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

Econometric Modelling For Short-Term Inflation Forecasting In The Emu

Contents:

Author Info

  • Antoni Espasa

    ()

  • Rebeca Albacete

    ()

Registered author(s):

    Abstract

    Inflation forecasts are in great demand by agents in financial markets and monetary authorities that also require frequent updates. In the case of the EMU, these can be done monthly using Harmonised Indices of Consumer Prices (HICP). Analysing the HICP it was detected in a previous paper that breaking down the HICP in a vector of n sectors so that each price index component corresponds to a group of relatively homogeneous markets, or in a vector of n countries, there are in both cases fewer than (n-1) cointegration relationships. It can then be said that the components of the index are not fully cointegrated in the sense that there is more than one common trend in the HICP vector. In such a case, one way to increase sample information about the HICP trend is to consider the n price components and approach disaggregated econometric modelling. The paper shows that the breakdown that joins both criteria by considering a price index for each large group of markets in each country improves EMU inflation forecasts and establishes a framework in which general and specific explanatory variables and non-linear structures can be introduced for further improvements. The paper shows that VEqCM of ten price indices – two sectors by five geographical areas – including three cointegration relationships, with a sector-block diagonal restriction, generates forecasts of the year-on-year inflation rate in the HICP such that their error variances are one third or one fifth of the forecast errors from an aggregate ARIMA model, depending whether the horizon is three or twelve months. This vector model also provides better forecasts than single-equation models or alternative vector models for the components. A successful formulation of the vector model requires the inclusion of dummy variables to take account of special events such as seasonality changes due to sales, the introduction of the euro, Greece becoming a member of the EMU, the introduction of ecological taxes, bad weather periods and others events altering the evolution of unprocessed food prices, etc. and the inclusion of international Brent prices in euros. With the breakdown used in the paper it is shown that a usual measure of core inflation is not a good predictor of total inflation, but the interest in core inflation could lie in the fact that its corresponding price index is constructed with price indices in which innovations are more persistent than those in the other consumer price indexes excluded from the core. The disaggregated forecasts presented in this paper are useful for policy-making because they tell us which sectors have the highest expected inflation rates and how persistent are the shocks affecting different sectors.

    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://docubib.uc3m.es/WORKINGPAPERS/WS/ws034309.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws034309.

    as in new window
    Length:
    Date of creation: Feb 2004
    Date of revision:
    Handle: RePEc:cte:wsrepe:ws034309

    Contact details of provider:
    Postal: C/ Madrid, 126 - 28903 GETAFE (MADRID)
    Phone: 6249847
    Fax: 6249849
    Web page: http://www.uc3m.es/uc3m/dpto/DEE/departamento.html
    More information through EDIRC

    Related research

    Keywords:

    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. Gordon de Brouwer & Neil R. Ericsson, 1995. "Modelling inflation in Australia," International Finance Discussion Papers 530, Board of Governors of the Federal Reserve System (U.S.).
    2. Banerjee, A. & Cockerell, L. & Russell, B., 1998. "An I(2) Analysis of Inflation and the Markup," Economics Series Working Papers 99203, University of Oxford, Department of Economics.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
    4. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
    5. A. Espasa & E. Senra & R. Albacete, 2002. "Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 402-421.
    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 in new window

    Cited by:
    1. Rebeca Albacete & Antoni Espasa, 2005. "Forecasting Inflation In The Euro Area Using Monthly Time Series Models And Quarterly Econometric Models," Statistics and Econometrics Working Papers ws050401, Universidad Carlos III, Departamento de Estadística y Econometría.
    2. Janine Aron & John Muellbauer & Coen Pretorius, 2004. "A Framework for Forecasting the Components of the Consumer Price," Development and Comp Systems 0409054, EconWPA.

    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:cte:wsrepe:ws034309. 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: ().

    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.