Identifying High-Frequency Shockswith Bayesian Mixed-Frequency VARs

Alessia Paccagnini and Fabio Parla ()
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Fabio Parla: Bank of Lithuania

No 97, Bank of Lithuania Working Paper Series from Bank of Lithuania

Abstract: We contribute to research on mixed-frequency regressions by introducing an innovative Bayesian approach. We impose a Normal-inverse Wishart prior by adding a set of auxiliary dummies in estimating a Mixed-Frequency VAR. We identify a high frequency shock in a Monte Carlo experiment and in an illustrative example with uncertainty shock for the U.S. economy. As the 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 in case of a large mismatching between the highfrequency shock and low-frequency business cycle variables.

Keywords: Bayesian mixed-frequency VAR; MIDAS; Monte Carlo; uncertainty shocks; macro-financial linkages (search for similar items in EconPapers)
JEL-codes: C32 E44 E52 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2021-12-29
New Economics Papers: this item is included in nep-cwa, nep-ecm, nep-ets, nep-mac, nep-mst and nep-ore
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Identifying high-frequency shocks with Bayesian mixed-frequency VARs (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:lie:wpaper:97

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