IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/21944.html
   My bibliography  Save this paper

Evaluating Combined Non-Replicable Forecast

Author

Listed:
  • Chang, C-L.
  • Franses, Ph.H.B.F.
  • McAleer, M.J.

Abstract

Macroeconomic forecasts are often based on the interaction between econometric models and experts. A forecast that is based only on an econometric model is replicable and may be unbiased, whereas a forecast that is not based only on an econometric model, but also incorporates an expert’s touch, is non-replicable and is typically biased. In this paper we propose a methodology to analyze the qualities of combined non-replicable forecasts. One part of the methodology seeks to retrieve a replicable component from the non-replicable forecasts, and compares this component against the actual data. A second part modifies the estimation routine due to the assumption that the difference between a replicable and a non-replicable forecast involves a measurement error. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the methodological approach.

Suggested Citation

  • Chang, C-L. & Franses, Ph.H.B.F. & McAleer, M.J., 2010. "Evaluating Combined Non-Replicable Forecast," Econometric Institute Research Papers EI 2010-74, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:21944
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/21944/EI2010-74.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2009. "Expert opinion versus expertise in forecasting," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 334-346, August.
    2. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    Full references (including those not matched with items on IDEAS)

    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. Chang, Chia-Lin & de Bruijn, Bert & Franses, Philip Hans & McAleer, Michael, 2013. "Analyzing fixed-event forecast revisions," International Journal of Forecasting, Elsevier, vol. 29(4), pages 622-627.
    2. Chang, Chia Lin & Franses, Philip Hans & Mcaleer, Michael, 2012. "Evaluating Individual and Mean Non-Replicable Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 22-43, September.
    3. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2013. "Are forecast updates progressive?," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 9-18.
    4. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    5. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Combining Non-Replicable Forecasts," Working Papers in Economics 10/35, University of Canterbury, Department of Economics and Finance.
    6. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2010. "Evaluating Macroeconomic Forecast: A Review of Some Recent Developments," Econometric Institute Research Papers EI 2010-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Chia-Lin Chang & Michael Mcaleer, 2013. "What Do Experts Know About Forecasting Journal Quality? A Comparison With Isi Research Impact In Finance," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 1-30.
    8. Chia-Lin Chang & Michael McAleer, 2012. "What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance," Documentos de Trabajo del ICAE 2012-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. Jeffrey Frankel, 2013. "A Solution to Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Central Banking, Analysis, and Economic Policies Book Series, in: Luis Felipe Céspedes & Jordi Galí (ed.),Fiscal Policy and Macroeconomic Performance, edition 1, volume 17, chapter 9, pages 323-391, Central Bank of Chile.
    10. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Does the ROMC have expertise, and can it forecast?," Econometric Institute Research Papers EI 2008-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Frankel, Jeffrey A., 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Scholarly Articles 4723209, Harvard Kennedy School of Government.
    12. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Chang, Chun-Ping & Lee, Chien-Chiang & Hsieh, Meng-Chi, 2015. "Does globalization promote real output? Evidence from quantile cointegration regression," Economic Modelling, Elsevier, vol. 44(C), pages 25-36.
    14. Philip Hans Franses, 2011. "Averaging Model Forecasts and Expert Forecasts: Why Does It Work?," Interfaces, INFORMS, vol. 41(2), pages 177-181, April.
    15. Chang, Chia-Lin & Franses, Philip Hans & McAleer, Michael, 2011. "How accurate are government forecasts of economic fundamentals? The case of Taiwan," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1066-1075, October.
    16. Franses, Philip Hans, 2013. "Improving judgmental adjustment of model-based forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 1-8.
    17. Harin, Alexander, 2014. "General correcting formulae for forecasts," MPRA Paper 55283, University Library of Munich, Germany.
    18. Egor Griva & Irina Butorina & Anatoly Sidorov & Pavel Senchenko, 2022. "Analysis and Forecasting of Sales Funnels," Mathematics, MDPI, vol. 11(1), pages 1-22, December.
    19. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(2), pages 129-138, September.
    20. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.

    More about this item

    Keywords

    combined forecasts; efficient estimation; expert’s intuition; generated regressors; non-replicable forecasts; replicable forecasts;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:ems:eureir:21944. 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: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.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.