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Real-time density nowcasts of US inflation: a model-combination approach

Author

Listed:
  • Edward Knotek

    () (Research Department, Federal Reserve Bank of Cleveland)

  • Saeed Zaman

    () (Research Department, Federal Reserve Bank of Cleveland, USA;)

Abstract

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Edward Knotek & Saeed Zaman, 2020. "Real-time density nowcasts of US inflation: a model-combination approach," Working Papers 2015, University of Strathclyde Business School, Department of Economics.
  • Handle: RePEc:str:wpaper:2015
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    as
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    More about this item

    Keywords

    mixed-frequency models; inflation; density nowcasts; density combinations;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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