Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference

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Auteurs
Date

17 avril 2024

Discipline
Type de document
Périmètre
Identifiant
  • 2404.11057
Source

arXiv - économie

Collection

arXiv

Organisation

Cornell University

Mots-clés Und

Economics - Econometrics Statistics - Applications

Sujets proches En

Surgical shock

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Helmut Lütkepohl et al., « Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference », arXiv - économie

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We consider structural vector autoregressions identified through stochastic volatility. Our focus is on whether a particular structural shock is identified by heteroskedasticity without the need to impose any sign or exclusion restrictions. Three contributions emerge from our exercise: (i) a set of conditions under which the matrix containing structural parameters is partially or globally unique; (ii) a statistical procedure to assess the validity of the conditions mentioned above; and (iii) a shrinkage prior distribution for conditional variances centred on a hypothesis of homoskedasticity. Such a prior ensures that the evidence for identifying a structural shock comes only from the data and is not favoured by the prior. We illustrate our new methods using a U.S. fiscal structural model.

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