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Random Walks with Drifts, Simulaneous Equation Errors, and Small Samples - Simulating the Bird's Eye View

Author

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  • Horst Entorf

Abstract

The paper illustrates finite sample problems of regression models with I(1) variables. The importance of drifts on test statistics is analysed both analytically and by simulation methods. Moreover, Haavelmo's famous example for the presence of some simultaneous equation bias is considered in the superconsistent case of cointegrated variables. It is shown that TSLS still leads to some improvement even in the case of cointegration when short times series are considered. A main purpose of the paper was to give a graphical exposition of finite sample problems. Most of the results are summarized by use of three-dimensional density functions.

Suggested Citation

  • Horst Entorf, 2004. "Random Walks with Drifts, Simulaneous Equation Errors, and Small Samples - Simulating the Bird's Eye View," Econometrics 0401009, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0401009
    Note: Type of Document - pdf; pages: 50. Discussion paper version (PDF file) of "Random walks with drifts: Nonsense regressions and spurious fixed-effect estimation, Journal of Econometrics 80 (1997), 287-296"
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0401/0401009.pdf
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    More about this item

    Keywords

    Spurious Regressions; Panel Econometrics; Fixed-Effect Modelling; Superconsistency; Monte Carlo;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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