Dr. Philipp Bach

Research Interests

• Estimation of causal effects and inference in high dimensionsal settings with machine learning methods
• Machine Learning and Deep Learning 
• Applications in labor, health and financial economics

Code

Code and supplemental materials of research projects and publications are available here. 

Publications

• Philipp Bach, Victor Chernozhukov, Malte S. Kurz, , Martin Spindler (2022).
  DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python.
  Journal of Machine Learning Research 23 (53), 1–6, available online.
• Philipp Bach, Helmut Farbmacher, Martin Spindler, Semiparametric count data modeling with an application to health service demand, Econometrics and Statistics, 8, 125-140, 2018, , available online.

Working Papers

• Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler, DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python, available at arxiv, 2021.
• Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler, DoubleML - An Object-Oriented Implementation of Double Machine Learning in R, available at arxiv, 2021.
  Philipp Bach, Victor Chernozhukov, Martin Spindler, Insights from Optimal Pandemic Shielding in a Multi-Group SEIR Framework, Working Paper, available at arxiv, 2020.
• Philipp Bach, Sven Klaassen, Jannis Kueck, Martin Spindler, Uniform Inference in High-Dimensional Generalized Additive Models, Working Paper, available at arXiv, 2020.
  Philipp Bach, Victor Chernozhukov, Martin Spindler, Closing the U.S. gender wage gap requires understanding its heterogeneity, Working Paper, available at arXiv, 2018.
• Philipp Bach, Victor Chernozhukov, Martin Spindler, Valid Simultaneous Inference in High-Dimensional Settings (with the HDM package for R), Working Paper, available at arXiv.
• Bach, Philipp, H. Farbmacher, and M. Spindler (2016): Semiparametric Count Data Modeling
  with an Application to Health Service Demand. No. 16/20. HEDG, c/o Department of Economics,
  University of York, 2016.

Education