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A hybrid econometric–machine learning approach for relative importance analysis: prioritizing food policy

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  • Akash Malhotra

    (Jawaharlal Nehru University)

Abstract

A measure of relative importance of variables is often desired by researchers when the explanatory aspects of econometric methods are of interest. To this end, the author briefly reviews the limitations of conventional econometrics in constructing a reliable measure of variable importance. The author highlights the relative stature of explanatory and predictive analysis in economics and the emergence of fruitful collaborations between econometrics and computer science. Learning lessons from both, the author proposes a hybrid approach based on conventional econometrics and advanced machine learning (ML) algorithms, which are otherwise, used in predictive analytics. The purpose of this article is two-fold: to propose a hybrid approach to assess relative importance and demonstrate its applicability in addressing policy priority issues with an example of food inflation in India, followed by a broader aim to introduce the possibility of conflation of ML and conventional econometrics to an audience of researchers in economics and social sciences, in general.

Suggested Citation

  • Akash Malhotra, 2021. "A hybrid econometric–machine learning approach for relative importance analysis: prioritizing food policy," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 549-581, September.
    • Handle: RePEc:spr:eurase:v:11:y:2021:i:3:d:10.1007_s40822-021-00170-9
    DOI: 10.1007/s40822-021-00170-9
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    More about this item

    Keywords

    Econometrics; Machine learning; Relative importance; Food policy;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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