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

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

A popular account for the demise of the UK’s monetary targeting regime in the 1980s blames the fluctuating predictive relationships between broad money and inflation and real output growth. Yet ex post policy analysis based on heavily-revised data suggests no fluctuations in the predictive content of money. In this paper, we investigate the predictive relationships for inflation and output growth using both real-time and heavily-revised data. We 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. We use Bayesian model averaging (BMA) to demonstrate that real-time monetary policymakers faced considerable model uncertainty. The in-sample predictive content of money fluctuated during the 1980s as a result of data revisions in the presence of model uncertainty. This feature is only apparent with real-time data as heavily-revised data obscure these fluctuations. Out of sample predictive evaluations rarely suggest that money matters for either inflation or real output. We conclude that both data revisions and model uncertainty contributed to the demise of the UK’s monetary targeting regime. Classification-C11, C32, C53, E51, E52

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.rbnz.govt.nz/-/media/ReserveBank/Files/Publications/Discussion%20papers/2008/dp08-13.pdf
Download Restriction: no

Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number DP2008/13.

as
in new window

Length: 26 p.
Date of creation: Aug 2008
Date of revision:
Handle: RePEc:nzb:nzbdps:2008/13
Contact details of provider: Postal:
P.O. Box 2498, Wellington

Phone: 64 4 471-3767
Fax: 64 4 471-2270
Web page: http://www.rbnz.govt.nz
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. Lance J. Bachmeier & Norman R. Swanson, 2003. "Predicting Inflation: Does The Quantity Theory Help?," Departmental Working Papers 200317, Rutgers University, Department of Economics.
  2. David Card & Richard B. Freeman, 2004. "What Have Two Decades of British Economic Reform Delivered?," NBER Chapters, in: Seeking a Premier Economy: The Economic Effects of British Economic Reforms, 1980-2000, pages 9-62 National Bureau of Economic Research, Inc.
  3. M. Lubrano & R. G. Pierse & J.-F. Richard, 1986. "Stability of a U.K. Money Demand Equation: A Bayesian Approach to Testing Exogeneity," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 603-634.
  4. Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics 9804001, EconWPA, revised 31 Jul 1999.
  5. 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.
  6. 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.
  7. 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.
  8. Dean Croushore & Charles L. Evans, 2003. "Data revisions and the identification of monetary policy shocks," Working Papers 03-1, Federal Reserve Bank of Philadelphia.
  9. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-19, June.
  10. Todd E. Clark & Michael W. McCracken, 2008. "Tests of equal predictive ability with real-time data," Working Papers 2008-029, Federal Reserve Bank of St. Louis.
  11. Anthony Garratt & Shaun P Vahey, 2006. "UK Real-Time Macro Data Characteristics," Economic Journal, Royal Economic Society, vol. 116(509), pages F119-F135, 02.
  12. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  13. 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.
  14. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  15. 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.
  16. 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.
  17. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  18. Athanasios Orphanides & Richard D. Porter, 1998. "P* revisited: money-based inflation forecasts with a changing equilibrium velocity," Finance and Economics Discussion Series 1998-26, Board of Governors of the Federal Reserve System (U.S.).
  19. 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.).
  20. Inoue, Atsushi & Kilian, Lutz, 2002. "In-sample or out-of-sample tests of predictability: which one should we use?," Working Paper Series 0195, European Central Bank.
  21. Hylleberg, Svend & Mizon, Grayham E, 1989. "Cointegration and Error Correction Mechanisms," Economic Journal, Royal Economic Society, vol. 99(395), pages 113-25, Supplemen.
  22. Anthony Garratt & Gary Koop & Shaun P. Vahey, 2006. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Birkbeck Working Papers in Economics and Finance 0617, Birkbeck, Department of Economics, Mathematics & Statistics.
  23. 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.
  24. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
  25. 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.
  26. 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.
  27. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
  28. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  29. Valentina Corradi & Norman Swanson, 2004. "Predictive Density Evaluation," Departmental Working Papers 200419, Rutgers University, Department of Economics.
  30. 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.
  31. 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.
  32. Egginton, Don M. & Pick, Andreas & Vahey, Shaun P., 2002. "'Keep it real!': a real-time UK macro data set," Economics Letters, Elsevier, vol. 77(1), pages 15-20, September.
  33. Dean Croushore, 2006. "An evaluation of inflation forecasts from surveys using real-time data," Working Papers 06-19, Federal Reserve Bank of Philadelphia.
  34. 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.
  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. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-65, October.
  37. 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.
  38. 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.
  39. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
  40. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  41. Clive, W.J. & Lin, Jin-Lung, 1995. "Causality in the Long Run," Econometric Theory, Cambridge University Press, vol. 11(03), pages 530-536, June.
  42. Norman R. Swanson & Jeffery D. Amato, 2000. "The real-time predictive content of money for output," BIS Working Papers 96, Bank for International Settlements.
  43. 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.
  44. 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.
  45. repec:cup:etheor:v:11:y:1995:i:3:p:530-36 is not listed on IDEAS
  46. 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.
  47. Swanson, Norman R., 1998. "Money and output viewed through a rolling window," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 455-474, May.
  48. 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.
  49. Rossi, Barbara & Inoue, Atsushi, 2003. "Recursive Predictability Tests for Real-Time Data," Working Papers 03-24, Duke University, Department of Economics.
  50. Eric M. Leeper & Jennifer E. Roush, 2003. "Putting 'M' back in Monetary Policy," NBER Working Papers 9552, National Bureau of Economic Research, Inc.
  51. Nicoletta Batini & Edward Nelson, 2005. "The U.K.'s rocky road to stability," Working Papers 2005-020, Federal Reserve Bank of St. Louis.
  52. 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.
  53. 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.
  54. 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.
  55. 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.
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:nzb:nzbdps:2008/13. 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: (Reserve Bank of New Zealand Knowledge Centre)

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.