Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach
Edward Knotek () and
No 202031, Working Papers from Federal Reserve Bank of Cleveland
We develop a flexible modeling framework to produce density nowcasts for US inflation at a trading-day frequency. Our framework: (1) combines individual density nowcasts from three classes of parsimonious mixed-frequency models; (2) adopts a novel flexible treatment in the use of the aggregation function; and (3) permits dynamic model averaging via the use of weights that are updated based on learning from past performance. Together these features provide density nowcasts that can accommodate non-Gaussian properties. We document the competitive properties of the nowcasts generated from our framework using high-frequency real-time data over the period 2000-2015.
Keywords: mixed-frequency models; inflation; density nowcasts; density combinations (search for similar items in EconPapers)
JEL-codes: C15 C53 E3 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://doi.org/10.26509/frbc-wp-202031 Full Text (text/html)
Working Paper: Real-time density nowcasts of US inflation: a model-combination approach (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedcwq:88961
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Papers from Federal Reserve Bank of Cleveland Contact information at EDIRC.
Bibliographic data for series maintained by ().