Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects

@inproceedings{Zhao2017QuantifyingHC,
  title={Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects},
  author={Jianing Zhao and Daniel M. Runfola and Peter Kemper},
  booktitle={ECML/PKDD},
  year={2017}
}
The World Bank provides billions of dollars in development finance to countries across the world every year. As many projects are related to the environment, we want to understand the World Bank projects impact to forest cover. However, the global extent of these projects results in substantial heterogeneity in impacts due to geographic, cultural, and other factors. Recent research by Athey and Imbens has illustrated the potential for hybrid machine learning and causal inferential techniques… 
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