Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters

Markus Heinrich and Magnus Reif

No 8054, CESifo Working Paper Series from CESifo

Abstract: This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying parameter VAR with stochastic volatility (MF-TVP-SV-VAR). Overall, the MF-TVP-SV-VAR delivers accurate now- and forecasts and, on average, outperforms its competitors. We assess the models’ accuracy relative to expert forecasts and show that the MF-TVP-SV-VAR delivers better inflation nowcasts in this regard. Using an optimal prediction pool, we moreover demonstrate that the MF-TVP-SV-VAR has gained importance since the Great Recession.

Keywords: time-varying parameters; forecasting; nowcasting; mixed-frequency models; Bayesian methods (search for similar items in EconPapers)
JEL-codes: C11 C53 C55 E32 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_8054

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