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Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach

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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.
JEL classifications: C15, C53, E3, E37.

Suggested citation: Knotek, Edward S., II, and Saeed Zaman. 2020. “Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach.” Federal Reserve Bank of Cleveland, Working Paper No. 20-31.

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