IDEAS home Printed from https://ideas.repec.org/p/ags/eureia/272294.html

Limited Information Maximum Likelihood Estimation Of A Subsystem Of Nonlinear Equations

Author

Listed:
  • van der Loeff, S. Schim

Abstract

This paper discusses the maximum likelihood estimation of the parameters of a subsystem of nonlinear equations under partial disregard of structural information. It provides a generalization of Godfrey and Wickens' (1982) limited information estimator to subsystems of nonlinear equations and Amemiya's (1975) nonlinear limited information estimator to subsystems containing more than one equation. Some attention is devoted to the asymptotic properties of the estimator and different estimators for the asymptotic covariance matrix are discussed. The estimation method is illustrated by means of an example dealing with the estimation of an aggregate two-level CES production function for The Netherlands' enterprises sector.

Suggested Citation

  • van der Loeff, S. Schim, 1985. "Limited Information Maximum Likelihood Estimation Of A Subsystem Of Nonlinear Equations," Econometric Institute Archives 272294, Erasmus University Rotterdam.
    • Handle: RePEc:ags:eureia:272294
    DOI: 10.22004/ag.econ.272294
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/272294/files/erasmus170.pdf
    Download Restriction: no
    File URL: https://ageconsearch.umn.edu/record/272294/files/erasmus170.pdf?subformat=pdfa
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.272294?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
    ---><---

    References listed on IDEAS

    as
    1. Wales, T. J., 1984. "A note on likelihood ratio tests of functional form and structural change in demand systems," Economics Letters, Elsevier, vol. 14(2-3), pages 213-220.
    2. Berndt, Ernst R & Wood, David O, 1975. "Technology, Prices, and the Derived Demand for Energy," The Review of Economics and Statistics, MIT Press, vol. 57(3), pages 259-268, August.
    3. 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.
    4. Ter Berg, Peter & Harkema, Rins, 1984. "Bayesian limited-information analysis of nonlinear simultaneous equations systems," Journal of Econometrics, Elsevier, vol. 24(3), pages 379-395, March.
    5. Godfrey, L. G. & Wickens, M. R., 1982. "A simple derivation of the limited information maximum likelihood estimator," Economics Letters, Elsevier, vol. 10(3-4), pages 277-283.
    6. Amemiya, Takeshi, 1975. "The nonlinear limited-information maximum- likelihood estimator and the modified nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 3(4), pages 375-386, November.
    7. 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.
    8. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    9. Davidson, Russel & MacKinnon, James G., 1983. "Small sample properties of alternative forms of the Lagrange Multiplier test," Economics Letters, Elsevier, vol. 12(3-4), pages 269-275.
    10. Loeff, Sybrand Schim van der & Harkema, Rins, 1981. "Estimation and testing of alternative production function models," Journal of Macroeconomics, Elsevier, vol. 3(1), pages 33-53.
    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. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
    2. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    3. 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.
    4. Masaru Chiba, 2023. "Robust and efficient specification tests in Markov-switching autoregressive models," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 99-137, April.
    5. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    6. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    7. 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.
    8. Calzolari, Giorgio, 2012. "Econometric notes," MPRA Paper 71440, University Library of Munich, Germany.
    9. 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.
    10. Paul Cashin, 1991. "A Model Of The Disaggregated Demand For Meat In Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 35(3), pages 263-283, December.
    11. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    12. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    13. Chirinko, Robert S., 1995. "Nonconvexities, labor hoarding, technology shocks, and procyclical productivity a structural econometric analysis," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 61-98.
    14. Davidson, Russell & MacKinnon, James G., 1984. "Convenient specification tests for logit and probit models," Journal of Econometrics, Elsevier, vol. 25(3), pages 241-262, July.
    15. Calzolari, Giorgio & Panattoni, Lorenzo, 1984. "A Simulation Study on FIML Covariance Matrix," MPRA Paper 28804, University Library of Munich, Germany.
    16. Rusdu Saracoglu, 1977. "The maximum likelihood estimation of parameters in mixed autoregressive moving-average multivariate models," Staff Report 20, Federal Reserve Bank of Minneapolis.
    17. 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.
    18. 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.
    19. Susan M. Capalbo & Michael Denny, 1985. "Testing Long-Run Productivity Models for the Canadian and U.S. Agricultural Sectors," NBER Working Papers 1764, National Bureau of Economic Research, Inc.
    20. Davidson, Russell & MacKinnon, James G, 1988. "Double Length Artificial Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(2), pages 203-217, May.

    More about this item

    Keywords

    ;
    ;

    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:ags:eureia:272294. 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: AgEcon Search (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.