IDEAS home Printed from https://ideas.repec.org/p/ptu/wpaper/w200818.html
   My bibliography  Save this paper

Forecasting investment: A fishing contest using survey data

Author

Listed:
  • Sara Serra
  • José R. Maria

Abstract

This paper assesses the usefulness of business surveys as a source of information for investment developments in Portugal. This will be achieved by what will be named a “fishing contest”, where the “participants” are bridge models, models based on principal components (derived from standard and non-standard methods), and models built with the outcome of partial least squares regressions. All models, based on quarterly data, are estimated using a general-to-specific approach and are designed to produce 1 to 4 out-of-sample direct forecasts. The accuracy of these forecasts is then compared with the one of autoregressive processes. The empirical evidence indicates that, in general, there is always a participant in the fishing context that produces a lower out-of-sample Root Mean Squared Error (RMSE) than the one associated with the autoregressive benchmark. In most cases, the combination of autoregressive processes with each participant reduces the RMSE further. A striking outcome is the relative accuracy of bridge models.

Suggested Citation

  • Sara Serra & José R. Maria, 2008. "Forecasting investment: A fishing contest using survey data," Working Papers w200818, Banco de Portugal, Economics and Research Department.
  • Handle: RePEc:ptu:wpaper:w200818
    as

    Download full text from publisher

    File URL: https://www.bportugal.pt/sites/default/files/anexos/papers/wp200818.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
    2. Francisco Dias & Maximiano Pinheiro & António Rua, 2010. "Forecasting using targeted diffusion indexes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 341-352.
    3. 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.
    4. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
    5. Jason Bram & Sydney Ludvigson, 1998. "Does consumer confidence forecast household expenditure? a sentiment index horse race," Economic Policy Review, Federal Reserve Bank of New York, issue Jun, pages 59-78.
    6. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
    7. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
    8. Teresa Santero & Niels Westerlund, 1996. "Confidence Indicators and Their Relationship to Changes in Economic Activity," OECD Economics Department Working Papers 170, OECD Publishing.
    9. A. W. Coats, 1996. "Introduction," History of Political Economy, Duke University Press, vol. 28(5), pages 3-11, Supplemen.
    10. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
    11. Alain N. Kabundi, 2004. "Estimation of Economic Growth in France Using Business Survey Data," IMF Working Papers 04/69, International Monetary Fund.
    12. Rünstler, Gerhard & Sédillot, Franck, 2003. "Short-term estimates of euro area real GDP by means of monthly data," Working Paper Series 276, European Central Bank.
    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. Paulo Soares Esteves & António Rua, 2012. "Short-term forecasting for the portuguese economy: a methodological overview," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

    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:ptu:wpaper:w200818. 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: (DEE-NTD). General contact details of provider: http://edirc.repec.org/data/bdpgvpt.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.