References

Each chapter lists the works it cites at the bottom of its own page; the complete bibliography lives in references.bib in the book repository. Selected entries appear below. The main background references are Imbens and Rubin (2015) and Hernán and Robins (2020).

Angrist, Joshua D., and Jörn-Steffen Pischke. 2009. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press.

Blandhol, Christine, John Bonney, Magne Mogstad, and Alexander Torgovitsky. 2025. “When Is TSLS Actually LATE?”

Botosaru, Irene, and Laura Liu. 2025. “Time-Varying Heterogeneous Treatment Effects in Event Studies.” arXiv Preprint arXiv:2509.13698. https://arxiv.org/abs/2509.13698.

———. 2026. “Event Studies with Feedback.” AEA Papers and Proceedings 116: 70–74. https://doi.org/10.1257/pandp.20261110.

Chernozhukov, Victor, Mert Demirer, Esther Duflo, and Iván Fernández-Val. 2018. “Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments.” NBER Working Paper 24678.

Hernán, Miguel A. 2010. “The Hazards of Hazard Ratios.” Epidemiology 21 (1): 13–15.

Hernán, Miguel A., and James M. Robins. 2020. Causal Inference: What If. Chapman & Hall/CRC.

Imbens, Guido W., and Donald B. Rubin. 2015. Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge University Press.

Kennedy, Edward H. 2020. “Towards Optimal Doubly Robust Estimation of Heterogeneous Causal Effects.” arXiv Preprint arXiv:2004.14497.

Kennedy, Edward H., Zongming Ma, Matthew D. McHugh, and Dylan S. Small. 2017. “Non-Parametric Methods for Doubly Robust Estimation of Continuous Treatment Effects.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 79 (4): 1229–45.

Künzel, Sören R., Jasjeet S. Sekhon, Peter J. Bickel, and Bin Yu. 2019. “Metalearners for Estimating Heterogeneous Treatment Effects Using Machine Learning.” Proceedings of the National Academy of Sciences 116 (10): 4156–65.

Mullahy, John. 1997. “Instrumental-Variable Estimation of Count Data Models: Applications to Models of Cigarette Smoking Behavior.” Review of Economics and Statistics 79 (4): 586–93.

Nie, Xinkun, and Stefan Wager. 2021. “Quasi-Oracle Estimation of Heterogeneous Treatment Effects.” Biometrika 108 (2): 299–319.

Ramsey, J. B. 1969. “Tests for Specification Errors in Classical Linear Least-Squares Regression Analysis.” Journal of the Royal Statistical Society, Series B 31 (2): 350–71.

Rho, Saeyoung, Cyrus Illick, Samhitha Narasipura, Alberto Abadie, Daniel Hsu, and Vishal Misra. 2026. “Time-Aware Synthetic Control.” arXiv Preprint arXiv:2601.03099. https://arxiv.org/abs/2601.03099.

Rubin, Donald B. 1980. “Randomization Analysis of Experimental Data: The Fisher Randomization Test Comment.” Journal of the American Statistical Association 75 (371): 591–93.

Słoczyński, Tymon. 2022. “Interpreting OLS Estimands When Treatment Effects Are Heterogeneous: Smaller Groups Get Larger Weights.” The Review of Economics and Statistics 104 (3): 501–9.

———. 2024. “When Should We (Not) Interpret Linear IV Estimands as LATE?” Quantitative Economics.

Xu, Ruonan. 2023. “Difference-in-Differences with Interference.” arXiv Preprint arXiv:2306.12003. https://arxiv.org/abs/2306.12003.

———. 2026. “Dynamic Difference-in-Differences with Interference.” AEA Papers and Proceedings 116: 58–63. https://doi.org/10.1257/pandp.20261108.