IDEAS home Printed from https://ideas.repec.org/p/lec/leecon/09-21.html
   My bibliography  Save this paper

Measuring the Natural Output Gap using Actual and Expected Output Data

Author

Listed:
  • Kevin Lee
  • Anthony Garratt
  • Kalvinder Shields

Abstract

An output gap measure is suggested based on the Beveridge-Nelson decomposition of output using a vector-autoregressive model that includes data on actual output and on expected output obtained from surveys. The paper explains the advantages of using survey data in business cycle analysis and the gap is provided economic meaning by relating it to the natural level of output defined in Dynamic Stochastic General Equilibrium models. The measure is applied to quarterly US data over the period 1970q1-2007q4 and the resultant gap estimates are shown to have sensible statistical properties and perform well in explaining inflation in estimates of New Keynesian Phillips curves.

Suggested Citation

  • Kevin Lee & Anthony Garratt & Kalvinder Shields, 2009. "Measuring the Natural Output Gap using Actual and Expected Output Data," Discussion Papers in Economics 09/21, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:09/21
    as

    Download full text from publisher

    File URL: https://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp09-21.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andres, Javier & Lopez-Salido, J. David & Nelson, Edward, 2005. "Sticky-price models and the natural rate hypothesis," Journal of Monetary Economics, Elsevier, vol. 52(5), pages 1025-1053, July.
    Full references (including those not matched with items on IDEAS)

    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. Andrea Gerali & Alberto Locarno & Alessandro Notarpietro & Massimiliano Pisani, 2015. "Every cloud has a silver lining. The sovereign crisis and Italian potential output," Temi di discussione (Economic working papers) 1010, Bank of Italy, Economic Research and International Relations Area.
    2. Fabio Verona & Maik Wolters, 2014. "Sticky Information Models in Dynare," Computational Economics, Springer;Society for Computational Economics, vol. 43(3), pages 357-370, March.
    3. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    4. Pengfei Wang & Yi Wen, 2006. "Solving linear difference systems with lagged expectations by a method of undetermined coefficients," Working Papers 2006-003, Federal Reserve Bank of St. Louis.
    5. Lena Draeger, 2011. "Endogenous persistence with recursive inattentiveness," KOF Working papers 11-285, KOF Swiss Economic Institute, ETH Zurich.
    6. Oliver Hülsewig & Eric Mayer & Timo Wollmershäuser, 2006. "Bank Behavior and the Cost Channel of Monetary Transmission," CESifo Working Paper Series 1813, CESifo.
    7. Eijffinger, Sylvester C. W. & Grajales-Olarte, Anderson & Uras, Burak R., 2020. "Heterogeneity In Wage Setting Behavior In A New-Keynesian Model," Macroeconomic Dynamics, Cambridge University Press, vol. 24(6), pages 1512-1546, September.
    8. Hilde Bjørnland & Kai Leitemo & Junior Maih, 2011. "Estimating the natural rates in a simple New Keynesian framework," Empirical Economics, Springer, vol. 40(3), pages 755-777, May.
    9. João Sousa Andrade & António Portugal Duarte, 2014. "Output-gaps in the PIIGS Economies: An Ingredient of a Greek Tragedy," GEMF Working Papers 2014-06, GEMF, Faculty of Economics, University of Coimbra.
    10. Wang, Pengfei & Wen, Yi, 2007. "Inflation dynamics: A cross-country investigation," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2004-2031, October.
    11. Henzel, Steffen & Hülsewig, Oliver & Mayer, Eric & Wollmershäuser, Timo, 2009. "The price puzzle revisited: Can the cost channel explain a rise in inflation after a monetary policy shock?," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 268-289, June.
    12. S. Boragan Aruoba & Frank Schorfheide, 2011. "Sticky Prices versus Monetary Frictions: An Estimation of Policy Trade-Offs," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(1), pages 60-90, January.
    13. Crucini, Mario J. & Shintani, Mototsugu & Tsuruga, Takayuki, 2010. "Accounting for persistence and volatility of good-level real exchange rates: The role of sticky information," Journal of International Economics, Elsevier, vol. 81(1), pages 48-60, May.
    14. McCallum, Bennett T., 2008. "Reconsideration of the P-bar model of gradual price adjustment," European Economic Review, Elsevier, vol. 52(8), pages 1480-1493, November.
    15. Carrillo, Julio A., 2012. "How well does sticky information explain the dynamics of inflation, output, and real wages?," Journal of Economic Dynamics and Control, Elsevier, vol. 36(6), pages 830-850.
    16. N. Gregory Mankiw & Ricardo Reis, 2007. "Sticky Information in General Equilibrium," Journal of the European Economic Association, MIT Press, vol. 5(2-3), pages 603-613, 04-05.
    17. Olivier Coibion & Yuriy Gorodnichenko & Mauricio Ulate, 2018. "The Cyclical Sensitivity in Estimates of Potential Output," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 49(2 (Fall)), pages 343-441.
    18. Benjamin D. Keen & Evan F. Koenig, 2018. "How Robust Are Popular Models of Nominal Frictions?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1299-1342, September.
    19. Maravall, Agustin, 2006. "An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustment," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2167-2190, May.

    More about this item

    Keywords

    Trend Output; Natural Output Level; Output Gap; Beveridge-Nelson Decomposition; Survey-based Expectations; New Keynesian Phillips Curve;
    All these keywords.

    JEL classification:

    • 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
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:lec:leecon:09/21. See general information about how to correct material in RePEc.

    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: Abbie Sleath (email available below). General contact details of provider: https://edirc.repec.org/data/deleiuk.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.