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Some Comments on the Current State of Econometrics

Author

Listed:
  • George Judge

    (Department of Agricultural and Resource Economics, University of California, Berkeley, California 94720)

Abstract
Regarding the current econometric scene, in this review I argue that (a) traditional econometric modeling approaches do not provide a reliable basis for making inferences about the causal effect of a supposed treatment of data in observational and quasi-experimental settings; and (b) the focus on conventional reductionist models and information recovery methods has led to irrelevant economic theories and questionable inferences and has failed in terms of prediction and the extraction of information relative to the nature of underlying economic behavior systems. Looking ahead, a nontraditional econometric approach is outlined. This method recognizes that our knowledge regarding the underlying behavioral system and observed data process is complex, partial, and incomplete. It then suggests a self-organized, agent-based, algorithmic-representation system that involves networks, machine learning, and an information theoretic basis for estimation, inference, model evaluation, and prediction.

Suggested Citation

  • George Judge, 2016. "Some Comments on the Current State of Econometrics," Annual Review of Resource Economics, Annual Reviews, vol. 8(1), pages 1-6, October.
    • Handle: RePEc:anr:reseco:v:8:y:2016:p:1-6
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    File URL: http://www.annualreviews.org/doi/10.1146/annurev-resource-100815-095408
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    Citations

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    Cited by:

    1. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.

    More about this item

    Keywords

    stochastic inverse problems; information theoretic methods; nontraditional information recovery;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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