IDEAS home Printed from https://ideas.repec.org/p/cte/wsrepe/ws080101.html
   My bibliography  Save this paper

Forecasting Spanish inflation using information from different sectors and geographical areas

Author

Listed:
  • Tena Horrillo, Juan de Dios
  • Espasa, Antoni
  • Pino, Gabriel

Abstract

This paper evaluates different strategies to forecast Spanish inflation using information of price series for 57 products and 18 regions in Spain. We consider vector equilibrium correction (VeqC) models that include cointegration relationships between Spanish prices and prices in the regions of Valencia, Andalusia, Madrid, Catalonia and the Basque Country. This approach is consistent with economic intuition and is shown to be of tangible importance after suitable econometric evaluation. It is found that inflation forecasts can always be improved by aggregating projections from differente sectors and geographical areas. Moreover, cointegration relationships between regional and national prices must be considered in order to obtain a significantly better inflation forecast.

Suggested Citation

  • Tena Horrillo, Juan de Dios & Espasa, Antoni & Pino, Gabriel, 2008. "Forecasting Spanish inflation using information from different sectors and geographical areas," DES - Working Papers. Statistics and Econometrics. WS ws080101, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:ws080101
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/ccd5b77d-14dc-48ac-ac0e-e6481542bd53/content
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
    2. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
    3. Stephen Cecchetti & Nelson C. Mark & Robert Sonora, 1998. "Price Level Convergence Among United States Cities: Lessons for the European Central Bank," Working Papers 32, Oesterreichische Nationalbank (Austrian Central Bank).
    4. Culver, Sarah E & Papell, David H, 1997. "Is There a Unit Root in the Inflation Rate? Evidence from Sequential Break and Panel Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(4), pages 435-444, July-Aug..
    5. Christoffersen, Peter F & Diebold, Francis X, 1998. "Cointegration and Long-Horizon Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 450-458, October.
    6. Osborn, Denise R, et al, 1988. "Seasonality and the Order of Integration for Consumption," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(4), pages 361-377, November.
    7. 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.
    8. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    9. Lothian, James R., 1997. "Multi-country evidence on the behavior of purchasing power parity under the current float," Journal of International Money and Finance, Elsevier, vol. 16(1), pages 19-35, February.
    10. MacDonald, Ronald, 1996. "Panel unit root tests and real exchange rates," Economics Letters, Elsevier, vol. 50(1), pages 7-11, January.
    11. John F. Henry & L. Randall Wray, 1998. "Economic Time," Macroeconomics 9811004, University Library of Munich, Germany.
    12. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    13. David C. Parsley & Shang-Jin Wei, 1996. "Convergence to the Law of One Price Without Trade Barriers or Currency Fluctuations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(4), pages 1211-1236.
    14. Abuaf, Niso & Jorion, Philippe, 1990. "Purchasing Power Parity in the Long Run," Journal of Finance, American Finance Association, vol. 45(1), pages 157-174, March.
    15. Espasa, Antoni & Albacete, Rebeca, 2004. "Econometric modelling for short-term inflation forecasting in the EMU," DES - Working Papers. Statistics and Econometrics. WS ws034309, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
    17. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    18. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, December.
    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. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.

    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. Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2010. "Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas," International Regional Science Review, , vol. 33(2), pages 181-204, April.
    2. Juan de Dios TENA & Antoni ESPASA & Gabriel PINO, 2010. "Forecasting Inflation and Relative Prices in the European Regions: A Case Study," Regional and Urban Modeling 284100040, EcoMod.
    3. Espasa, Antoni & Pino, Gabriel & Tena Horrillo, Juan de Dios, 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.
    4. Matthew Higgins & Egon Zakrajšek, 1999. "Purchasing power parity: three stakes through the heart of the unit root null," Staff Reports 80, Federal Reserve Bank of New York.
    5. Martin Wagner, 2008. "On PPP, unit roots and panels," Empirical Economics, Springer, vol. 35(2), pages 229-249, September.
    6. Hendry, David F. & Hubrich, Kirstin, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 216-227.
    7. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    8. Helena Marques & Gabriel Pino & Juan Dios Tena Horrillo, 2014. "Regional inflation dynamics using space–time models," Empirical Economics, Springer, vol. 47(3), pages 1147-1172, November.
    9. Engel, Charles & Hendrickson, Michael K. & Rogers, John H., 1997. "Intranational, Intracontinental, and Intraplanetary PPP," Journal of the Japanese and International Economies, Elsevier, vol. 11(4), pages 480-501, December.
    10. Marco G. Ercolani & Jayasri Dutta, 2006. "The Euro-changeoverand Euro-inflation: Evidence from Eurostat's HICP," Discussion Papers 06-03, Department of Economics, University of Birmingham.
    11. repec:onb:oenbwp:y::i:32:b:1 is not listed on IDEAS
    12. Stephen Cecchetti & Nelson C. Mark & Robert Sonora, 1998. "Price Level Convergence Among United States Cities: Lessons for the European Central Bank," Working Papers 32, Oesterreichische Nationalbank (Austrian Central Bank).
    13. Robinson Durán & Evelyn Garrido & Carolina Godoy & Juan de Dios Tena, 2012. "Predicción de la inflación en México con modelos desagregados por componente," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 27(1), pages 133-167.
    14. 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.
    15. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2002. "A simple test for PPP among traded goods," Econometric Institute Research Papers EI 2002-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Josep LluIs Carrion-I-Silvestre & Tomas Del Barrio & Enrique Lopez-Bazo, 2004. "Evidence on the purchasing power parity in a panel of cities," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 961-966.
    17. Chen, Natalie, 2004. "The behaviour of relative prices in the European Union: A sectoral analysis," European Economic Review, Elsevier, vol. 48(6), pages 1257-1286, December.
    18. Das, Samarjit & Bhattacharya, Kaushik, 2004. "Price Convergence across Regions in India," Bonn Econ Discussion Papers 1/2005, University of Bonn, Bonn Graduate School of Economics (BGSE).
    19. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    20. Hans Franses, Philip & Koehler, Anne B., 1998. "A model selection strategy for time series with increasing seasonal variation," International Journal of Forecasting, Elsevier, vol. 14(3), pages 405-414, September.
    21. Koedijk, Kees G. & Tims, Ben & van Dijk, Mathijs A., 2011. "Why panel tests of purchasing power parity should allow for heterogeneous mean reversion," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 246-267, February.

    More about this item

    Keywords

    Vector equilibrium correction models;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    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:ws080101. 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.