arXiv 12 Nov 2023 · Econometrics · 2 citations (OpenAlex)
arXiv:2311.06891 · PDF · DOI · OpenAlex · Extracted main text
This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units. We develop a design-based estimation theory for arbitrary experimental designs. Our theory facilitates the analysis of many design-estimator pairs that researchers commonly employ in practice and provide procedures to consistently estimate asymptotic variance bounds. We propose new classes of estimators with favorable asymptotic properties from a design-based point of view. In addition, we propose a scalar measure of experimental complexity which can be linked to the design-based variance of the estimators. We demonstrate the performance of our estimators using simulated datasets based on an actual network experiment studying the effect of social networks on insurance adoptions.
appendix boundary found by appendix_titled_section at “Proof for Results in Appendix \ref{network_experiments}” · 84% of the source is main text. Read the extracted text to check this.
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 | Aronow, Peter M and Cyrus Samii (2017) Estimating average causal effects under general interference, with application to a social network experiment | 1.000 | 8 | 4 | 100% |
| 2 | Horn, Roger A and Charles R Johnson (2012) Matrix analysis | 0.928 | 5 | 4 | 80% |
| 3 | Imbens, Guido W and Donald B Rubin (2015) Causal inference in statistics, social, and biomedical sciences | 0.928 | 5 | 4 | 80% |
| 4 | Guo, Kevin and Guillaume Basse (2021) The generalized oaxaca-blinder estimator | 0.928 | 4 | 3 | 100% |
| 5 | Cai, Jing, Alain De Janvry, and Elisabeth Sadoulet (2015) Social networks and the decision to insure | 0.923 | 14 | 3 | 79% |
| 6 | Middleton, Joel A (2021) b): Unifying Design-based Inference: On bounding and estimating the variance of any linear estimator in any experimental design | 0.874 | 11 | 2 | 100% |
| 7 | Lin, Winston (2013) Agnostic notes on regression adjustments to experimental data: Reexamining Freedman’s critique | 0.874 | 9 | 2 | 100% |
| 8 | Cohen, Peter L and Colin B Fogarty (2020) No-harm calibration for generalized oaxaca-blinder estimators | 0.874 | 5 | 2 | 100% |
| 9 | Middleton, Joel A (2018) A unified theory of regression adjustment for design-based inference | 0.874 | 5 | 2 | 100% |
| 10 | Freedman, David A (2008) b): On regression adjustments to experimental data | 0.811 | 4 | 2 | 100% |
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