IDEAS home Printed from https://ideas.repec.org/p/mur/wpaper/4695.html
   My bibliography  Save this paper

Extending the New Keynesian Monetary Model with Information Revision Processes: Real-time and Revised Data

Author

Listed:
  • María-Dolores, Ramon
  • Vazquez, Jesus
  • Londoño, Juan M.

    (Departamentos y Servicios::Departamentos de la UMU::Fundamentos del Análisis Económico)

Abstract

This paper proposes an extended version of the New Keynesian Monetary (NKM) model which contemplates revision processes of output and inflation data in order to assess the influence of data revisions on the estimated monetary policy rule parameters. In line with the evidence provided by Aruoba (2008), by using the indirect inference principle, we observe that real-time data are not rational forecasts of revised data. This result along with the differences observed when estimating a model restricted to white noise revision processes provide evidence that policymakers decisions could be determined by the availability of data at the time of policy implementation.

Suggested Citation

  • María-Dolores, Ramon & Vazquez, Jesus & Londoño, Juan M., 2009. "Extending the New Keynesian Monetary Model with Information Revision Processes: Real-time and Revised Data," UMUFAE Economics Working Papers 4695, DIGITUM. Universidad de Murcia.
  • Handle: RePEc:mur:wpaper:4695
    as

    Download full text from publisher

    File URL: http://digitum.um.es/xmlui/bitstream/10201/4695/1/WPUMUFAE.2009.04.pdf?sequence=1
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
    2. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    3. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    4. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    5. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    6. English William B. & Nelson William R. & Sack Brian P., 2003. "Interpreting the Significance of the Lagged Interest Rate in Estimated Monetary Policy Rules," The B.E. Journal of Macroeconomics, De Gruyter, vol. 3(1), pages 1-18, April.
    7. Eric Ghysels & Norman R. Swanson & Myles Callan, 2002. "Monetary Policy Rules with Model and Data Uncertainty," Southern Economic Journal, John Wiley & Sons, vol. 69(2), pages 239-265, October.
    8. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
    9. Mariano,Roberto & Schuermann,Til & Weeks,Melvyn J. (ed.), 2000. "Simulation-based Inference in Econometrics," Cambridge Books, Cambridge University Press, number 9780521591126.
    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. Vázquez, Jesús & María-Dolores, Ramón & Londoño, Juan-Miguel, 2013. "On the informational role of term structure in the US monetary policy rule," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1852-1871.
    2. Vázquez, Jesús & María-Dolores, Ramón & Londoño, Juan M., 2012. "The Effect of Data Revisions on the Basic New Keynesian Model," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 235-249.
    3. Clements, Michael P. & Beatriz Galvão, Ana, 2010. "First announcements and real economic activity," European Economic Review, Elsevier, vol. 54(6), pages 803-817, August.
    4. Ramón María-Dolores & Jesús Vázquez, 2008. "Term structure and the estimated monetary policy rule in the Eurozone," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(4), pages 251-277, December.
    5. Casares, Miguel & Vázquez, Jesús, 2016. "Data Revisions In The Estimation Of Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 20(7), pages 1683-1716, October.
    6. Seth Pruitt, 2012. "Uncertainty Over Models and Data: The Rise and Fall of American Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44, pages 341-365, March.
    7. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    8. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    9. Ramón Maria-Dolores & Jesus Vazquez, 2006. "The relative importance of Term Spread, Policy Inertia and Persistent Monetary Policy Shocks in Monetary Policy Rules," Computing in Economics and Finance 2006 6, Society for Computational Economics.
    10. Christoffersen, Peter & Ghysels, Eric & Swanson, Norman R., 2002. "Let's get "real" about using economic data," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 343-360, August.
    11. Frederick H. Wallace & Gary L. Shelley & Luis F. Cabrera Castellanos, 2004. "Pruebas de la neutralidad monetaria a largo plazo: el caso de Nicaragua," Monetaria, CEMLA, vol. 0(4), pages 407-418, octubre-d.
    12. Brave, Scott A. & Gascon, Charles & Kluender, William & Walstrum, Thomas, 2021. "Predicting benchmarked US state employment data in real time," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1261-1275.
    13. Croushore, Dean & Evans, Charles L., 2006. "Data revisions and the identification of monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1135-1160, September.
    14. Clements, Michael P. & Beatriz Galvao, Ana, 2010. "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," Economic Research Papers 270771, University of Warwick - Department of Economics.
    15. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
    16. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    17. Corradi, Valentina & Fernandez, Andres & Swanson, Norman R., 2009. "Information in the Revision Process of Real-Time Datasets," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 455-467.
    18. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
    19. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    20. Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.

    More about this item

    Keywords

    NKM model; Monetary Policy Rule; Indirect Inference; Real-time Data; Rational Forecast Errors;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

    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:mur:wpaper:4695. 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: Francisco Monreal López (email available below). General contact details of provider: https://edirc.repec.org/data/fcmures.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.