Advanced Search
MyIDEAS: Login to save this paper or follow this series

Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence

Contents:

Author Info

  • Tierney, Heather L.R.

Abstract

The purpose of this paper is to examine the forecasting ability of sixty-two vintages of revised real-time PCE and core PCE using nonparametric methodologies. The combined fields of real-time data and nonparametric forecasting have not been previously explored with rigor, which this paper remedies. The contributions of this paper are on the three fronts of (i.) analysis of real-time data; (ii.) the additional benefits of using nonparametric econometrics to examine real-time data; and (iii.) nonparametric forecasting with real-time data. Regarding the analysis of real-time data revisions, this paper finds that the third quarter releases of real-time data have the largest number of data revisions. Secondly, nonparametric regressions are beneficial in utilizing the information provided by data revisions, which typically are just a few tenths in magnitude but are significant enough to statistically affect regression results. The deviations in window widths can be useful in identifying potential problematic time periods such as a large spike in oil prices. The third and final front of this paper regards nonparametric forecasting and the best performing real-time data release with the three local nonparametric forecasting methods outperforming the parametric benchmark forecasts. Lastly, this paper shows that the best performing quarterly-release of real-time data is dependent on the benchmark revision periods. For vintages 1996:Q1 to 2003:Q3, the second quarter real-time data releases produce the smaller RMSE 58% of the time and for vintages 2003:Q4 to 2011:Q2, the third quarter real-time data releases produce forecasts with smaller RMSE approximately 60% of the time.

Download Info

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://mpra.ub.uni-muenchen.de/51398/
File Function: original version
Download Restriction: no

Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 51398.

as in new window
Length:
Date of creation: 08 Nov 2013
Date of revision:
Handle: RePEc:pra:mprapa:51398

Contact details of provider:
Postal: Schackstr. 4, D-80539 Munich, Germany
Phone: +49-(0)89-2180-2219
Fax: +49-(0)89-2180-3900
Web page: http://mpra.ub.uni-muenchen.de
More information through EDIRC

Related research

Keywords: Nonparametric Forecasting; Real-Time Data; Monetary Policy; Inflation Persistence;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

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. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
  2. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, Elsevier, vol. 136(1), pages 163-188, January.
  3. Wolfgang HÄRDLE & A. TSYBAKOV, 1995. "Local Polynomial Estimators of the Volatility Function in Nonparametric Autoregression," SFB 373 Discussion Papers, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1995,42, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  4. Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 34(1), pages 94-113, February.
  5. William D. Nordhaus, 2011. "The Economics of Tail Events with an Application to Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 5(2), pages 240-257, Summer.
  6. Elliott, Graham, 2002. "Comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, Elsevier, vol. 24(4), pages 533-539, December.
  7. Gooijer, Jan G. De & Gannoun, Ali, 2000. "Nonparametric conditional predictive regions for time series," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 33(3), pages 259-275, May.
  8. Heather L. R. Tierney, 2012. "Examining the ability of core inflation to capture the overall trend of total inflation," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 44(4), pages 493-514, February.
  9. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, Econometric Society, vol. 48(4), pages 817-38, May.
  10. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, Elsevier, vol. 105(1), pages 111-130, November.
  11. Fujiwara, Ippei & Koga, Maiko, 2004. "A Statistical Forecasting Method for Inflation Forecasting: Hitting Every Vector Autoregression and Forecasting under Model Uncertainty," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, Institute for Monetary and Economic Studies, Bank of Japan, vol. 22(1), pages 123-142, March.
  12. Chauvet, Marcelle & Tierney, Heather L. R., 2007. "Real Time Changes in Monetary Policy," MPRA Paper 16199, University Library of Munich, Germany, revised Apr 2009.
  13. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, Elsevier, vol. 13(2), pages 281-291, June.
  14. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, Princeton University Press, edition 1, volume 1, number 8355.
  15. Barkoulas, John T. & Baum, Christopher F. & Onochie, Joseph, 1997. "A nonparametric investigation of the 90-day t-bill rate," Review of Financial Economics, Elsevier, Elsevier, vol. 6(2), pages 187-198.
  16. Marron, J S, 1988. "Automatic Smoothing Parameter Selection: A Survey," Empirical Economics, Springer, Springer, vol. 13(3/4), pages 187-208.
  17. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(1), pages 134-44, January.
  18. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 16(2), pages 254-59, April.
  19. Robert Rich & Charles Steindel, 2005. "A review of core inflation and an evaluation of its measures," Staff Reports, Federal Reserve Bank of New York 236, Federal Reserve Bank of New York.
Full references (including those not matched with items on IDEAS)

Citations

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:51398. 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: (Ekkehart Schlicht).

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.