2SLS with Multiple Treatments

2022/05/16 by Manudeep Bhuller, Bhuller, Manudeep, Henrik Sigstad +1 · 1 citation
Business, Management and Accounting · Mathematics · Economics, Econometrics and Finance · #Consumer Market Behavior and Pricing #Advanced Causal Inference Techniques #Merger and Competition Analysis

paper · pdf · doi:10.48550/arxiv.2205.07836

Abstract

We study what two-stage least squares (2SLS) identifies in models with multiple treatments under treatment effect heterogeneity. Two conditions are shown to be necessary and sufficient for the 2SLS to identify positively weighted sums of agent-specific effects of each treatment: average conditional monotonicity and no cross effects. Our identification analysis allows for any number of treatments, any number of continuous or discrete instruments, and the inclusion of covariates. We provide testable implications and present characterizations of choice behavior implied by our identification conditions.

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