IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/0805.html
   My bibliography  Save this paper

Modeling the Phillips curve with unobserved components

Author

Listed:
  • Harvey, A.

Abstract

The relationship between in.ation and the output gap can be modeled simply and effectively by including an unobserved random walk component in the model. The dynamic properties match the stylized facts and the random walk component satisfies the properties normally required for core in.ation. The model may be generalized to as to include a term for the expectation of next period's output, but it is shown that this is difficult to distinguish from the original specification. The model is fited as a single equation and as part of a bivariate model that includes an equation for GDP. Fitting the bivariate model highlights some new aspects of unobserved components modeling. Single equation and bivariate models tell a similar story: an output gap two per cent above trend is associated with an annual inflation rate that is one percent above core inflation.

Suggested Citation

  • Harvey, A., 2008. "Modeling the Phillips curve with unobserved components," Cambridge Working Papers in Economics 0805, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0805
    as

    Download full text from publisher

    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe0805.pdf
    File Function: Working Paper Version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-368, July.
    2. Harvey, Andrew C. & Trimbur, Thomas M. & Van Dijk, Herman K., 2007. "Trends and cycles in economic time series: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 618-649, October.
    3. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    4. Pesaran, M. H., 1981. "Identification of rational expectations models," Journal of Econometrics, Elsevier, vol. 16(3), pages 375-398, August.
    5. Christophe Planas & Alessandro Rossi, 2004. "Can inflation data improve the real-time reliability of output gap estimates?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 121-133.
    6. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    7. Rudd, Jeremy & Whelan, Karl, 2005. "New tests of the new-Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1167-1181, September.
    8. Martin Fukac & Adrian Pagan, 2006. "Issues in Adopting DSGE Models for Use in the Policy Process," Working Papers 2006/6, Czech National Bank.
    9. Basistha, Arabinda & Nelson, Charles R., 2007. "New measures of the output gap based on the forward-looking new Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 498-511, March.
    10. M. Dossche & G. Everaert, 2005. "Measuring inflation persistence: a structural time series approach," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/340, Ghent University, Faculty of Economics and Business Administration.
    11. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    12. Planas, Christophe & Rossi, Alessandro & Fiorentini, Gabriele, 2008. "Bayesian Analysis of the Output Gap," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 18-32, January.
    13. James M. Nason & Gregor W. Smith, 2008. "Identifying the new Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 525-551.
    14. Mise, Emi & Kim, Tae-Hwan & Newbold, Paul, 2005. "On suboptimality of the Hodrick-Prescott filter at time series endpoints," Journal of Macroeconomics, Elsevier, vol. 27(1), pages 53-67, March.
    15. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
    16. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    17. Mavroeidis, Sophocles, 2005. "Identification Issues in Forward-Looking Models Estimated by GMM, with an Application to the Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 421-448, June.
    18. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    19. 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.
    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. Mallick, Debdulal, 2019. "Policy regimes and the shape of the Phillips curve in Australia," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1077-1094.
    2. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    3. Kavtaradze, Lasha, 2014. "Inflation Dynamics in Georgia," MPRA Paper 59966, University Library of Munich, Germany.
    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. Kajuth Florian, 2016. "NAIRU Estimates for Germany: New Evidence on the Inflation–Unemployment Tradeoff," German Economic Review, De Gruyter, vol. 17(1), pages 104-125, February.
    6. Sumru Altug & Cem Cakmakli, 2014. "Inflation Targeting and Inflation Expectations: Evidence for Brazil and Turkey," Koç University-TUSIAD Economic Research Forum Working Papers 1413, Koc University-TUSIAD Economic Research Forum.
    7. Macchiarelli, Corrado, 2014. "Bond market co-movements, expected inflation and the GBP-USD equilibrium real exchange rate," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 242-256.
    8. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, October.
    9. Kajuth, Florian, 2012. "Identifying the Phillips curve through shifts in volatility," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 975-991.
    10. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    11. De la Serve, M-E. & Lemoine, M., 2011. "Measuring the NAIRU: a complementary approach," Working papers 342, Banque de France.
    12. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    13. Mallick, Debdulal, 2014. "A Spectral Representation of the Phillips Curve in Australia," MPRA Paper 59794, University Library of Munich, Germany.
    14. Mengheng Li & Irma Hindrayanto, 2018. "Looking for the stars: Estimating the natural rate of interest," Working Paper Series 51, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    15. Byron J. Idrovo-Aguirre & Javier E. Contreras-Reyes, 2019. "Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015," Empirical Economics, Springer, vol. 57(5), pages 1829-1852, November.
    16. Basistha, Arabinda & Kurov, Alexander, 2010. "Estimating earnings trend using unobserved components framework," Economics Letters, Elsevier, vol. 107(1), pages 55-57, April.
    17. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    18. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    19. Antonio Paradiso & Saten Kumar & B. Bhaskara Rao, 2013. "A New Keynesian IS curve for Australia: is it forward looking or backward looking?," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3691-3700, September.
    20. Lena Vogel, 2008. "The Relationship between the Hybrid New Keynesian Phillips Curve and the NAIRU over Time," Macroeconomics and Finance Series 200803, University of Hamburg, Department of Socioeconomics.
    21. Paradiso, Antonio & Rao, B. Bhaskara, 2012. "Flattening of the Phillips curve and the role of the oil price: An unobserved component model for the USA and Australia," Economics Letters, Elsevier, vol. 117(1), pages 259-262.
    22. Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.
    23. Mohammad Naim Azimi, 2016. "Drawing on Phillips curve: does the inverse relation between inflation and unemployment persist in transitional economies," International Journal of Economics and Accounting, Inderscience Enterprises Ltd, vol. 7(2), pages 89-100.
    24. Hindrayanto, Irma & Samarina, Anna & Stanga, Irina M., 2019. "Is the Phillips curve still alive? Evidence from the euro area," Economics Letters, Elsevier, vol. 174(C), pages 149-152.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bertille Antoine & Otilia Boldea, 2015. "Efficient Inference with Time-Varying Information and the New Keynesian Phillips Curve," Discussion Papers dp15-04, Department of Economics, Simon Fraser University, revised 25 Aug 2016.
    2. Bill Russell & Anindya Banerjee & Issam Malki & Natalia Ponomareva, 2010. "A Multiple Break Panel Approach To Estimating United States Phillips Curves," Dundee Discussion Papers in Economics 232, Economic Studies, University of Dundee.
    3. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    4. Antoine, Bertille & Boldea, Otilia, 2018. "Efficient estimation with time-varying information and the New Keynesian Phillips Curve," Journal of Econometrics, Elsevier, vol. 204(2), pages 268-300.
    5. Russell, Bill, 2011. "Non-stationary inflation and panel estimates of United States short and long-run Phillips curves," Journal of Macroeconomics, Elsevier, vol. 33(3), pages 406-419, September.
    6. 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.
    7. 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, vol. 94(Fall), pages 361-395.
    8. Carlos Medel, 2017. "Forecasting Chilean inflation with the hybrid new keynesian Phillips curve: globalisation, combination, and accuracy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 20(3), pages 004-050, December.
    9. Gary Koop & M. Hashem Pesaran & Ron P. Smith, 2013. "On Identification of Bayesian DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 300-314, July.
    10. Bratsiotis, George J. & Robinson, Wayne A., 2016. "Unit Total Costs: An Alternative Marginal Cost Proxy for Inflation Dynamics," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 1826-1849.
    11. Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
    12. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    13. Tim Willems, 2009. "Visualizing the Invisible: Estimating the New Keynesian Output Gap via a Bayesian Approach," Tinbergen Institute Discussion Papers 09-074/2, Tinbergen Institute, revised 26 Mar 2010.
    14. 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.
    15. Malikane, Christopher, 2014. "A new Keynesian triangle Phillips curve," Economic Modelling, Elsevier, vol. 43(C), pages 247-255.
    16. Stephane Dees & M. Hashem Pesaran & L. Vanessa Smith & Ron P. Smith, 2009. "Identification of New Keynesian Phillips Curves from a Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1481-1502, October.
    17. Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.
    18. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
    19. 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.
    20. Russell, Bill & Banerjee, Anindya, 2008. "The long-run Phillips curve and non-stationary inflation," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1792-1815, December.

    More about this item

    Keywords

    Cycle; hybrid new Keynesian Phillips curve; inflation gap; Kalman filter; output gap.;
    All these keywords.

    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:cam:camdae:0805. 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: . General contact details of provider: https://www.econ.cam.ac.uk/ .

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jake Dyer (email available below). General contact details of provider: https://www.econ.cam.ac.uk/ .

    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.