The Nudge Average Treatment Effect

TL;DR

This paper introduces the Nudge Average Treatment Effect, a new identification strategy for instrumental variable analysis that accounts for defiers and heterogeneity, expanding causal inference capabilities.

Contribution

It proposes an alternative condition to monotonicity, enabling the estimation of causal effects in the presence of defiers and heterogeneity.

Findings

Recovers average causal effect for manipulable subgroup

Accommodates defiers and heterogeneity

Extends IV methodology beyond traditional assumptions

Abstract

The instrumental variable method is a prominent approach to recover under certain conditions, valid inference about a treatment causal effect even when unmeasured confounding might be present. In a groundbreaking paper, Imbens and Angrist (1994) established that a valid instrument nonparametrically identifies the average causal effect among compliers, also known as the local average treatment effect under a certain monotonicity assumption which rules out the existence of so-called defiers. An often-cited attractive property of monotonicity is that it facilitates a causal interpretation of the instrumental variable estimand without restricting the degree of heterogeneity of the treatment causal effect. In this paper, we introduce an alternative equally straightforward and interpretable condition for identification, which accommodates both the presence of defiers and heterogenous treatment effects. Mainly, we show that under our new conditions, the instrumental variable estimand recovers the average causal effect for the subgroup of units for whom the treatment is manipulable by the instrument, a subgroup which may consist of both defiers and compliers, therefore recovering an effect estimand we aptly call the Nudge Average Treatment Effect.