40511