IDEAS home Printed from https://ideas.repec.org/a/eee/streco/v45y2018icp30-36.html
   My bibliography  Save this article

Qualitative equationless macroeconomic models as generators of all possible forecasts based on three trend values—Increasing, constant, decreasing

Author

Listed:
  • Doubravsky, Karel
  • Dohnal, Mirko

Abstract

This paper studies macroeconomic models based on a set of qualitative heuristics. A qualitative heuristic is described using just trends; i.e. increasing, decreasing, constant. The trends are the least information intensive quantifiers. E.g. an unemployment is increasing more and more rapidly represents the positive first time derivative of the unemployment (increasing) and positive second derivative (more and more rapidly). It means that not just trends but higher derivatives can be incorporated into a model if they are qualitatively known. No quantitative quantifiers, e.g. numbers, fuzzy sets, are used in this paper. The solution of a qualitative model is a set S of scenarios. A set T of transitions among the set of scenarios S is used to generate an oriented graph H. Any future and past time behaviour of the system under study is described by a path within the graph H. A ten-dimensional macroeconomic serves as a case study.

Suggested Citation

  • Doubravsky, Karel & Dohnal, Mirko, 2018. "Qualitative equationless macroeconomic models as generators of all possible forecasts based on three trend values—Increasing, constant, decreasing," Structural Change and Economic Dynamics, Elsevier, vol. 45(C), pages 30-36.
  • Handle: RePEc:eee:streco:v:45:y:2018:i:c:p:30-36
    DOI: 10.1016/j.strueco.2018.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0954349X16300352
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.strueco.2018.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Vicha, T. & Dohnal, M., 2008. "Qualitative identification of chaotic systems behaviours," Chaos, Solitons & Fractals, Elsevier, vol. 38(1), pages 70-78.
    2. Fiordaliso, Antonio, 1998. "A nonlinear forecasts combination method based on Takagi-Sugeno fuzzy systems," International Journal of Forecasting, Elsevier, vol. 14(3), pages 367-379, September.
    3. Berndsen, Ron & Daniels, Hennie, 1990. "Qualitative dynamics and causality in a Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 435-450, May.
    4. Punzo, Lionello F., 2003. "Some new tools for the qualitative analysis of dynamic economic data: symbolic and distribution analyses for multi-regime dynamics," Structural Change and Economic Dynamics, Elsevier, vol. 14(2), pages 121-131, June.
    5. Orrell, David & McSharry, Patrick, 2009. "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach," International Journal of Forecasting, Elsevier, vol. 25(4), pages 734-743, 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. Dohnal, Mirko, 2016. "Complex biofuels related scenarios generated by qualitative reasoning under severe information shortages: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 676-684.
    2. Thomassey, Sebastien & Happiette, Michel & Castelain, Jean Marie, 2005. "A short and mean-term automatic forecasting system--application to textile logistics," European Journal of Operational Research, Elsevier, vol. 161(1), pages 275-284, February.
    3. Caron, E.A.M. & Daniels, H.A.M., 2008. "Explanation of exceptional values in multi-dimensional business databases," European Journal of Operational Research, Elsevier, vol. 188(3), pages 884-897, August.
    4. Vicha, T. & Dohnal, M., 2008. "Qualitative feature extractions of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 38(2), pages 364-373.
    5. Berndsen, Ron & Daniels, Hennie, 1994. "Causal reasoning and explanation in dynamic economic systems," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 251-271, January.
    6. Rendon-Sanchez, Juan F. & de Menezes, Lilian M., 2019. "Structural combination of seasonal exponential smoothing forecasts applied to load forecasting," European Journal of Operational Research, Elsevier, vol. 275(3), pages 916-924.
    7. Karel Doubravský & Alena Kocmanová & Mirko Dohnal, 2018. "Analysis of Sustainability Decision Trees Generated by Qualitative Models Based on Equationless Heuristics," Sustainability, MDPI, vol. 10(7), pages 1-18, July.
    8. Olga Kiuila, 2011. "Interactions between trade and environmental policies in the Czech economy," Working Papers 2011-16, Faculty of Economic Sciences, University of Warsaw.
    9. -, 2011. "An assessment of the economic impact of climate change on the tourism sector In Barbados," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 38602, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    10. Prasad, Ravita D. & Bansal, R.C. & Raturi, Atul, 2014. "Multi-faceted energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 686-699.
    11. Peter Nielsen & Liping Jiang & Niels Gorm Malý Rytter & Gang Chen, 2014. "An investigation of forecast horizon and observation fit's influence on an econometric rate forecast model in the liner shipping industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(7), pages 667-682, December.
    12. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2013. "Property Market Modelling and Forecasting: A Case for Simplicity," ERES eres2013_10, European Real Estate Society (ERES).
    13. Wright, George & Goodwin, Paul, 2009. "Decision making and planning under low levels of predictability: Enhancing the scenario method," International Journal of Forecasting, Elsevier, vol. 25(4), pages 813-825, October.
    14. Roberto Savona & Marika Vezzoli, 2015. "Fitting and Forecasting Sovereign Defaults using Multiple Risk Signals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 66-92, February.
    15. Makridakis, Spyros & Hogarth, Robin M. & Gaba, Anil, 2009. "Forecasting and uncertainty in the economic and business world," International Journal of Forecasting, Elsevier, vol. 25(4), pages 794-812, October.
    16. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    17. Lady, George M., 1995. "Robust economic models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(3), pages 481-501, April.
    18. Zanoli, Raffaele & Gambelli, Danilo & Vairo, Daniela, 2012. "Scenarios of the organic food market in Europe," Food Policy, Elsevier, vol. 37(1), pages 41-57.
    19. Punzo, Lionello F., 2006. "Towards a disequilibrium theory of structural dynamics: Goodwin's contribution," Structural Change and Economic Dynamics, Elsevier, vol. 17(4), pages 382-399, December.
    20. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.

    More about this item

    Keywords

    Qualitative; Dynamics; Multidimensional; Macroeconomic forecasting;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - 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:eee:streco:v:45:y:2018:i:c:p:30-36. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/525148 .

    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.