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

Manuel de Mier (manueldemier@gmail.com), Fernando Delbianco (fernando.delbianco@uns.edu.ar), 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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