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Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model

Abstract : The Great Recession and the subsequent period of subdued GDP growth in most advanced economies have highlighted the need for macroeconomic forecasters to account for sudden and deep recessions, periods of higher macroeconomic volatility, and fluctuations in trend GDP growth. In this paper, we put forward an extension of the standard Markov-Switching Dynamic Factor Model (MS-DFM) by incorporating two new features: switches in volatility and time-variation in trend GDP growth. First, we show that volatility switches largely improve the detection of business cycle turning points in the low-volatility environment prevailing since the mid-1980s. It is an important result for the detection of future recessions since, according to our model, the US economy is now back to a low-volatility environment after an interruption during the Great Recession. Second, our model also captures a continuous decline in the US trend GDP growth that started a few years before the Great Recession and continued thereafter. These two extensions of the standard MS-DFM framework are supported by information criteria, marginal likelihood comparisons and improved real-time GDP forecasting performance.
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https://halshs.archives-ouvertes.fr/halshs-02443364
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Submitted on : Friday, January 17, 2020 - 10:00:40 AM
Last modification on : Tuesday, September 22, 2020 - 3:51:03 AM

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  • HAL Id : halshs-02443364, version 1

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Catherine Doz, Laurent Ferrara, Pierre-Alain Pionnier. Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model. 2020. ⟨halshs-02443364⟩

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