Real-Time Density Nowcasts of U.S. Inflation : a Model-Combination Approach

Knotek II, Edward S. and Zaman, Saeed (2020) Real-Time Density Nowcasts of U.S. Inflation : a Model-Combination Approach. Preprint / Working Paper. University of Strathclyde, Glasgow.

[thumbnail of Knotek-Zaman-2020-Real-time-density-nowcasts-of-US-inflation]
Preview
 Text. Filename: Knotek_Zaman_2020_Real_time_density_nowcasts_of_US_inflation.pdf
Final Published Version
Download (6MB)| Preview

Abstract

We develop a flexible modeling framework to produce density nowcasts for U.S. 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.

CORE (COnnecting REpositories)