Mixed frequency structural models: estimation, and policy analysis

Claudia Foroni and Massimiliano Marcellino

No 2013/15, Working Paper from Norges Bank

Abstract: In this paper we show analytically, with simulation experiments and with actual data that a mismatch between the time scale of a DSGE model and that of the time series data used for its estimation generally creates identfication problems, introduces estimation bias and distorts the results of policy analysis. On the constructive side, we prove that the use of mixed frequency data, combined with a proper estimation approach, can alleviate the temporal aggregation bias, mitigate the identfication issues, and yield more reliable policy conclusions. The problems and possible remedy are illustrated in the context of standard structural monetary policy models.

Keywords: Structural VAR; DSGE models; temporal aggregation; mixed frequency data; estimation. policy analysis (search for similar items in EconPapers)
JEL-codes: C32 C43 E32 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2013-06-11
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:bno:worpap:2013_15

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