Tracking trend output using expectations data

Lee, Kevin; Mahony, Michael

Abstract

This article proposes a new approach to measuring trend output that exploits survey data on expectations to distinguish the effects of permanent and transitory shocks and to track the time-variation in the processes underlying the determination of output. The approach is illustrated using measures of output expectations and output uncertainties based on a business survey conducted for UK manufacturing. The measures are employed in a time-varying vector autoregression (VAR) to track trend output and to provide a compelling characterization of the output fluctuations in UK manufacturing over the last 20 years.

Citation

Lee, K., & Mahony, M. (2024). Tracking trend output using expectations data. Journal of the Royal Statistical Society: Series A, Article qnae064. https://doi.org/10.1093/jrsssa/qnae064

• Journal Article Type: Article
• Acceptance Date: Jul 18, 2024
• Online Publication Date: Jul 24, 2024
• Publication Date: Jul 24, 2024
• Deposit Date: Jul 5, 2024
• Publicly Available Date: Jul 30, 2024
• Journal: Journal of the Royal Statistical Society Series A: Statistics in Society
• Print ISSN: 0964-1998
• Electronic ISSN: 1467-985X
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Article Number: qnae064
• DOI: https://doi.org/10.1093/jrsssa/qnae064
• Keywords: Output Trend; Business Cycles; Expectations; Productivity Slowdown; Sur- vey Data; Uncertainty
• Public URL: https://nottingham-repository.worktribe.com/output/36876180
• Publisher URL: https://academic.oup.com/jrsssa/advance-article/doi/10.1093/jrsssa/qnae064/7719358