What is a relevant control?: An algorithmic proposal

Fernando Delbianco () and Fernando Tohmé

No 269, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)

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.

Keywords: Individualized inference; Relevance selection; and classification; Synthetic controls (search for similar items in EconPapers)
JEL-codes: C15 C6 C63 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2023-08
New Economics Papers: this item is included in nep-ecm and nep-gth
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https://rednie.eco.unc.edu.ar/files/DT/269.pdf (application/pdf)

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Working Paper: What is a relevant control?: An algorithmic proposal (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:269

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