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The Two Interpretations Of The Beveridge–Nelson Decomposition

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  • Morley, James C.

Abstract

The Beveridge–Nelson decomposition calculates trend and cycle for an integrated time series. However, there are two ways to interpret the results from the decomposition. One interpretation is that the optimal long-run forecast (minus any deterministic drift) used to calculate the Beveridge–Nelson trend corresponds to an estimate of an unobserved permanent component. The other interpretation is that the optimal long-run forecast defines an observable permanent component. This paper examines some issues surrounding these two interpretations and provides empirical support for interpreting the Beveridge–Nelson trend as an estimate when considering macroeconomic data.

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  • Morley, James C., 2011. "The Two Interpretations Of The Beveridge–Nelson Decomposition," Macroeconomic Dynamics, Cambridge University Press, vol. 15(3), pages 419-439, June.
    • Handle: RePEc:cup:macdyn:v:15:y:2011:i:03:p:419-439_00
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    Cited by:

    1. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    2. Blasques, F. & van Brummelen, J. & Gorgi, P. & Koopman, S.J., 2024. "A robust Beveridge–Nelson decomposition using a score-driven approach with an application," Economics Letters, Elsevier, vol. 236(C).
    3. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    4. Angelia L. Grant & Joshua C.C. Chan, 2017. "A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(2-3), pages 525-552, March.
    5. Tommaso Proietti, 2016. "The Multistep Beveridge--Nelson Decomposition," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 373-395, March.
    6. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
    7. Donayre, Luiggi, 2014. "Estimated Thresholds In The Response Of Output To Monetary Policy: Are Large Policy Changes Less Effective?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(1), pages 41-64, January.
    8. Katsuyuki Shibayama, 2015. "Trend Dominance in Macroeconomic Fluctuations," Studies in Economics 1518, School of Economics, University of Kent.
    9. James McNeil & Gregor W. Smith, 2023. "The All‐Gap Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 269-282, April.
    10. Mardi Dungey & Jan P.A.M. Jacobs & Jing Jian & Simon van Norden, 2013. "Trend-Cycle Decomposition: Implications from an Exact Structural Identification," CIRANO Working Papers 2013s-23, CIRANO.
    11. James Morley, 2014. "Measuring economic slack in Asia and the Pacific," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation, inflation and monetary policy in Asia and the Pacific, volume 77, pages 35-50, Bank for International Settlements.
    12. Morley, James & Piger, Jeremy, 2008. "Trend/cycle decomposition of regime-switching processes," Journal of Econometrics, Elsevier, vol. 146(2), pages 220-226, October.
    13. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    14. Martínez-García, Enrique, 2021. "Get the lowdown: The international side of the fall in the U.S. natural rate of interest," Economic Modelling, Elsevier, vol. 100(C).

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