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Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data

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  • Nalan Baştürk
  • Cem Çakmakli
  • S. Pinar Ceyhan
  • Herman K. Van Dijk

Abstract

This discussion paper resulted in a publication in the 'Journal of Applied Econometrics' , 2014, 29(7), 1164-1182. Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended Phillips Curve (PC) models. It is shown that mechanical removal or modeling of simple low frequency movements in the data may yield poor predictive results which depend on the model specification used. Basic PC models are extended to include structural time series models that describe typical time varying patterns in levels and volatilities. Forward as well as backward looking expectation mechanisms for inflation are incorporated and their relative importance evaluated. Survey data on expected inflation are introduced to strengthen the information in the likelihood. Use is made of simulation based Bayesian techniques for the empirical analysis. No credible evidence is found on endogeneity and long run stability between inflation and marginal costs. Backward-looking inflation appears stronger than forward-looking one. Levels and volatilities of inflation are estimated more precisely using rich PC models. Estimated inflation expectations track nicely the observed long run inflation from the survey data. The extended PC structures compare favorably with existing basic Bayesian Vector Autoregressive and Stochastic Volatility models in terms of fit and prediction. Tails of the complete predictive distributions indicate an increase in the probability of disinflation in recent years.
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  • Nalan Baştürk & Cem Çakmakli & S. Pinar Ceyhan & Herman K. Van Dijk, 2014. "Posterior‐Predictive Evidence On Us Inflation Using Extended New Keynesian Phillips Curve Models With Non‐Filtered Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1164-1182, November.
  • Handle: RePEc:wly:japmet:v:29:y:2014:i:7:p:1164-1182
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    Citations

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    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model," Working Papers 2013:17, Department of Economics, University of Venice "Ca' Foscari", revised 2014.
    2. Grant, Angelia L. & Chan, Joshua C.C., 2017. "Reconciling output gaps: Unobserved components model and Hodrick–Prescott filter," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 114-121.
    3. repec:wly:jmoncb:v:49:y:2017:i:5:p:969-995 is not listed on IDEAS
    4. Altug, Sumru & Çakmaklı, Cem, 2016. "Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey," International Journal of Forecasting, Elsevier, vol. 32(1), pages 138-153.
    5. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, Open Access Journal, vol. 4(1), pages 1-20, March.
    6. Nalan Basturk & Pinar Ceyhan & Herman K. van Dijk, 2014. "Bayesian Forecasting of US Growth using Basic Time Varying Parameter Models and Expectations Data," Tinbergen Institute Discussion Papers 14-119/III, Tinbergen Institute, revised 14 Sep 2014.
    7. Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
    8. Kapetanios, George & Khalaf, Lynda & Marcellino, Massimiliano, 2015. "Factor based identification-robust inference in IV regressions," CEPR Discussion Papers 10390, C.E.P.R. Discussion Papers.
    9. Francesca Rondina, 2018. "Estimating Unobservable Inflation Expectations in the New Keynesian Phillips Curve," Econometrics, MDPI, Open Access Journal, vol. 6(1), pages 1-20, February.
    10. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    11. repec:rjr:romjef:v::y:2018:i:1:p:42-62 is not listed on IDEAS
    12. repec:gam:jecnmx:v:4:y:2016:i:1:p:11:d:65219 is not listed on IDEAS
    13. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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