IDEAS home Printed from https://ideas.repec.org/a/ier/iecrev/v24y1983i3p523-36.html
   My bibliography  Save this article

Asymptotic Behavior of Predictors in a Nonlinear Simultaneous System

Author

Listed:
  • Mariano, Roberto S
  • Brown, Bryan W

Abstract

No abstract is available for this item.

Suggested Citation

  • Mariano, Roberto S & Brown, Bryan W, 1983. "Asymptotic Behavior of Predictors in a Nonlinear Simultaneous System," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 523-536, October.
  • Handle: RePEc:ier:iecrev:v:24:y:1983:i:3:p:523-36
    as

    Download full text from publisher

    File URL: http://links.jstor.org/sici?sici=0020-6598%28198310%2924%3A3%3C523%3AABOPIA%3E2.0.CO%3B2-2&origin=repec
    File Function: full text
    Download Restriction: Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
    ---><---

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

    Citations

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


    Cited by:

    1. Neil R. Ericsson & Jaime R. Marquez, 1990. "Evaluating the predictive performance of trade-account models," International Finance Discussion Papers 377, Board of Governors of the Federal Reserve System (U.S.).
    2. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
    3. Bryan W. Brown, 2000. "Efficient Semiparametric Prediction Intervals," Econometric Society World Congress 2000 Contributed Papers 1633, Econometric Society.
    4. Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.
    5. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976, Elsevier.
    6. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    7. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    8. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    9. Mariano, Roberto S, 1985. "Finite-Sample Properties in Stochastic Predictors in Nonlinear Systems : Some Initial Results," The Warwick Economics Research Paper Series (TWERPS) 266, University of Warwick, Department of Economics.
    10. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    11. van Garderen, Kees Jan, 2001. "Optimal prediction in loglinear models," Journal of Econometrics, Elsevier, vol. 104(1), pages 119-140, August.
    12. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results," MPRA Paper 22657, University Library of Munich, Germany, revised 1983.
    13. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Confidence intervals of forecasts from nonlinear econometric models," MPRA Paper 29025, University Library of Munich, Germany.
    14. Arthur Hsu & Ronald T. Wilcox, 2000. "Stochastic Prediction in Multinomial Logit Models," Management Science, INFORMS, vol. 46(8), pages 1137-1144, August.
    15. Bianchi, Carlo & Calzolari, Giorgio & Weihs, Claus, 1986. "Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models," MPRA Paper 29120, University Library of Munich, Germany.
    16. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
    17. Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "Coherent optimal prediction with large nonlinear systems: an example based on a French model," MPRA Paper 29057, University Library of Munich, Germany.

    More about this item

    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:ier:iecrev:v:24:y:1983:i:3:p:523-36. 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.

    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: Wiley-Blackwell Digital Licensing or the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.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.