IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Monetary Policy Analysis in Real-Time. Vintage combination from a real-time dataset

  • Carlo Altavilla

    ()

    (University of Naples Parthenope and CSEF)

  • Matteo Ciccarelli

    ()

    (European Central Bank)

This paper provides a general strategy for analyzing monetary policy in real time which accounts for data uncertainty without explicitly modelling the revision process. The strategy makes use of all the data available from a real-time data matrix and averages model estimates across all data releases. Using standard forecasting and policy models to analyze monetary authorities’ reaction functions, we show that this simple method can improve forecasting performance and provide reliable estimates of the policy model coe¢cients associated with small central bank losses, in particular during periods of high macroeconomic uncertainty.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.csef.it/WP/wp274.pdf
Download Restriction: no

Paper provided by Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy in its series CSEF Working Papers with number 274.

as
in new window

Length:
Date of creation: 20 Feb 2011
Date of revision:
Handle: RePEc:sef:csefwp:274
Contact details of provider: Postal: I-80126 Napoli
Phone: +39 081 - 675372
Fax: +39 081 - 675372
Web page: http://www.csef.it/
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Swanson, Norman R. & van Dijk, Dick, 2006. "Are Statistical Reporting Agencies Getting It Right? Data Rationality and Business Cycle Asymmetry," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 24-42, January.
  2. Rudebusch, Glenn D & Svensson, Lars E O, 2000. "Eurosystem Monetary Targeting: Lessons from US Data," CEPR Discussion Papers 2522, C.E.P.R. Discussion Papers.
  3. James H. Stock & Mark W. Watson, 2002. "Has the Business Cycle Changed and Why?," NBER Working Papers 9127, National Bureau of Economic Research, Inc.
  4. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
  5. Coenen, Guenter & Levin, Andrew & Wieland, Volker, 2003. "Data Uncertainty and the Role of Money as an Information Variable for Monetary Policy," CFS Working Paper Series 2003/07, Center for Financial Studies (CFS).
  6. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  7. J. Tetlow, Robert & von zur Muehlen, Peter, 2001. "Robust monetary policy with misspecified models: Does model uncertainty always call for attenuated policy?," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 911-949, June.
  8. Norman R. Swanson & Valentina Corradi & Andres Fernandez, 2011. "Information in the Revision Process of Real-Time Datasets," Departmental Working Papers 201107, Rutgers University, Department of Economics.
  9. Taylor, John B. & Williams, John C., 2010. "Simple and Robust Rules for Monetary Policy," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 15, pages 829-859 Elsevier.
  10. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
  11. Svensson, Lars E.O. & Rudebusch , Glenn, 1998. "Policy Rules for Inflation Targeting," Seminar Papers 637, Stockholm University, Institute for International Economic Studies.
  12. Guerrero, Victor M., 1993. "Combining historical and preliminary information to obtain timely time series data," International Journal of Forecasting, Elsevier, vol. 9(4), pages 477-485, December.
  13. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  14. Altavilla, Carlo & Ciccarelli, Matteo, 2007. "Information combination and forecast (st)ability evidence from vintages of time-series data," Working Paper Series 0846, European Central Bank.
  15. Brock, William A. & Durlauf, Steven N. & West, Kenneth D., 2007. "Model uncertainty and policy evaluation: Some theory and empirics," Journal of Econometrics, Elsevier, vol. 136(2), pages 629-664, February.
  16. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, 03.
  17. Orphanides, Athanasios, 2003. "Historical monetary policy analysis and the Taylor rule," Journal of Monetary Economics, Elsevier, vol. 50(5), pages 983-1022, July.
  18. Todd E. Clark & Michael W. McCracken, 2007. "Forecasting with small macroeconomic VARs in the presence of instabilities," Finance and Economics Discussion Series 2007-41, Board of Governors of the Federal Reserve System (U.S.).
  19. Boschen, John F. & Grossman, Herschel I., 1982. "Tests of equilibrium macroeconomics using contemporaneous monetary data," Journal of Monetary Economics, Elsevier, vol. 10(3), pages 309-333.
  20. Glenn D. Rudebusch, 1999. "Is the Fed too timid? Monetary policy in an uncertain world," Working Papers in Applied Economic Theory 99-05, Federal Reserve Bank of San Francisco.
  21. Pierre Siklos, 2006. "What Can We Learn from Comprehensive Data Revisions for Forecasting Inflation: Some US Evidence," Working Papers eg0049, Wilfrid Laurier University, Department of Economics, revised 2006.
  22. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
  23. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  24. 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.
  25. Richard Dennis, 2001. "The policy preferences of the U.S. Federal Reserve," Working Paper Series 2001-08, Federal Reserve Bank of San Francisco.
  26. Christian Jensen & Bennett T. Mccallum, 2010. "Optimal Continuation versus the Timeless Perspective in Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(6), pages 1093-1107, 09.
  27. Athanasios Orphanides & Simon van Norden, 1999. "The reliability of output gap estimates in real time," Finance and Economics Discussion Series 1999-38, Board of Governors of the Federal Reserve System (U.S.).
  28. Altavilla, Carlo & Ciccarelli, Matteo, 2010. "Evaluating the effect of monetary policy on unemployment with alternative inflation forecasts," Economic Modelling, Elsevier, vol. 27(1), pages 237-253, January.
  29. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.
  30. Cateau, Gino, 2007. "Monetary policy under model and data-parameter uncertainty," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2083-2101, October.
  31. Aoki, Kosuke, 2003. "On the optimal monetary policy response to noisy indicators," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 501-523, April.
  32. Patterson, K. D., 2003. "Exploiting information in vintages of time-series data," International Journal of Forecasting, Elsevier, vol. 19(2), pages 177-197.
  33. Schwartz, Anna J., 2003. "Comment on: Historical monetary policy analysis and the Taylor rule," Journal of Monetary Economics, Elsevier, vol. 50(5), pages 1023-1027, July.
  34. Robert J. Tetlow & Brian Ironside, 2007. "Real-Time Model Uncertainty in the United States: The Fed, 1996-2003," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1533-1561, October.
  35. Dean Croushore & Tom Stark, 1999. "A real-time data set for marcoeconomists: does the data vintage matter?," Working Papers 99-21, Federal Reserve Bank of Philadelphia.
  36. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages S63-S79, October.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:sef:csefwp:274. 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: (Lia Ambrosio)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.