Examining the ability of core inflation to capture the overall trend of total inflation
AbstractThis article examines whether core inflation is able to predict the overall trend of total inflation using real-time data in a parametric and nonparametric framework. Specifically, two sample periods and five in-sample forecast horizons in two measures of inflation, which are the Personal Consumption Expenditure (PCE) and the Consumer Price Index (CPI), are used in the exclusions-from-core inflation persistence model. This article finds that core inflation is only able to capture the overall trend of total inflation for the 12-quarter in-sample forecast horizon using the CPI in both the parametric and nonparametric models in the longer sample period. The nonparametric model outperforms the parametric model for both data samples and for all five in-sample forecast horizons.
Download InfoIf 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.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 44 (2012)
Issue (Month): 4 (February)
Contact details of provider:
Web page: http://www.tandfonline.com/RAEC20
Other versions of this item:
- Tierney, Heather L.R., 2009. "Examining the Ability of Core Inflation to Capture the Overall Trend of Total Inflation," MPRA Paper 22409, University Library of Munich, Germany, revised Feb 2010.
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
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.:
- Jianqing Fan & Qiwei Yao, 1998. "Efficient estimation of conditional variance functions in stochastic regression," LSE Research Online Documents on Economics 6635, London School of Economics and Political Science, LSE Library.
- Robert Rich & Charles Steindel, 2005. "A review of core inflation and an evaluation of its measures," Staff Reports 236, Federal Reserve Bank of New York.
- Zongwu Cai & Jianqing Fan & Qiwei Yao, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
- Hardle, W., 1992.
"Applied Nonparametric Methods,"
1992-6, Tilburg University, Center for Economic Research.
- HÄRDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9206, Tilburg - Center for Economic Research.
- Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
- Hardle, W., 1992. "Applied Nonparametric Methods," Papers 9204, Catholique de Louvain - Institut de statistique.
- Marron, J S, 1988. "Automatic Smoothing Parameter Selection: A Survey," Empirical Economics, Springer, vol. 13(3/4), pages 187-208.
- Joseph E. Gagnon, 2008.
"Inflation regimes and inflation expectations,"
Federal Reserve Bank of St. Louis, issue May, pages 229-243.
- Joseph E. Gagnon, 1997. "Inflation Regimes and Inflation Expectations," RBA Research Discussion Papers rdp9701, Reserve Bank of Australia.
- Joseph E. Gagnon, 1997. "Inflation regimes and inflation expectations," International Finance Discussion Papers 581, Board of Governors of the Federal Reserve System (U.S.).
- Michael Creel & Dennis Kristensen, 2009.
"Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments,"
UFAE and IAE Working Papers
792.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
- Michael Creel & Dennis Kristensen, 2012. "Estimation of dynamic latent variable models using simulated non‐parametric moments," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 490-515, October.
- Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
- Oliver LINTON, .
"Applied nonparametric methods,"
Statistic und Oekonometrie
9312, Humboldt Universitaet Berlin.
- Jushan Bai, 1995.
"Estimating Multiple Breaks One at a Time,"
95-18, Massachusetts Institute of Technology (MIT), Department of Economics.
- Dean Croushore, 2008. "Revisions to PCE inflation measures: implications for monetary policy," Working Papers 08-8, Federal Reserve Bank of Philadelphia.
- Elliott, Graham, 2002. "Comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 533-539, December.
- Croushore, Dean & Stark, Tom, 2001.
"A real-time data set for macroeconomists,"
Journal of Econometrics,
Elsevier, vol. 105(1), pages 111-130, November.
- Florian Hoppner & Christian Melzer & Thorsten Neumann, 2008. "Changing effects of monetary policy in the US-evidence from a time-varying coefficient VAR," Applied Economics, Taylor & Francis Journals, vol. 40(18), pages 2353-2360.
- Thérèse Laf;èche & Jamie Armour, 2006. "Evaluating Measures of Core Inflation," Bank of Canada Review, Bank of Canada, vol. 2006(Summer), pages 19-29.
- 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, vol. 22(1), pages 123-142, March.
- Wolfgang HÄRDLE & A. TSYBAKOV, 1995.
"Local Polynomial Estimators of the Volatility Function in Nonparametric Autoregression,"
SFB 373 Discussion Papers
1995,42, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Hardle, W. & Tsybakov, A., 1997. "Local polynomial estimators of the volatility function in nonparametric autoregression," Journal of Econometrics, Elsevier, vol. 81(1), pages 223-242, November.
- Chauvet, Marcelle & Tierney, Heather L. R., 2007. "Real Time Changes in Monetary Policy," MPRA Paper 16199, University Library of Munich, Germany, revised Apr 2009.
- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
- P. M. Robinson, 1998. "Inference-Without-Smoothing in the Presence of Nonparametric Autocorrelation," Econometrica, Econometric Society, vol. 66(5), pages 1163-1182, September.
- Kozicki, Sharon, 2002. "Comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 541-557, December.
- Tristen Hayfield & Jeffrey S. Racine, . "Nonparametric Econometrics: The np Package," Journal of Statistical Software, American Statistical Association, vol. 27(i05).
- Cogley, Timothy, 2002. "A Simple Adaptive Measure of Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 94-113, February.
- Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
- Tierney, Heather L.R., 2013.
"Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence,"
51398, University Library of Munich, Germany.
- Tierney, Heather L.R., 2011. "Forecasting and tracking real-time data revisions in inflation persistence," MPRA Paper 34439, University Library of Munich, Germany.
- Tierney, Heather L.R., 2013. "Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence," MPRA Paper 53374, University Library of Munich, Germany, revised Nov 2013.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.