IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/28804.html
   My bibliography  Save this paper

A Simulation Study on FIML Covariance Matrix

Author

Listed:
  • Calzolari, Giorgio
  • Panattoni, Lorenzo

Abstract

In econometric models, estimates of the asymptotic covariance matrix of FIML coefficients are traditionally computed in several different ways: with a generalized least squares type matrix; using the Hessian of the concentrated log-likelihood; using the outer product of the first derivatives of the log-likelihoods; with some suitable joint use of Hessian and outer product. The different alternative estimators are asymptotically equivalent in case of correct model's specification, but may produce large differences in the numerical application to small samples. The behaviour of the different estimators of the covariance matrix in standardizing or normalizing FIML estimated coefficients in the small samples is investigated in this paper. Monte Carlo experiments are performed on several small-medium size models, and some systematic behaviours are evidenced.

Suggested Citation

  • Calzolari, Giorgio & Panattoni, Lorenzo, 1984. "A Simulation Study on FIML Covariance Matrix," MPRA Paper 28804, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:28804
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/28804/1/MPRA_paper_28804.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Calzolari, Giorgio, 1983. "Asymptotic distribution of power spectra and peak frequencies in the stochastic response of econometric models," Journal of Economic Dynamics and Control, Elsevier, vol. 5(1), pages 235-247, February.
    2. Hendry, D F, 1971. "Maximum Likelihood Estimation of Systems of Simultaneous Regression Equations with Errors Generated by a Vector Autoregressive Process," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(2), pages 257-272, June.
    3. Anderson, T W & Kunitomo, Naoto & Sawa, Takamitsu, 1982. "Evaluation of the Distribution Function of the Limited Information Maximum Likelihood Estimator," Econometrica, Econometric Society, vol. 50(4), pages 1009-1027, July.
    4. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    5. Parke, William R, 1982. "An Algorithm for FIML and 3SLS Estimation of Large Nonlinear Models," Econometrica, Econometric Society, vol. 50(1), pages 81-95, January.
    6. Dagenais, Marcel G, 1978. "The Computation of FIML Estimates as Iterative Generalized Least Squares Estimates in Linear and Nonlinear Simultaneous Equations Models," Econometrica, Econometric Society, vol. 46(6), pages 1351-1362, November.
    7. Morimune, Kimio, 1983. "Approximate Distributions of k-Class Estimators When the Degree of Overidentifiability Is Large Compared with the Sample Size," Econometrica, Econometric Society, vol. 51(3), pages 821-841, May.
    8. Hall, A.R., 1984. "The Information Matrix Test for the Linear Model," The Warwick Economics Research Paper Series (TWERPS) 250, University of Warwick, Department of Economics.
    9. Jerry A. Hausman, 1974. "Full Information Instrumental Variables Estimation of Simultaneous Equations Systems," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 641-652, National Bureau of Economic Research, Inc.
    10. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    11. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
    12. Brundy, James M & Jorgenson, Dale W, 1971. "Efficient Estimation of Simultaneous Equations by Instrumental Variables," The Review of Economics and Statistics, MIT Press, vol. 53(3), pages 207-224, August.
    13. Calzolari, Giorgio & Panattoni, Lorenzo, 1983. "Hessian and approximated Hessian matrices in maximum likelihood estimation: a Monte Carlo study," MPRA Paper 28847, University Library of Munich, Germany.
    14. Amemiya, Takeshi, 1977. "The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model," Econometrica, Econometric Society, vol. 45(4), pages 955-968, May.
    15. Klein, Lawrence R, 1969. "Estimation on Interdependent Systems in Macroeconometrics," Econometrica, Econometric Society, vol. 37(2), pages 171-192, April.
    16. Hatanaka, Michio, 1978. "On the efficient estimation methods for the macro-economic models nonlinear in variables," Journal of Econometrics, Elsevier, vol. 8(3), pages 323-356, December.
    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. Calzolari, Giorgio & Panattoni, Lorenzo, 1987. "Finite sample performance of the robust Wald test in simultaneous equation systems," MPRA Paper 22557, University Library of Munich, Germany.
    2. Weihs, Claus & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "The behavior of trust-region methods in FIML estimation," MPRA Paper 24122, University Library of Munich, Germany, revised 1987.

    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. Calzolari, Giorgio & Panattoni, Lorenzo, 1984. "Evaluating Forecast Uncertainty in Econometric Models: The Effect of Alternative Estimators of Maximum Likelihood Covariance Matrix," MPRA Paper 28806, University Library of Munich, Germany.
    2. Calzolari, Giorgio & Panattoni, Lorenzo, 1983. "Hessian and approximated Hessian matrices in maximum likelihood estimation: a Monte Carlo study," MPRA Paper 28847, University Library of Munich, Germany.
    3. Calzolari, Giorgio, 1992. "Stima delle equazioni simultanee non-lineari: una rassegna [Estimation of nonlinear simultaneous equations: a survey]," MPRA Paper 24123, University Library of Munich, Germany, revised 1992.
    4. Calzolari, Giorgio & Panattoni, Lorenzo, 1985. "Gradient methods in FIML estimation of econometric models," MPRA Paper 24843, University Library of Munich, Germany.
    5. Calzolari, Giorgio, 2012. "Econometric notes," MPRA Paper 71440, University Library of Munich, Germany.
    6. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    7. Calzolari, Giorgio & Fiorentini, Gabriele, 1994. "Conditional heteroskedasticity in nonlinear simultaneous equations," MPRA Paper 24428, University Library of Munich, Germany.
    8. Calzolari, Giorgio & Sampoli, Letizia, 1989. "Instrumental variables interpretations of FIML and nonlinear FIML," MPRA Paper 29024, University Library of Munich, Germany.
    9. Fiorentini, Gabriele & Calzolari, Giorgio & Panattoni, Lorenzo, 1996. "Analytic Derivatives and the Computation of GARCH Estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 399-417, July-Aug..
    10. Bianchi, Carlo & Calzolari, Giorgio, 1982. "Evaluating forecast uncertainty due to errors in estimated coefficients: empirical comparison of alternative methods," MPRA Paper 22559, University Library of Munich, Germany.
    11. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389, Elsevier.
    12. Weihs, Claus & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "The behavior of trust-region methods in FIML estimation," MPRA Paper 24122, University Library of Munich, Germany, revised 1987.
    13. Richard M. Golden & Steven S. Henley & Halbert White & T. Michael Kashner, 2019. "Consequences of Model Misspecification for Maximum Likelihood Estimation with Missing Data," Econometrics, MDPI, vol. 7(3), pages 1-27, September.
    14. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo & Panattoni, Lorenzo, 1985. "Asymptotic properties of dynamic multipliers in nonlinear econometric models," MPRA Paper 24401, University Library of Munich, Germany.
    15. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.
    16. Calzolari, Giorgio & Panattoni, Lorenzo, 1987. "Finite sample performance of the robust Wald test in simultaneous equation systems," MPRA Paper 22557, University Library of Munich, Germany.
    17. Emanuele BACCHIOCCHI, 2011. "Identification through heteroskedasticity: a likelihood-based approach," Departmental Working Papers 2011-19, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    18. Calzolari, Giorgio & Fiorentini, Gabriele & Panattoni, Lorenzo, 1993. "Alternative estimators of the covariance matrix in GARCH models," MPRA Paper 24433, University Library of Munich, Germany.
    19. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1981. "Alternative estimates of the Klein-I model," MPRA Paper 23337, University Library of Munich, Germany, revised Sep 1981.
    20. Jansson, Leif & Mellander, Erik, 1984. "CONRAD – A Maximum Likelihood Program for Estimation of Simultaneous Equations Models that are Non-Linear in the Parameters," Working Paper Series 131, Research Institute of Industrial Economics.

    More about this item

    Keywords

    Econometric models; simultaneous equations; FIML; maximum likelihood; covariance matrix; Hessian; outer product;
    All these keywords.

    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:pra:mprapa:28804. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.