IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/44484.html
   My bibliography  Save this paper

A Disaggregate Model and Second Round Effects for the CPI Inflation in Costa Rica

Author

Listed:
  • Leon, Jorge

Abstract

This paper estimates a medium-term forecasting model for the headline inflation of Costa Rica, utilizing disaggregate data from the components of the Consumer Price Index (CPI). The period used for the estimation is characterize by a process of reduction of inflation and stabilized around the Central Bank's inflation target. The result show that the use of disaggregate data is at least as good as the aggregate data in forecast accuracy. The disaggregate model allows to differentiate the inertia and the Second-Round effects present on the inflation.

Suggested Citation

  • Leon, Jorge, 2012. "A Disaggregate Model and Second Round Effects for the CPI Inflation in Costa Rica," MPRA Paper 44484, University Library of Munich, Germany, revised 2012.
    • Handle: RePEc:pra:mprapa:44484
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/44484/1/MPRA_paper_44484.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aigner, D.J. & Goldfeld, S.M., 1974. "Estimation and prediction from aggregate data when aggregates are measured more accurately than their components," LIDAM Reprints CORE 190, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
    3. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    4. Aigner, Dennis J & Goldfeld, Stephen M, 1974. "Estimation and Prediction from Aggregate Data when Aggregates are Measured More Accurately than Their Components," Econometrica, Econometric Society, vol. 42(1), pages 113-134, January.
    5. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    6. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    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. International Monetary Fund, 2015. "Cross-Country Report on Inflation: Selected Issues," IMF Staff Country Reports 2015/184, International Monetary Fund.

    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. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    2. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
    3. Edward E. Leamer, 1982. "Optimal Aggegation of Linear Systems," UCLA Economics Working Papers 240, UCLA Department of Economics.
    4. Monteforte, Libero, 2007. "Aggregation bias in macro models: Does it matter for the euro area?," Economic Modelling, Elsevier, vol. 24(2), pages 236-261, March.
    5. Ariel Pakes & Mark Schankerman, 1984. "An Exploration into the Determinants of Research Intensity," NBER Chapters, in: R&D, Patents, and Productivity, pages 209-232, National Bureau of Economic Research, Inc.
    6. M. Faruk Aydin & Ugur Ciplak & Eray M. Yucel, 2004. "Export Supply and Import Demand Models for the Turkish Economy," Working Papers 0409, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Giacomo Sbrana, 2007. "Testing for Model Selection in Predicting Aggregate Variables," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 66(1), pages 3-28, March.
    8. Shingal, Anirudh, 2007. "Examining responsiveness of India’s trade flows to exchange rate movements," MPRA Paper 32820, University Library of Munich, Germany, revised 18 Mar 2010.
    9. Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
    10. van Garderen, Kees Jan & Lee, Kevin & Pesaran, M. Hashem, 2000. "Cross-sectional aggregation of non-linear models," Journal of Econometrics, Elsevier, vol. 95(2), pages 285-331, April.
    11. Carson, Richard T. & Cenesizoglu, Tolga & Parker, Roger, 2011. "Forecasting (aggregate) demand for US commercial air travel," International Journal of Forecasting, Elsevier, vol. 27(3), pages 923-941.
    12. Bernardina Algieri, 2004. "Price and Income Elasticities of Russian Exports," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 1(2), pages 175-193, December.
    13. Jonathan Corcoran & Alan T. Murray & Robert J. Stimson, 2011. "Spatially Disaggregating Employment Growth Estimates," International Regional Science Review, , vol. 34(2), pages 138-156, April.
    14. Duncan Simester & Artem Timoshenko & Spyros I. Zoumpoulis, 2020. "Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges," Management Science, INFORMS, vol. 66(6), pages 2495-2522, June.
    15. Eisenhauer, Joseph G., 2008. "Ethical preferences, risk aversion, and taxpayer behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(1), pages 45-63, February.
    16. Roy E. Welsch & Edwin Kuh, 1974. "The Variances of Regression Coefficient Estimates Using Aggregate Data," NBER Working Papers 0060, National Bureau of Economic Research, Inc.
    17. Bahman Rostami‐Tabar & M. Zied Babai & Aris Syntetos & Yves Ducq, 2013. "Demand forecasting by temporal aggregation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(6), pages 479-498, September.
    18. Chen, Argon & Blue, Jakey, 2010. "Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands," International Journal of Production Economics, Elsevier, vol. 128(2), pages 586-602, December.
    19. Ariel Pakes, 1979. "Aggregation Effects And Panel Data Estimation Problems: An Investigationof the R&D Intensity Decision," NBER Working Papers 0344, National Bureau of Economic Research, Inc.
    20. Ronald Bewley & Thomas Parry, 1991. "Predicting the Monthly and Annual Current Account Balance from Provisional Data," The Economic Record, The Economic Society of Australia, vol. 67(4), pages 317-330, December.

    More about this item

    Keywords

    Inflation; Forecast; CPI; PPI; Second Round Effect.;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

    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:pra:mprapa:44484. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.