IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v6y1990i3p317-326.html

Mode predictors in nonlinear systems with identities

Author

Listed:
  • Calzolari, Giorgio
  • Panattoni, Lorenzo

Abstract

For a nonlinear system of simultaneous equations, the mode of the joint distribution of the endogenous variables in the forecast period is proposed as alternative to the more usual deterministic or mean predictors. A first method follows from maximizing the joint density of a subset of the endogenous variables, corresponding to stochastic equations only (analogously to FIML estimation, where identities are first substituted into stochastic equations). Then a more general approach is developed, which maintains the identities. The model with identities is viewed as a mapping between the space of the random errors and a hypersurface in the space of the endogenous variables; the probability density is defined, and maximization is performed on such a hypersurface. Experimental results on these two mode predictors (and comparisons with deterministic and mean predictors) are provided for a macro model of the Italian economy.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.
    • Handle: RePEc:eee:intfor:v:6:y:1990:i:3:p:317-326
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0169-2070(90)90059-K
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maximiano Pinheiro & Paulo Esteves, 2012. "On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information," Empirical Economics, Springer, vol. 42(3), pages 639-665, June.

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

    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:intfor:v:6:y:1990:i:3:p:317-326. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/ijforecast .

    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.