Identification strategies are discussed for Structural Vector Autoregressions (SVARs) which combine the use of external instruments, the so-called proxy-SVAR or SVAR-IV approach with the heteroskedasticity found in the data, the so-called identification-via-heteroskedasticity approach. The focus in on the case in which r valid instruments are used to identify g>=1 structural shocks of interest, with r>=g, and there are m structural breaks in the VAR error covariance matrix which give rise to m+1 volatility regimes. It is shown that the combination of the two approaches enhances identification possibilities for practitioners and produce overidentified testable models, denoted HP-SVARs. Two types of heteroskedasticity are considered. In one case, the structural breaks do not affect the on-impact coefficients so that the Impulse Response Functions (IRFs) are constant across volatillity regimes. In the other case, the structural breaks affect the on-impact coefficients and thee IRFs are regime-dependent. General identification results for HP-SVARs are derived for these two cases. Estimation can be carried out through maximum likelihood.

Heteroskedastic proxy-SVARs / Luca Fanelli. - STAMPA. - (2018), pp. 144-144. (Intervento presentato al convegno 12th International Conference on Computational and Financial Econometrics (CFE 2018) tenutosi a University of Pisa, Italy nel 14-16 December 2018).

Heteroskedastic proxy-SVARs

Luca Fanelli
2018

Abstract

Identification strategies are discussed for Structural Vector Autoregressions (SVARs) which combine the use of external instruments, the so-called proxy-SVAR or SVAR-IV approach with the heteroskedasticity found in the data, the so-called identification-via-heteroskedasticity approach. The focus in on the case in which r valid instruments are used to identify g>=1 structural shocks of interest, with r>=g, and there are m structural breaks in the VAR error covariance matrix which give rise to m+1 volatility regimes. It is shown that the combination of the two approaches enhances identification possibilities for practitioners and produce overidentified testable models, denoted HP-SVARs. Two types of heteroskedasticity are considered. In one case, the structural breaks do not affect the on-impact coefficients so that the Impulse Response Functions (IRFs) are constant across volatillity regimes. In the other case, the structural breaks affect the on-impact coefficients and thee IRFs are regime-dependent. General identification results for HP-SVARs are derived for these two cases. Estimation can be carried out through maximum likelihood.
2018
12th International Conference on Computational and Financial Econometrics (CFE 2018)
144
144
Heteroskedastic proxy-SVARs / Luca Fanelli. - STAMPA. - (2018), pp. 144-144. (Intervento presentato al convegno 12th International Conference on Computational and Financial Econometrics (CFE 2018) tenutosi a University of Pisa, Italy nel 14-16 December 2018).
Luca Fanelli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/681708
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