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Consistent Maximum Likelihood Estimation With Dependent Observations: The General (Non-Normal) Case And The Normal Case

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  • Heijmans, Risto
  • Magnus, Jan

Abstract

These seems to be almost universal consensus among econometricians that the method of maximum likelihood estimation yields estimators which, under mild assumptions, are consistent. The purpose of this paper is to show that this unanimity is largely justified, but on grounds that are not quite so trivial as generally assumed.

Suggested Citation

  • Heijmans, Risto & Magnus, Jan, 1985. "Consistent Maximum Likelihood Estimation With Dependent Observations: The General (Non-Normal) Case And The Normal Case," University of Amsterdam, Actuarial Science and Econometrics Archive 293107, University of Amsterdam, Faculty of Economics and Business.
    • Handle: RePEc:ags:amstas:293107
    DOI: 10.22004/ag.econ.293107
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    Cited by:

    1. Julie Le Gallo, 2002. "Économétrie spatiale : l'autocorrélation spatiale dans les modèles de régression linéaire," Économie et Prévision, Programme National Persée, vol. 155(4), pages 139-157.
    2. Furrer, Reinhard, 2002. "M-Estimation for dependent random variables," Statistics & Probability Letters, Elsevier, vol. 57(4), pages 337-341, May.
    3. Cem Ertur & Thiaw Kalidou, 2005. "Growth and Spatial Dependence - The Mankiw, Romer and Weil model revisited," ERSA conference papers ersa05p660, European Regional Science Association.
    4. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    5. Wang, Jian-Xin, 2001. "Quote revision and information flow among foreign exchange dealers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 11(2), pages 115-136, June.
    6. Julie Le Gallo, 2000. "Spatial econometrics (1, Spatial autocorrelation) [Econométrie spatiale (1, Autocorrélation spatiale)]," Working Papers hal-01527290, HAL.
    7. Conley, Timothy G. & Molinari, Francesca, 2007. "Spatial correlation robust inference with errors in location or distance," Journal of Econometrics, Elsevier, vol. 140(1), pages 76-96, September.
    8. Kevin W. Lu, 2022. "Calibration for multivariate Lévy-driven Ornstein-Uhlenbeck processes with applications to weak subordination," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 365-396, July.
    9. Wilfried Koch, 2004. "Effets de voisinage dans le modèle de Solow avec des externalités spatiales," Working Papers hal-01526536, HAL.
    10. Abadir, Karim M. & Distaso, Walter, 2007. "Testing joint hypotheses when one of the alternatives is one-sided," Journal of Econometrics, Elsevier, vol. 140(2), pages 695-718, October.
    11. LE GALLO, Julie, 2000. "Econométrie spatiale 1 -Autocorrélation spatiale," LATEC - Document de travail - Economie (1991-2003) 2000-05, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.

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