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Probabilistic Quantile Factor Analysis

Dimitris Korobilis and Maximilian Schröder ()

No No 05/2023, Working Papers from Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School

Abstract: This paper extends quantile factor analysis to a probabilistic variant that incorporates regularization and computationally efficient variational approximations. By means of synthetic and real data experiments it is established that the proposed estimator can achieve, in many cases, better accuracy than a recently proposed loss-based estimator. We contribute to the literature on measuring uncertainty by extracting new indexes of low, medium and high economic policy uncertainty, using the probabilistic quantile factor methodology. Medium and high indexes have clear contractionary effects, while the low index is benign for the economy, showing that not all manifestations of uncertainty are the same.

Pages: 51 pages
Date: 2023-08
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://hdl.handle.net/11250/3082893

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Working Paper: Probabilistic Quantile Factor Analysis (2024) Downloads
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