Introduction

Social-impact investing seeks positive social outcomes, but quantifying causality is difficult: correlation between company social investment and social outcomes doesn't imply causality. Causal inference methods identify companies creating genuine social impact vs greenwashing.

Causal Inference for Impact

Use difference-in-differences, propensity score matching, and instrumental variables to isolate causal social impact. Compare regions with company social programs to matched controls without programs. Estimate causal treatment effects. Distinguish genuine social impact from selection bias (company already serves communities more advanced than average).

Application

Identify companies creating genuine social impact. Support these with capital. Avoid companies claiming impact without causal evidence of effect.

Conclusion

Causal inference methods enable rigorous social-impact assessment, improving authenticity of social-impact investing.