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

Abstract

In this paper, we investigate the performance of fivecausality-detection methods and the aggregation of their resultswhen considering multiple units in a panel data setting. We employvoting rules as an aggregation procedure to determine which causalpaths are identified for the sample population. Using both simu-lated and real-world panel data, we show the performance of thesemethods in detecting the correct causal paths by comparing themto a benchmark that represents a standard growth model as theground truth.