The Front-door Criterion in the Potential Outcome Framework

TL;DR

This paper integrates the front-door criterion into the potential outcome framework, clarifying assumptions, analyzing biases, and demonstrating its robustness and utility as an empirical causal inference tool in social sciences.

Contribution

It redefines the front-door criterion within the potential outcome model, compares it with instrumental variables, and explores its robustness under assumption violations.

Findings

FDC assumptions are more comprehensive in RCM.

FDC provides valid causal insights even when assumptions are violated.

Simulation confirms theoretical bias analysis.

Abstract

In recent years, the front-door criterion (FDC) has been increasingly noticed in economics and social science. However, most economists still resist collecting this tool in their empirical toolkit. This article aims to incorporate the FDC into the framework of the potential outcome model (RCM). It redefines the key assumptions of the FDC with the language of the RCM. These assumptions are more comprehensive and detailed than the original ones in the structure causal model (SCM). The causal connotations of the FDC estimates are elaborated in detail, and the estimation bias caused by violating some key assumptions is theoretically derived. Rigorous simulation data are used to confirm the theoretical derivation. It is proved that the FDC can still provide useful insights into causal relationships even when some key assumptions are violated. The FDC is also comprehensively compared with the instrumental variables (IV) from the perspective of assumptions and causal connotations. The analyses of this paper show that the FDC can serve as a powerful empirical tool. It can provide new insights into causal relationships compared with the conventional methods in social science.