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On autoregressive errors in singular systems of equations

Author

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  • Haupt, Harry
  • Oberhofer, Walter

Abstract

Dhrymes (1994, Econometric Theory, 10, 254-285) demonstrates the arising identification and estimation problems in singular equation systems when the error vector obeys an autoregressive scheme, as an extension of restricted least squares. Unfortunately, his main theorem concerning the identification of such systems, does not hold in general, though. Die Identifikations- und Schätzprobleme, die bei singulären System von Regressionsbeziehungen mit autoregressiven Fehlern auftreten, analysiert Dhrymes (1994, Econometric Theory, 10, 254-285) durch eine Erweiterung der restringierten Kleinst-Quadrate-Schätzung. Sein zentrales Theorem zur Identifikation derartiger Systeme gilt jedoch nicht im Allgemeinen.

Suggested Citation

  • Haupt, Harry & Oberhofer, Walter, 2005. "On autoregressive errors in singular systems of equations," University of Regensburg Working Papers in Business, Economics and Management Information Systems 410, University of Regensburg, Department of Economics.
  • Handle: RePEc:bay:rdwiwi:597
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    References listed on IDEAS

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    1. repec:ebl:ecbull:v:3:y:2002:i:1:p:1-7 is not listed on IDEAS
    2. Dhrymes, Phoebus J., 1994. "Autoregressive Errors in Singular Systems of Equations," Econometric Theory, Cambridge University Press, vol. 10(02), pages 254-285, June.
    3. Harry Haupt & Walter Oberhofer, 2002. "Fully restricted linear regression: A pedagogical note," Economics Bulletin, AccessEcon, vol. 3(1), pages 1-7.
    4. Berndt, Ernst R & Savin, N Eugene, 1975. "Estimation and Hypothesis Testing in Singular Equation Systems with Autoregressive Disturbances," Econometrica, Econometric Society, vol. 43(5-6), pages 937-957, Sept.-Nov.
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    Keywords

    Verallgemeinertes Regressionsmodell; Singuläre Systeme ; Identifikation; singular equation systems ; identification;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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