IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Real-time Prediction with UK Monetary Aggregates in the Presence of Model Uncertainty

  • Anthony Garratt

    (Department of Economics, Mathematics & Statistics, Birkbeck)

  • Gary Koop
  • Emi Mise
  • Shaun P Vahey

A popular account for the demise of the UK monetary targeting regime in the 1980s blames the weak predictive relationships between broad money and inflation and real output. In this paper, we investigate these relationships using a variety of monetary aggregates which were used as intermediate UK policy targets. We use both real-time and final vintage data and consider a large set of recursively estimated Vector Autoregressive (VAR) and Vector Error Correction models (VECM). These models differ in terms of lag length and the number of cointegrating relationships. Faced with this model uncertainty, we utilize Bayesian model averaging (BMA) and contrast it with a strategy of selecting a single best model. Using the real-time data available to UK policymakers at the time, we demonstrate that the in-sample predictive content of broad money fluctuates throughout the 1980s for both strategies. However, the strategy of choosing a single best model amplifies these fluctuations. Out-of-sample predictive evaluations rarely suggest that money matters for either inflation or real output, regardless of whether we select a single model or do BMA. Overall, we conclude that the money was a weak (and unreliable) predictor for these key macroeconomic variables. But the view that the predictive content of UK broad money diminished during the 1980s receives little support using either the real-time or final vintage data.

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:
File Function: First version, 2007
Download Restriction: no

Paper provided by Birkbeck, Department of Economics, Mathematics & Statistics in its series Birkbeck Working Papers in Economics and Finance with number 0714.

in new window

Date of creation: Sep 2007
Date of revision:
Handle: RePEc:bbk:bbkefp:0714
Contact details of provider: Postal:
Malet Street, London WC1E 7HX, UK

Phone: 44-20- 76316429
Fax: 44-20- 76316416
Web page:

Order Information: Email:

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. Pesaran, M.H. & Timmermann, A., 1990. "A Simple, Non-Parametric Test Of Predictive Performance," Cambridge Working Papers in Economics 9021, Faculty of Economics, University of Cambridge.
  2. Hylleberg, Svend & Mizon, Grayham E, 1989. "Cointegration and Error Correction Mechanisms," Economic Journal, Royal Economic Society, vol. 99(395), pages 113-25, Supplemen.
  3. Nickell, Stephen, 1985. "Error Correction, Partial Adjustment and All That: An Expository Note," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 47(2), pages 119-29, May.
  4. Martin Feldstein & James H. Stock, 1993. "The Use of Monetary Aggregate to Target Nominal GDP," NBER Working Papers 4304, National Bureau of Economic Research, Inc.
  5. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
  6. Lance J. Bachmeier & Norman R. Swanson, 2005. "Predicting Inflation: Does The Quantity Theory Help?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 570-585, July.
  7. Anthony Garratt & Gary Koop & ShaunP. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, 07.
  8. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
  9. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  10. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive Density Evaluation," Handbook of Economic Forecasting, Elsevier.
  11. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  12. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  13. Dean Croushore, 2006. "An evaluation of inflation forecasts from surveys using real-time data," Working Papers 06-19, Federal Reserve Bank of Philadelphia.
  14. Roberds, William & Whiteman, Charles H, 1992. "Monetary Aggregates as Monetary Targets: A Statistical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 24(2), pages 141-61, May.
  15. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
  16. Orphanides, Athanasios & Porter, Richard D., 2000. "P revisited: money-based inflation forecasts with a changing equilibrium velocity," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 87-100.
  17. Patterson, Kerry D & Heravi, Saeed M, 1991. "Data Revisions and the Expenditure Components of GDP," Economic Journal, Royal Economic Society, vol. 101(407), pages 887-901, July.
  18. Shaun Vahey & Tony Garratt, 2005. "UK Real-time Macro Data Characteristics," Computing in Economics and Finance 2005 253, Society for Computational Economics.
  19. Eric M. Leeper & Jennifer E. Roush, 2003. "Putting "M" back in monetary policy," Proceedings, Federal Reserve Bank of Cleveland, pages 1217-1264.
  20. Steel, M.F.J. & Richard, J.F., 1989. "Bayesian Multivariate Exogeneity Analysis: An Application To A Uk Money Demand Equation," Papers 8929, Tilburg - Center for Economic Research.
  21. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
  22. 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.
  23. Mills, Terence C, 1987. "Uncertainty in the U.K. Monetary Aggregates: Modelling Data Revisions in Economic Time Series," The Manchester School of Economic & Social Studies, University of Manchester, vol. 55(4), pages 337-52, December.
  24. Clark, Todd E. & McCracken, Michael W., 2009. "Tests of Equal Predictive Ability With Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 441-454.
  25. Athanasios Orphanides, 1998. "Monetary policy evaluation with noisy information," Finance and Economics Discussion Series 1998-50, Board of Governors of the Federal Reserve System (U.S.).
  26. Jon Faust & John H. Rogers & Jonathan H. Wright, 2000. "News and noise in G-7 GDP announcements," International Finance Discussion Papers 690, Board of Governors of the Federal Reserve System (U.S.).
  27. Lubrano, M. & Pierse, R.G. & Richard, J.-F., . "Stability of a U.K. money demand equation: a Bayesian approach to testing exogeneity," CORE Discussion Papers RP 712, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  28. David G. Blanchflower & Richard B. Freeman, 1993. "Did the Thatcher Reforms Change British Labour Performance?," NBER Working Papers 4384, National Bureau of Economic Research, Inc.
  29. David Card & Richard B. Freeman, 2002. "What Have Two Decades of British Economic Reform Delivered?," NBER Working Papers 8801, National Bureau of Economic Research, Inc.
  30. 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.
  31. Hall, S. G. & Henry, S. G. B., 1986. "A dynamic econometric model of the UK with rational expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 10(1-2), pages 219-223, June.
  32. Shaun P. Vahey & Andreas Pick & Don M. Egginton, 2001. ""Keep it real!": A real-time UK macro data set," Economics Bulletin, AccessEcon, vol. 28(18), pages A0.
  33. Stock, James H. & Watson, Mark W., 1989. "Interpreting the evidence on money-income causality," Journal of Econometrics, Elsevier, vol. 40(1), pages 161-181, January.
  34. 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.).
  35. Jurgen A. Doornik & David F. Hendry & Bent Nielsen, 1998. "Inference in Cointegrating Models: UK M1 Revisited," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 533-572, December.
  36. Dean Croushore & Charles L. Evans, 2000. "Data Revisions and the Identification of Monetary Policy Shocks," Econometric Society World Congress 2000 Contributed Papers 0842, Econometric Society.
  37. repec:cup:etheor:v:11:y:1995:i:3:p:530-36 is not listed on IDEAS
  38. Inoue, Atsushi & Kilian, Lutz, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers 3671, C.E.P.R. Discussion Papers.
  39. Edward Nelson, 2004. "The U.K.’s rocky road to stability," Monetary Trends, Federal Reserve Bank of St. Louis, issue Oct.
  40. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
  41. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
  42. Friedman, Benjamin M & Kuttner, Kenneth N, 1992. "Money, Income, Prices, and Interest Rates," American Economic Review, American Economic Association, vol. 82(3), pages 472-92, June.
  43. Todd E. Clark & Michael W. McCracken, 2003. "The predictive content of the output gap for inflation : resolving in-sample and out-of-sample evidence," Research Working Paper RWP 03-06, Federal Reserve Bank of Kansas City.
  44. Norman R. Swanson & Jeffery D. Amato, 2000. "The real-time predictive content of money for output," BIS Working Papers 96, Bank for International Settlements.
  45. Norman Swanson & Nii Ayi Armah, 2006. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 200619, Rutgers University, Department of Economics.
  46. Clive, W.J. & Lin, Jin-Lung, 1995. "Causality in the Long Run," Econometric Theory, Cambridge University Press, vol. 11(03), pages 530-536, June.
  47. Valentina Corradi & Andres Fernandez & Norman R. Swanson, 2008. "Information in the revision process of real-time datasets," Working Papers 08-27, Federal Reserve Bank of Philadelphia.
  48. Rossi, Barbara & Inoue, Atsushi, 2003. "Recursive Predictability Tests for Real-Time Data," Working Papers 03-24, Duke University, Department of Economics.
  49. 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.
  50. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  51. Swanson, Norman R., 1998. "Money and output viewed through a rolling window," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 455-474, May.
  52. 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.
  53. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  54. Patterson, Kerry, 2002. "The Data Measurement Process for UK GNP: Stochastic Trends, Long Memory, and Unit Roots," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(4), pages 245-64, July.
  55. Howrey, E Philip, 1978. "The Use of Preliminary Data in Econometric Forecasting," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 193-200, May.
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:bbk:bbkefp:0714. 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: ()

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.