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The Evolution of the Phillips Curve: A Modern Time Series Viewpoint

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  • CLIVE W. J. GRANGER
  • YONGIL JEON

Abstract

Phillips' (1958) original curve involves a nonlinear relationship between inflation and unemployment. We consider how his original results change due to updated theoretic and empirical studies, increased computer power, enlarged datasets, increases in data frequency and developed time series econometric models. In the linear models, there was weak causation from unemployment to inflation. Rather than using any of the many nonlinear models that are now available, we adopt a time-varying parameter linear model as their convenient proxy, which empirically supports Phillips' use of nonlinear model form and causation, but the strength of this result is much weaker in recent periods.

Suggested Citation

  • Clive W. J. Granger & Yongil Jeon, 2011. "The Evolution of the Phillips Curve: A Modern Time Series Viewpoint," Economica, London School of Economics and Political Science, vol. 78(309), pages 51-66, January.
    • Handle: RePEc:bla:econom:v:78:y:2011:i:309:p:51-66
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    File URL: http://hdl.handle.net/10.1111/j.1468-0335.2009.00839.x
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    References listed on IDEAS

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    1. A. W. Phillips, 1958. "The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957," Economica, London School of Economics and Political Science, vol. 25(100), pages 283-299, November.
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    Cited by:

    1. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Econom a Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    2. Medel, Carlos, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," MPRA Paper 62609, University Library of Munich, Germany.
    3. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
    4. Annalisa Cristini & Piero Ferri, 2021. "Nonlinear models of the Phillips curve," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1129-1155, September.
    5. Andrea Stella & James H. Stock, 2012. "A state-dependent model for inflation forecasting," International Finance Discussion Papers 1062, Board of Governors of the Federal Reserve System (U.S.).
    6. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    7. Guizhou Wang & Kjell Hausken, 2023. "Modeling which Factors Impact Interest Rates," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 12(2), pages 211-237.
    8. Baffigi, Alberto & Bontempi, Maria Elena & Felice, Emanuele & Golinelli, Roberto, 2015. "The changing relationship between inflation and the economic cycle in Italy: 1861–2012," Explorations in Economic History, Elsevier, vol. 56(C), pages 53-70.
    9. Fumitaka Furuoka & Qaiser Munir & Hanafiah Harvey, 2013. "Does the Phillips curve exist in the Philippines?," Economics Bulletin, AccessEcon, vol. 33(3), pages 2001-2016.
    10. Guizhou Wang & Kjell Hausken, 2022. "Interest Rates, the Taylor Rule, the Quantity Equation, and the Phillips Curve," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 10(3), pages 83-93.
    11. Marfatia Hardik A., 2018. "Estimating the New Keynesian Phillips Curve for the UK: evidence from the inflation-indexed bonds market," The B.E. Journal of Macroeconomics, De Gruyter, vol. 18(1), pages 1-18, January.
    12. Panagiotis Pegkas, 2024. "The Asymmetric Effects of Unemployment and Output on Inflation in Greece: A Nonlinear ARDL Approach," Economies, MDPI, vol. 12(12), pages 1-21, December.
    13. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.

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