Hugo Bodory, Federica Mascolo, Michael Lechner
arXiv 4 Jun 2024 · Econometrics · publishedAlgorithms (2024) · 3 citations (OpenAlex)
arXiv:2406.02241 · PDF · DOI · OpenAlex · Extracted main text
Decision-making plays a pivotal role in shaping outcomes in various disciplines, such as medicine, economics, and business. This paper provides guidance to practitioners on how to implement a decision tree designed to address treatment assignment policies using an interpretable and non-parametric algorithm. Our Policy Tree is motivated on the method proposed by Zhou, Athey, and Wager (2023), distinguishing itself for the policy score calculation, incorporating constraints, and handling categorical and continuous variables. We demonstrate the usage of the Policy Tree for multiple, discrete treatments on data sets from different fields. The Policy Tree is available in Python's open-source package mcf (Modified Causal Forest).
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Zhou, Athey \ Wager (2023) Offline multi-action policy learning: Generalization and optimization, Operations Research 71(1): 148–183 | 1.000 | 7 | 3 | 100% |
| 2 | Athey \ Wager (2021) Policy learning with observational data, Econometrica 89(1): 133–161 | 0.737 | 3 | 2 | 100% |
| 3 | Karlan \ Zinman (2008) Credit elasticities in less-developed economies: Implications for microfinance, American Economic Review 98(3): 1040–1068 | 0.644 | 4 | 1 | 100% |
| 4 | Finkelstein, Taubman, Wright, Bernstein, Gruber, Newhouse, Allen, Ba… (2012) The oregon health insurance experiment: evidence from the first year, The Quarterly journal of economics 127(3): 1057–1106 | 0.585 | 3 | 1 | 100% |
| 5 | Bodory, Busshoff \ Lechner (2022) High resolution treatment effects estimation: Uncovering effect heterogeneities with the modified causal forest, Entropy 24(8):… | 0.511 | 2 | 1 | 100% |
| 6 | Connors, Speroff, Dawson, Thomas, Harrell, Wagner, Desbiens, Goldman… (1996) The effectiveness of right heart catheterization in the initial care of critically iii patients, Jama 276(11): 889–897 | 0.511 | 2 | 1 | 100% |
| 7 | Kitagawa \ Tetenov (2018) Who should be treated? empirical welfare maximization methods for treatment choice, Econometrica 86(2): 591–616 | 0.511 | 2 | 1 | 100% |
| 8 | Ramsahai, Grieve \ Sekhon (2011) Extending iterative matching methods: an approach to improving covariate balance that allows prioritisation, Health Services and… | 0.511 | 2 | 1 | 100% |
| 9 | Carcillo \ Grubb (2006) From inactivity to work, (36) | 0.405 | 1 | 1 | 100% |
| 10 | Imbens \ Wooldridge (2009) Recent developments in the econometrics of program evaluation, Journal of Economic Literature 47(1): 5–86 | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 27 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Aggregation Trees | 0.405 | 1 | 1 |