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Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset

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  • Carlo Altavilla
  • Matteo Ciccarelli

Abstract

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 coefficients associated with small central bank losses, in particular during periods of high macroeconomic uncertainty.

Suggested Citation

  • Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
  • Handle: RePEc:ces:ceswps:_3372
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    1. 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, September.
    2. 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, January.
    3. Coenen, Gunter & Levin, Andrew & Wieland, Volker, 2005. "Data uncertainty and the role of money as an information variable for monetary policy," European Economic Review, Elsevier, vol. 49(4), pages 975-1006, May.
    4. 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.
    5. 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.
    6. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    7. 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.
    8. 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.
    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. Nikolsko-Rzhevskyy, Alex, 2008. "Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data," MPRA Paper 11352, University Library of Munich, Germany.
    11. 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.
    12. 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.
    13. Richard Dennis, 2006. "The policy preferences of the US Federal Reserve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 55-77.
    14. 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.
    15. Arturo Estrella & Jeffrey C. Fuhrer, 2003. "Monetary Policy Shifts and the Stability of Monetary Policy Models," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 94-104, February.
    16. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters, in: Monetary Policy Rules, pages 203-262, National Bureau of Economic Research, Inc.
    17. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    18. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    19. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    20. Taylor, John B. (ed.), 2001. "Monetary Policy Rules," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226791258, September.
    21. Altavilla, Carlo & Ciccarelli, Matteo, 2009. "The effects of monetary policy on unemployment dynamics under model uncertainty: evidence from the US and the euro area," Working Paper Series 1089, European Central Bank.
    22. 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.
    23. Aoki, Kosuke, 2003. "On the optimal monetary policy response to noisy indicators," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 501-523, April.
    24. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters, in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230, National Bureau of Economic Research, Inc.
    25. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    26. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    27. 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.
    28. 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.).
    29. 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 63-79, October.
    30. Rudebusch, Glenn D. & Svensson, Lars E. O., 2002. "Eurosystem monetary targeting: Lessons from U.S. data," European Economic Review, Elsevier, vol. 46(3), pages 417-442, March.
    31. Cateau, Gino, 2007. "Monetary policy under model and data-parameter uncertainty," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2083-2101, October.
    32. 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.
    33. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1.
    34. 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.
    35. Carlo Altavilla & Matteo Ciccarelli, 2009. "The Effects of Monetary Policy on Unemployment Dynamics under Model Uncertainty: Evidence from the United States and the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1265-1300, October.
    36. 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.
    37. Jacob A. Mincer, 1969. "Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance," NBER Books, National Bureau of Economic Research, Inc, number minc69-1.
    38. Glenn D. Rudebusch, 2001. "Is The Fed Too Timid? Monetary Policy In An Uncertain World," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 203-217, May.
    39. 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.
    40. Michael Woodford, 2003. "Optimal Interest-Rate Smoothing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(4), pages 861-886.
    41. 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.
    42. Patterson, K. D., 2003. "Exploiting information in vintages of time-series data," International Journal of Forecasting, Elsevier, vol. 19(2), pages 177-197.
    43. 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.
    44. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    45. 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.
    46. Orphanides, Athanasios, 2003. "Historical monetary policy analysis and the Taylor rule," Journal of Monetary Economics, Elsevier, vol. 50(5), pages 983-1022, July.
    47. Ciccarelli, Matteo & Altavilla, Carlo, 2007. "Information combination and forecast (st)ability evidence from vintages of time-series data," Working Paper Series 846, European Central Bank.
    48. 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.
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    Cited by:

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    2. Kenza Benhima & Céline Poilly, 2017. "Do Misperceptions about Demand Matter? Theory and Evidence," AMSE Working Papers 1717, Aix-Marseille School of Economics, France.
    3. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.

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    More about this item

    Keywords

    monetary policy; Taylor rule; real-time data; great moderation; forecasting;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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