Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference

Helmut L\"utkepohl, Fei Shang, Luis Uzeda and Tomasz Wo\'zniak
Additional contact information
Helmut L\"utkepohl: Freie Universit\"at Berlin and DIW Berlin
Fei Shang: South China University of Technology and Yuexiu Capital Holdings Group
Tomasz Wo\'zniak: University of Melbourne
Authors registered in the RePEc Author Service: Helmut Lütkepohl

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Abstract: 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.

Date: 2024-04
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (2)

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Working Paper: Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2404.11057

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