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Comparing the New Keynesian Phillips Curve with Time Series Models to Forecast Inflation

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Abstract

The New Keynesian Phillips Curve, as a structural model of inflation dynamics, has mostly been used to explain past inflation developments, but has hardly been used for forecasting purposes. We propose a method of forecasting inflation based on the present-value formulation of the hybrid New Keynesian Phillips Curve. To evaluate the forecasting performance of this model we compare it with forecasts generated from time series models at different forecast horizons. As state-of-the-art time series models used in inflation forecasting we employ a Bayesian VAR, a traditional VAR and a simple autoregressive model. We find that the New Keynesian Phillips Curve delivers relatively more accurate forecasts compared to the other models for longer forecast horizons (more than 3 months) while they are outperformed by the time series models only for the very short forecast horizon. This is consistent with the finding in the literature that structural models are able to outperform time series models only for longer horizons.

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  • Fabio Rumler & Maria Teresa Valderrama, 2008. "Comparing the New Keynesian Phillips Curve with Time Series Models to Forecast Inflation," Working Papers 148, Oesterreichische Nationalbank (Austrian Central Bank).
  • Handle: RePEc:onb:oenbwp:148
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    Cited by:

    1. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    2. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    3. Szafranek, Karol, 2017. "Flattening of the New Keynesian Phillips curve: Evidence for an emerging, small open economy," Economic Modelling, Elsevier, vol. 63(C), pages 334-348.
    4. Carlos A. Medel, 2015. "Inflation Dynamics and the Hybrid New Keynesian Phillips Curve: The Case of Chile," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(1), pages 25-69, january-j.
    5. 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.
    6. Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski, Economic Research Department.
    7. Ivan Kitov & Oleg Kitov, 2013. "Inflation, unemployment, and labour force. Phillips curves and long-term projections for Austria," Papers 1310.1786, arXiv.org.
    8. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    9. Arruda, Elano Ferreira & Ferreira, Roberto Tatiwa & Castelar, Ivan, 2011. "Modelos Lineares e Não Lineares da Curva de Phillips para Previsão da Taxa de Inflação no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 65(3), September.
    10. El-Shagi, Makram, 2011. "Inflation expectations: Does the market beat econometric forecasts?," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 298-319.
    11. Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
    12. Dandan Liu & Dennis Jansen, 2011. "Does a factor Phillips curve help? An evaluation of the predictive power for U.S. inflation," Empirical Economics, Springer, vol. 40(3), pages 807-826, May.
    13. repec:onb:oenbwp:y::i:150:b:1 is not listed on IDEAS
    14. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    15. Medel, Carlos A., 2015. "A Critical Review of Posch, J. and F. Rumler (2015), 'Semi-Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve,' Journal of Forecasting 34(2): 145-62," MPRA Paper 65665, University Library of Munich, Germany.
    16. Monir Uddin Ahmed & Md. Moniruzzaman Muzib & Md. Mahedi Hasan, 2016. "Inflation, inflation uncertainty and relative price variability in Bangladesh," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(3), pages 389-427, December.
    17. Mamdouh Abdelmoula M. ABDELSALAM, 2017. "Improving Phillips Curve’s Inflation Forecasts under Misspecification," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 54-76, September.

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    More about this item

    Keywords

    New Keynesian Phillips Curve; Inflation Forecasting; Forecast Evaluation; Bayesian VAR;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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