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Estimating a Falsified Model: Some Impossibility Theorems

Author

Listed:
  • Andrew J. Buck

    (Department of Economics, Temple University)

  • George M. Lady

    (Department of Economics, Temple University)

Abstract

A recent literature, e.g., Lady and Buck (2011), has shown that a qualitative analysis of a model’s structural and estimated reduced form arrays can provide a robust procedure for assessing if a model’s hypothesized structure has been falsified. This paper shows that the even weaker statement of the model’s structure provided by zero restrictions on the structural arrays can be falsified, independent of the proposed nonzero entries. When this takes place, multi-stage least squares, or any procedure for estimating the structural arrays with the zero restrictions imposed, will present estimates that could not possibly have generated the data upon which the estimated reduced form is based. The examples given in the paper are based upon a Monte Carlo sampling procedure that is briefly described in the appendix.

Suggested Citation

  • Andrew J. Buck & George M. Lady, 2015. "Estimating a Falsified Model: Some Impossibility Theorems," DETU Working Papers 1506, Department of Economics, Temple University.
    • Handle: RePEc:tem:wpaper:1506
    as

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    File URL: http://www.cla.temple.edu/RePEc/documents/DETU_15_06.pdf
    File Function: First version, 2015
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    References listed on IDEAS

    as
    1. Lady, George M. & Buck, Andrew J., 2011. "Structural models, information and inherited restrictions," Economic Modelling, Elsevier, vol. 28(6), pages 2820-2831.
    2. Lady, George M., 1995. "Robust economic models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(3), pages 481-501, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    qualitative analysis; Monte Carlo; model falsification; impossible estimates;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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