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Causality by Vote: Aggregating Evidence on Causal Relations in Economic Growth Processes

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  • De Mier Manuel
  • Delbianco Fernando
  • Tohmé Fernando
  • Patrizio Luisina
  • Rodriguez Facundo
  • Stéfani Mauro

Abstract

In this paper we investigate the performance of five causality-detection methods and how their results can be aggregated when multiple units are considered in a panel data setting. The aggregation procedure employs voting rules for determining which causal paths are identified for the sample population. Using simulated and real-world panel data, we show the performance of these methods in detecting the correct causal paths in comparison to a benchmark that comprises a standard representation of growth processes as ground truth model. We find that the results may be better when only simulated, instead of real-world, data are analyzed. While this may suggest that the methods presented here are currently incapable of detecting causal links, it is plausible that the ground ``truth'' may incorporate false relations.

Suggested Citation

  • De Mier Manuel & Delbianco Fernando & Tohmé Fernando & Patrizio Luisina & Rodriguez Facundo & Stéfani Mauro, 2023. "Causality by Vote: Aggregating Evidence on Causal Relations in Economic Growth Processes," Asociación Argentina de Economía Política: Working Papers 4641, Asociación Argentina de Economía Política.
    • Handle: RePEc:aep:anales:4641
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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