Exogenous uncertainty and the identification of structural vector autoregressions with external instruments

Angelini, Giovanni; Fanelli, Luca

doi:10.1002/jae.2736

Cited by 42 publications

(38 citation statements)

References 61 publications

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“…Lütkepohl and Milunovich () and Casarin et al () confirm this finding. Angelini et al () do not reject the hypothesis that both financial and macroeconomic uncertainty are drivers of the business cycle (for similar results, see Angelini and Fanelli ) . We see the relationship between the financial side of uncertainty and the term structure of interest rates as a natural one.…”

Section: Introductionmentioning

confidence: 95%

Yield Curve and Financial Uncertainty: Evidence Based on US Data

Castelnuovo

2019

Australian Economic Review

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How do short-and long-term interest rates respond to a jump in financial uncertainty? We address this question by conducting a local projections analysis with US monthly data, period: 1962-2018. The state-of-the-art financial uncertainty measure proposed by Ludvigson, Ma and Ng (2019) is found to predict movements in interest rates at different maturities. In particular, an increase in financial uncertainty is found to trigger a negative and significant response of both short-and long-term interest rates. The response of the short end of the yield curve (i.e., of short-term interest rates) is found to be stronger than that of the long end (i.e., of longterm ones). In other words, a financial uncertainty shock causes a temporary steepening of the yield curve. This result is consistent, among other interpretations, with medium-term expectations of a recovery in real activity after a financial uncertainty shock.

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Section: Introductionmentioning

confidence: 95%

Yield Curve and Financial Uncertainty: Evidence Based on US Data

Castelnuovo

2019

Australian Economic Review

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“…where W t and t are (n+k)-dimensional, and " " indicates that e (L) and e G incorporate 11 A detailed exposition of the properties of the AC-SVAR approach can be found in Angelini and Fanelli (2019). We use their notation to facilitate the mapping between their derivations and our presentation of their framework and its properties.…”

Section: Relation To the Literaturementioning

confidence: 99%

“…16 When the restrictions that characterize e G are zero constraints, separable across columns, a convenient way to study the identi…cation of the proxy-SVAR is to check whether the su¢ cient conditions for global identi…cation in Theorem 2 of Rubio-Ramírez, Waggoner, and Zha (2010) are met. See Angelini and Fanelli (2019) for some examples. error with standard deviation !…”

Section: Relation To the Literaturementioning

confidence: 99%

“…Methodology. We obtain these results by working with a ‡exible proxy-SVAR methodology recently proposed by Angelini and Fanelli (2019) and termed "augmented and constrained SVAR" (AC-SVAR). In short, the AC-SVAR jointly models both the variables of interest (e.g., …scal spending, tax revenues, and output) and the proxies used to identify the shocks of interest.…”

Section: Introductionmentioning

confidence: 99%

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Are Fiscal Multipliers Estimated with Proxy-SVARs Robust?

et al. 2020

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How large are government spending and tax multipliers? The …scal proxy-SVAR literature provides heterogenous estimates, depending on which proxies-…scal or non-…scal-are used to identify …scal shocks. We reconcile the existing estimates via a ‡exible vector autoregressive model that allows to achieve identi…cation in presence of a number of structural shocks larger than that of the available instruments. Our two main …ndings are the following. First, the estimate of the tax multiplier is sensitive to the assumption of orthogonality between total factor productivity (non-…scal proxy) and tax shocks. If this correlation is assumed to be zero, the tax multiplier is found to be around one. If such correlation is nonzero, as supported by our empirical evidence, we …nd a tax multiplier three times as large. Second, we …nd the spending multiplier to be robustly larger than one across di¤erent models that feature di¤erent sets of instruments. Our results are robust to the joint employment of di¤erent …scal and non-…scal instruments.

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“…Angelini and Fanelli (2019),Arias et al (2018b), and Giacomini et al (2019a), we augment m t into the original SVAR,…”

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confidence: 99%

Locally- but not globally-identified SVARs

Bacchiocchi¹,

Kitagawa²

2020

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This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not globally. In this case there exists a set of isolated structural parameter points that are observationally equivalent under the imposed restrictions. Although the data do not inform us which observationally equivalent point should be selected, the common frequentist practice is to obtain one as a maximum likelihood estimate and perform impulse response analysis accordingly. For Bayesians, the lack of global identification translates to nonvanishing sensitivity of the posterior to the prior, and the multi-modal likelihood gives rise to computational challenges as posterior sampling algorithms can fail to explore all the modes. This paper overcomes these challenges by proposing novel estimation and inference procedures. We characterize a class of identifying restrictions that deliver local but non-global identification, and the resulting number of observationally equivalent parameter values. We propose algorithms to exhaustively compute all admissible structural parameter given reduced-form parameters and utilize them to sampling from the multi-modal posterior. In addition, viewing the set of observationally equivalent parameter points as the identified set, we develop Bayesian and frequentist procedures for inference on the corresponding set of impulse responses. An empirical example illustrates our proposal.

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Exogenous uncertainty and the identification of structural vector autoregressions with external instruments

Cited by 42 publications

References 61 publications

Yield Curve and Financial Uncertainty: Evidence Based on US Data

Yield Curve and Financial Uncertainty: Evidence Based on US Data

Are Fiscal Multipliers Estimated with Proxy-SVARs Robust?

Locally- but not globally-identified SVARs

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