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

Manuel de Mier (), Fernando Delbianco (), Fernando Tohmé, Luisina Patrizio, Facundo Rodriguez and Mauro Romero Stéfani
Additional contact information
Luisina Patrizio: UNS
Facundo Rodriguez: UNS
Mauro Romero Stéfani: UNS

No 260, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)

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 this 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 are currently incapable of detecting causal links, it is plausible that the ground “truth” may incorporate false relations.

Keywords: Granger causality; Transfer Entropy; Stochastic Causality; LiNGAM; Ground Truth; Economic Growth. (search for similar items in EconPapers)
JEL-codes: C18 C43 O47 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2023-07
New Economics Papers: this item is included in nep-ecm
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https://rednie.eco.unc.edu.ar/files/DT/260.pdf (application/pdf)

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Working Paper: Causality by Vote: Aggregating Evidence on Causal Relations in Economic Growth Processes (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:260

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