Identifying high-frequency shocks with Bayesian mixed-frequency VARs

We contribute to research on mixed-frequency regressions by introducing an innovative Bayesian approach. Based on a new “high-frequency” identification scheme, we provide novel empirical evidence of identifying uncertainty shock for the US economy. As main findings, we document a “temporal aggregation bias” when we adopt a common low frequency model instead of estimating a mixed-frequency framework. The bias is amplified when we identify a higher frequency shock

MoreLess

Year of publication:	[2021]
Authors:	Paccagnini, Alessia ; Parla, Fabio
Publisher:	[S.l.] : SSRN
Subject:	Schock \| Shock \| VAR-Modell \| VAR model \| Bayes-Statistik \| Bayesian inference \| Prognoseverfahren \| Forecasting model \| Schätzung \| Estimation \| Theorie \| Theory

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Extent:	1 Online-Ressource (50 p)
Series:	CAMA Working Paper ; No. 26/2021
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 26, 2021 erstellt
Other identifiers:	10.2139/ssrn.3793335 [DOI]
Classification:	C32 - Time-Series Models ; E44 - Financial Markets and the Macroeconomy ; E52 - Monetary Policy (Targets, Instruments, and Effects)
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013244964