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Nowcasting recession risk

In: Handbook of Research Methods and Applications in Macroeconomic Forecasting

Author

Listed:
  • Francesco Furno
  • Domenico Giannone

Abstract

Bringing together the recent advances and innovative methods in macroeconomic forecasting, this erudite Handbook outlines how to forecast, including following world events such as the Covid-19 pandemic and the global financial crisis. With contributions from global experts, chapters explore the use of machine-learning techniques, the value of social media data, and climate change forecasting. This title contains one or more Open Access chapters.

Suggested Citation

  • Francesco Furno & Domenico Giannone, 2024. "Nowcasting recession risk," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 7, pages 156-186, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:22222_7
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    File URL: https://www.elgaronline.com/doi/10.4337/9781035310050.00011
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    Cited by:

    1. Patrick J. Coe & Shaun P. Vahey, 2025. "Reassessing the Predictive Power of the Yield Spread for Recessions in the United States," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(2), pages 231-236, March.

    More about this item

    Keywords

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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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