IDEAS home Printed from https://ideas.repec.org/p/cte/wsrepe/24678.html
   My bibliography  Save this paper

22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis

Author

Listed:
  • Espasa, Antoni
  • Senra, Eva

Abstract

The Bulletin of EU & US Inflation and Macroeconomic Analysis (BIAM) is a monthly publication that has been reporting real time analysis and forecasts for inflation and other macroeconomic aggregates for the Euro Area, the US and Spain since 1994. The BIAM inflation forecasting methodology stands on working with useful disaggregation schemes, using leading indicators when possible and applying outliers' correction. The paper relates this methodology to corresponding topics in the literature and discusses the design of disaggregation schemes. It concludes that those schemes would be useful if they were formulated according to economic, institutional and statistical criteria aiming to end up with a set of components with very different statistical properties for which valid single-equation models could be built. The BIAM assessment, which derives from a new observation, is based on (a) an evaluation of the forecasting errors (innovations) at the components' level. It provides information on which sectors they come from and allows, when required, for the appropriate correction in the specific models. (b) In updating the path forecast with its corresponding fan chart. Finally, we show that BIAM real time Euro Area inflation forecasts compare successfully with the consensus from the ECB Survey of Professional Forecasters, one and two years ahead.

Suggested Citation

  • Espasa, Antoni & Senra, Eva, 2017. "22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis," DES - Working Papers. Statistics and Econometrics. WS 24678, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:24678
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/bitstream/handle/10016/24678/ws201715.pdf?sequence=1
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
    2. Athanasopoulos, George & Ahmed, Roman A. & Hyndman, Rob J., 2009. "Hierarchical forecasts for Australian domestic tourism," International Journal of Forecasting, Elsevier, vol. 25(1), pages 146-166.
    3. Espasa, Antoni & Mayo-Burgos, Iván, 2013. "Forecasting aggregates and disaggregates with common features," International Journal of Forecasting, Elsevier, vol. 29(4), pages 718-732.
    4. Jean Boivin & Marc P. Giannoni & Ilian Mihov, 2009. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," American Economic Review, American Economic Association, vol. 99(1), pages 350-384, March.
    5. Dreger, Christian & Marcellino, Massimiliano, 2007. "A macroeconometric model for the Euro economy," Journal of Policy Modeling, Elsevier, vol. 29(1), pages 1-13.
    6. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    7. Cuevas Ángel & Quilis Enrique M. & Espasa Antoni, 2015. "Quarterly Regional GDP Flash Estimates by Means of Benchmarking and Chain Linking," Journal of Official Statistics, Sciendo, vol. 31(4), pages 627-647, December.
    8. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    9. Guenter W. Beck & Kirstin Hubrich & Massimiliano Marcellino, 2016. "On the Importance of Sectoral and Regional Shocks for Price‐Setting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1234-1253, November.
    10. Kenny, Geoff & Genre, Véronique & Bowles, Carlos & Friz, Roberta & Meyler, Aidan & Rautanen, Tuomas, 2007. "The ECB survey of professional forecasters (SPF) - A review after eight years' experience," Occasional Paper Series 59, European Central Bank.
    11. Jurgen A. Doornik & David F. Hendry, 2016. "Outliers and Model Selection: Discussion of the Paper by Søren Johansen and Bent Nielsen," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 360-365, June.
    12. Mojon, Benoît & Altissimo, Filippo & Zaffaroni, Paolo, 2007. "Fast micro and slow macro: can aggregation explain the persistence of inflation?," Working Paper Series 729, European Central Bank.
    13. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    14. Antoni Espasa & Rebeca Albacete, 2007. "Econometric modelling for short-term inflation forecasting in the euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 303-316.
    15. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587, July.
    16. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
    17. Espasa, Antoni & Llanos Matea, Maria de los, 1991. "Underlying inflation in the spanish economy: estimation and methodology," UC3M Working papers. Economics 2817, Universidad Carlos III de Madrid. Departamento de Economía.
    18. Aron, Janine & Muellbauer, John, 2012. "Improving forecasting in an emerging economy, South Africa: Changing trends, long run restrictions and disaggregation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 456-476.
    19. Carlos Bowles & Roberta Friz & Veronique Genre & Geoff Kenny & Aidan Meyler & Tuomas Rautanen, 2010. "An Evaluation of the Growth and Unemployment Forecasts in the ECB Survey of Professional Forecasters," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-28.
    20. Carlomagno, Guillermo & Espasa, Antoni, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    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. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.

    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. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, vol. 5(4), pages 1-28, October.
    2. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Carlomagno, Guillermo & Espasa, Antoni, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Carlomagno, Guillermo & Espasa, Antoni, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Guillermo Carlomagno & Nicolas Eterovic & L. G. Hernández-Román, 2023. "Disentangling Demand and Supply Inflation Shocks from Chilean Electronic Payment Data," Working Papers Central Bank of Chile 986, Central Bank of Chile.
    6. Pilar Poncela & Eva Senra, 2017. "Measuring uncertainty and assessing its predictive power in the euro area," Empirical Economics, Springer, vol. 53(1), pages 165-182, August.
    7. Simone Elmer & Thomas Maag, 2009. "The Persistence of Inflation in Switzerland," KOF Working papers 09-235, KOF Swiss Economic Institute, ETH Zurich.
    8. Wu, Zhang & Chong, Terence Tai-Leung, 2019. "Price rigidity in China: Empirical results at home and abroad," China Economic Review, Elsevier, vol. 55(C), pages 218-235.
    9. Terence Tai Leung Chong & M. S. Rafiq & Tingting Juni Zhu & Zhang Wu, 2019. "Are Prices Sticky In Large Developing Economies? An Empirical Comparison Of China And India," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(02), pages 341-363, March.
    10. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    11. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    12. Pino, Gabriel & Tena Horrillo, Juan de Dios & Espasa, Antoni, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2013. "International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(5), pages 913-932, August.
    14. Matteo G. Richiardi & Luis Valenzuela, 2024. "Firm heterogeneity and the aggregate labour share," LABOUR, CEIS, vol. 38(1), pages 66-101, March.
    15. Cantelmo, Alessandro & Melina, Giovanni, 2018. "Monetary policy and the relative price of durable goods," Journal of Economic Dynamics and Control, Elsevier, vol. 86(C), pages 1-48.
    16. Alex Nikolsko‐Rzhevskyy & Oleksandr Talavera & Nam Vu, 2023. "The flood that caused a drought," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 965-981, October.
    17. Jean Boivin & Marc P. Giannoni & Ilian Mihov, 2009. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," American Economic Review, American Economic Association, vol. 99(1), pages 350-384, March.
    18. Andrade, Philippe & Zachariadis, Marios, 2016. "Global versus local shocks in micro price dynamics," Journal of International Economics, Elsevier, vol. 98(C), pages 78-92.
    19. repec:prg:jnlpep:v:preprint:id:640:p:1-18 is not listed on IDEAS
    20. Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
    21. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2013. "Changes in the effects of monetary policy on disaggregate price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 543-560.

    More about this item

    Keywords

    Disaggregation;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    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:cte:wsrepe:24678. 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: Ana Poveda (email available below). General contact details of provider: http://portal.uc3m.es/portal/page/portal/dpto_estadistica .

    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.