IDEAS home Printed from https://ideas.repec.org/p/koc/wpaper/1321.html
   My bibliography  Save this paper

Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data

Author

Listed:
  • Nalan Basturk

    () (Erasmus University Rotterdam Econometric Institute, Tinbergen Institute)

  • Cem Cakmakli

    () (University of Amsterdam Department of Quantitative Economics, Koç University)

  • Pinar Ceyhan

    () (Erasmus University Rotterdam Econometric Institute, Tinbergen Institute)

  • Herman K. van Dijk

    () (Erasmus University Rotterdam Econometric Institute, Tinbergen Institute, VU University Amsterdam Department of Econometrics)

Abstract

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 and backward looking expectation components for inflation are incorporated and their relative importance is 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. 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 deflation in recent years.

Suggested Citation

  • Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.
  • Handle: RePEc:koc:wpaper:1321
    as

    Download full text from publisher

    File URL: http://eaf.ku.edu.tr/sites/eaf.ku.edu.tr/files/erf_wp_1321.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Fabio Canova & Filippo Ferroni, 2011. "Multiple filtering devices for the estimation of cyclical DSGE models," Quantitative Economics, Econometric Society, pages 73-98.
    2. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, pages 211-219.
    3. Rudd, Jeremy & Whelan, Karl, 2005. "New tests of the new-Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, pages 1167-1181.
    4. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    5. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    6. Frank Schorfheide, 2003. "Learning and monetary policy shifts," FRB Atlanta Working Paper 2003-23, Federal Reserve Bank of Atlanta.
    7. Gali, Jordi & Gertler, Mark & David Lopez-Salido, J., 2005. "Robustness of the estimates of the hybrid New Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, pages 1107-1118.
    8. Christiano, Lawrence J. & Vigfusson, Robert J., 2003. "Maximum likelihood in the frequency domain: the importance of time-to-plan," Journal of Monetary Economics, Elsevier, pages 789-815.
    9. Gabriel Perez-Quiros & Margaret M. McConnell, 2000. "Output Fluctuations in the United States: What Has Changed since the Early 1980's?," American Economic Review, American Economic Association, pages 1464-1476.
    10. Giorgio Gobbi & Roberta Zizza, 2007. "Does the Underground Economy Hold Back Financial Deepening? Evidence from the Italian Credit Market," CEP Discussion Papers dp0789, Centre for Economic Performance, LSE.
    11. Christopher A. Sims & Tao Zha, 2005. "Were There Regime Switches in U.S. Monetary Policy?," Working Papers 92, Princeton University, Department of Economics, Center for Economic Policy Studies..
    12. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, pages 113-172.
    13. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, pages 54-81.
    14. Frank Schorfheide, 2005. "Learning and Monetary Policy Shifts," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 392-419, April.
    15. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, Elsevier.
    16. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, pages 383-398.
    17. Ferroni Filippo, 2011. "Trend Agnostic One-Step Estimation of DSGE Models," The B.E. Journal of Macroeconomics, De Gruyter, pages 1-36.
    18. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, pages 586-606.
    19. Levin, Andrew & Yun, Tack, 2007. "Reconsidering the natural rate hypothesis in a New Keynesian framework," Journal of Monetary Economics, Elsevier, pages 1344-1365.
    20. Ascari, Guido & Ropele, Tiziano, 2007. "Optimal monetary policy under low trend inflation," Journal of Monetary Economics, Elsevier, pages 2568-2583.
    21. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco.
    22. James M. Nason & Gregor W. Smith, 2008. "The New Keynesian Phillips curve : lessons from single-equation econometric estimation," Economic Quarterly, Federal Reserve Bank of Richmond, issue Fall, pages 361-395.
    23. James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007. "Normalization in Econometrics," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 221-252.
    24. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco.
    25. Boswijk, H. Peter & Jansson, Michael & Nielsen, Morten Ørregaard, 2015. "Improved likelihood ratio tests for cointegration rank in the VAR model," Journal of Econometrics, Elsevier, pages 97-110.
    26. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
    27. Yun, Tack, 1996. "Nominal price rigidity, money supply endogeneity, and business cycles," Journal of Monetary Economics, Elsevier, pages 345-370.
    28. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
    29. Arnold Zellner & Tomohiro Ando & Nalan Baştük & Lennart Hoogerheide & Herman K. van Dijk, 2014. "Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo," Econometric Reviews, Taylor & Francis Journals, pages 3-35.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    2. 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," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
    3. Altug, Sumru & Çakmaklı, Cem, 2016. "Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey," International Journal of Forecasting, Elsevier, pages 138-153.
    4. Skorepa, Michal & Komarek, Lubos, 2015. "Sources of asymmetric shocks: The exchange rate or other culprits?," Economic Systems, Elsevier, pages 654-674.
    5. Laura Hering & Rodrigo Paillacar, 2016. "Does Access to Foreign Markets Shape Internal Migration? Evidence from Brazil," World Bank Economic Review, World Bank Group, pages 78-103.
    6. Michal Andrle & Jan Bruha & Serhat Solmaz, 2013. "Inflation and Output Comovement in the Euro Area: Love at Second Sight?," Working Papers 2013/07, Czech National Bank, Research Department.
    7. Michal Andrle & Jan Bruha & Serhat Solmaz, 2013. "Inflation and Output Comovement in the Euro Area: Love at Second Sight?," Working Papers 2013/07, Czech National Bank, Research Department.
    8. Thomas Buser & Anna Dreber, 2016. "The Flipside of Comparative Payment Schemes," Management Science, INFORMS, vol. 62(9), pages 2626-2638, September.
    9. repec:bpj:bejmac:v:17:y:2017:i:1:p:42:n:3 is not listed on IDEAS

    More about this item

    Keywords

    New Keynesian Phillips curve; unobserved components; time varying parameters; level shifts; inflation expectations; survey data;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:koc:wpaper:1321. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sumru Oz). General contact details of provider: http://edirc.repec.org/data/dekoctr.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.