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What is a relevant control?: An algorithmic proposal

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  • Delbianco Fernando
  • Tohmé Fernando

Abstract

Individualized inference (or prediction) is an approach to data analysis that is increasingly relevant thanks to the availability of large datasets. In this paper, we present an algorithm that starts by detecting the relevant observations for a given query. Further refinement of that subsample is obtained by selecting the ones with the largest Shapley values. The probability distribution over this selection allows to generate synthetic controls, which in turn can be used to generate a robust inference (or prediction). Data collected from repeating this procedure for different queries provides a deeper understanding of the general process that generates the data.

Suggested Citation

  • Delbianco Fernando & Tohmé Fernando, 2023. "What is a relevant control?: An algorithmic proposal," Asociación Argentina de Economía Política: Working Papers 4643, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4643
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    References listed on IDEAS

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    1. Min-ge Xie & Kesar Singh, 2013. "Confidence Distribution, the Frequentist Distribution Estimator of a Parameter: A Review," International Statistical Review, International Statistical Institute, vol. 81(1), pages 3-39, April.
    2. Xinran Li & Xiao-Li Meng, 2021. "A Multi-resolution Theory for Approximating Infinite-p-Zero-n: Transitional Inference, Individualized Predictions, and a World Without Bias-Variance Tradeoff," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(533), pages 353-367, January.
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    Cited by:

    1. Fernando Delbianco & Fernando Tohmé, 2025. "Identifying Highly Relevant Entries in Datasets: A Relevance-Based Classification," Journal of Classification, Springer;The Classification Society, vol. 42(3), pages 674-694, November.

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    More about this item

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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