This interdisciplinary project links insights from philosophy of science and econometrics in order to build a more solid framework to understand the meaning that causal notions have in economic contexts. The research provides a more integrated approach which encompasses the diverse meanings that causality takes in economic contexts, clarifying how they relate to each other. In addition to this conceptual clarification, the specific objectives of the project aim to improve the reliability and possibility of causal inference in three particular “non-standard” data settings, namely (1) the nonparametric, (2) the linear but nonnormal, and (3) the setting with aggregative structures. Extending the possibility of causal inference to these settings, which are likely to be encountered in macroeconomic empirical investigations, allows the researcher to take into better account the complexity of economic systems.
Causal Analysis in Economics: Philosophical Underpinnings and Econometric Tools for Non-Standard Settings