IDEAS home Printed from https://ideas.repec.org/p/bbv/wpaper/1534.html
   My bibliography  Save this paper

The evasive predictive ability of core inflation

Author

Listed:
  • Jose Luis Nolazco
  • Pablo Pincheira
  • Jorge Selaive

Abstract

We explore the ability of traditional core inflation –consumer prices excluding food and energy–to predict headline CPI annual inflation. We analyze a sample of OECD and non-OECD economies using monthly data from January 1994 to March 2015. Our results indicate that sizable predictability emerges for a small subset of countries.

Suggested Citation

  • Jose Luis Nolazco & Pablo Pincheira & Jorge Selaive, 2016. "The evasive predictive ability of core inflation," Working Papers 15/34, BBVA Bank, Economic Research Department.
    • Handle: RePEc:bbv:wpaper:1534
    as

    Download full text from publisher

    File URL: https://www.bbvaresearch.com/wp-content/uploads/2016/01/WP15-34_Core-Inflation.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    2. Pablo Pincheira & Andrés Gatty, 2016. "Forecasting Chilean inflation with international factors," Empirical Economics, Springer, vol. 51(3), pages 981-1010, November.
    3. James H. Stock & Mark W. Watson, 2016. "Core Inflation and Trend Inflation," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 770-784, October.
    4. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    5. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
    6. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    7. Michael P. Clements & David F.Hendry, 2001. "Forecasting with difference-stationary and trend-stationary models," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-19.
    8. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    9. Freeman, Donald G., 1998. "Do core inflation measures help forecast inflation?," Economics Letters, Elsevier, vol. 58(2), pages 143-147, February.
    10. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    11. Alan S. Blinder & Ricardo Reis, 2005. "Understanding the Greenspan standard," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, issue Aug, pages 11-96.
    12. Olivier Blanchard & Giovanni Dell'Ariccia & Paolo Mauro, 2010. "Rethinking Macroeconomic Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(s1), pages 199-215, September.
    13. Julie K. Smith, 2012. "PCE inflation and core inflation," Working Papers 1203, Federal Reserve Bank of Dallas.
    14. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    15. Theodore M. Crone & N. Neil K. Khettry & Loretta J. Mester & Jason A. Novak, 2013. "Core Measures of Inflation as Predictors of Total Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2‐3), pages 505-519, March.
    16. Lei Lei Song, 2005. "Do underlying measures of inflation outperform headline rates? Evidence from Australian data," Applied Economics, Taylor & Francis Journals, vol. 37(3), pages 339-345.
    17. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    18. Pablo M. Pincheira & Carlos A. Medel, 2015. "Forecasting Inflation with a Simple and Accurate Benchmark: The Case of the US and a Set of Inflation Targeting Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 2-29, January.
    19. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    20. Alan S. Blinder & Ricardo Reis, 2005. "Understanding the Greenspan standard," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, issue Aug, pages 11-96.
    21. 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.
    22. repec:mcb:jmoncb:v:45:y:2013:i::p:505-519 is not listed on IDEAS
    23. Colin Bermingham, 2007. "How Useful is Core Inflation for Forecasting Headline Inflation?," The Economic and Social Review, Economic and Social Studies, vol. 38(3), pages 355-377.
    24. N. Neil K. Khettry & Loretta J. Mester, 2006. "Core inflation as a predictor of total inflation," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Apr.
    25. Brent Meyer & Mehmet Pasaogullari, 2010. "Simple ways to forecast inflation: what works best?," Economic Commentary, Federal Reserve Bank of Cleveland, issue Dec.
    26. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    27. Michael T. Kiley, 2008. "Estimating the common trend rate of inflation for consumer prices and consumer prices excluding food and energy prices," Finance and Economics Discussion Series 2008-38, Board of Governors of the Federal Reserve System (U.S.).
    28. Le Bihan, Herve & Sedillot, Franck, 2000. "Do core inflation measures help forecast inflation?: Out-of-sample evidence from French data," Economics Letters, Elsevier, vol. 69(3), pages 261-266, December.
    29. Olivier Blanchard & Giovanni Dell'Ariccia & Paolo Mauro, 2010. "Rethinking Macroeconomic Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(s1), pages 199-215, September.
    30. Pablo Pincheira & Carlos Medel, 2012. "Forecasting Inflation With a Random Walk," Working Papers Central Bank of Chile 669, Central Bank of Chile.
    31. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    2. Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023. "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, vol. 3(1), pages 1-32, January.
    3. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    2. Pablo Pincheira & Andrés Gatty, 2016. "Forecasting Chilean inflation with international factors," Empirical Economics, Springer, vol. 51(3), pages 981-1010, November.
    3. Pincheira, Pablo & Hardy, Nicolas, 2022. "Correlation Based Tests of Predictability," MPRA Paper 112014, University Library of Munich, Germany.
    4. Matheson, Troy D., 2008. "Phillips curve forecasting in a small open economy," Economics Letters, Elsevier, vol. 98(2), pages 161-166, February.
    5. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    6. Carlos A. Medel & Michael Pedersen & Pablo M. Pincheira, 2016. "The Elusive Predictive Ability of Global Inflation," International Finance, Wiley Blackwell, vol. 19(2), pages 120-146, June.
    7. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    8. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    9. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
    10. Pablo Pincheira Brown, 2022. "A Power Booster Factor for Out-of-Sample Tests of Predictability," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 45(89), pages 150-183.
    11. Granziera, Eleonora & Hubrich, Kirstin & Moon, Hyungsik Roger, 2014. "A predictability test for a small number of nested models," Journal of Econometrics, Elsevier, vol. 182(1), pages 174-185.
    12. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    13. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    14. Pablo M. Pincheira & Carlos A. Medel, 2016. "Forecasting with a Random Walk," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 539-564, December.
    15. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    16. Kirstin Hubrich & Kenneth D. West, 2010. "Forecast evaluation of small nested model sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 574-594.
    17. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
    18. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    19. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    20. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.

    More about this item

    Keywords

    Chile ; Economic Analysis ; Working Paper;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bbv:wpaper:1534. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSCAR DE LAS PENAS SANCHEZ-CARO (email available below). General contact details of provider: https://edirc.repec.org/data/ebbvaes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.