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

Manuel de Mier (), Fernando Delbianco (), Fernando Tohmé, Luisina Patrizio, Facundo Luisina and Mauro Stéfani

No 4641, Asociación Argentina de Economía Política: Working Papers from Asociación Argentina de Economía Política

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.

JEL-codes: C18 C43 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2023-11
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Working Paper: Causality by Vote: Aggregating Evidence on Causal Relations in Economic Growth Processes (2023)
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