Large Sample Randomization Inference of Causal Effects in the Presence of Interference
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DOI: 10.1080/01621459.2013.844698
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Cited by:
- Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2020.
"Treatment Effects With Heterogeneous Externalities,"
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- Patacchini, Eleonora & Rainone, Edoardo, 2019. "Treatment Effects with Heterogeneous Externalities," CEPR Discussion Papers 13781, C.E.P.R. Discussion Papers.
- Yi Zhang & Kosuke Imai, 2023. "Individualized Policy Evaluation and Learning under Clustered Network Interference," Papers 2311.02467, arXiv.org, revised Feb 2024.
- Clarke, Damian, 2017. "Estimating Difference-in-Differences in the Presence of Spillovers," MPRA Paper 81604, University Library of Munich, Germany.
- Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Efficient Treatment Effect Estimation in Observational Studies under Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2022.
- Alan Andre Borges da Costa & Sergio Pinheiro Firpo, 2018. "An analysis of the distributive effects of public policies and their spillovers," Working Papers, Department of Economics 2018_06, University of São Paulo (FEA-USP).
- Denis Fougère & Nicolas Jacquemet, 2020.
"Policy Evaluation Using Causal Inference Methods,"
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers)
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- Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Working Papers hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Post-Print hal-03098058, HAL.
- Fougère, Denis & Jacquemet, Nicolas, 2020. "Policy Evaluation Using Causal Inference Methods," IZA Discussion Papers 12922, Institute of Labor Economics (IZA).
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2019.
"Causal Inference and Impact Evaluation,"
Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 181-200.
- Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," SciencePo Working papers Main hal-02866828, HAL.
- Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02866828, HAL.
- Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," Post-Print hal-02866828, HAL.
- Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," PSE-Ecole d'économie de Paris (Postprint) hal-02866828, HAL.
- David Choi, 2017. "Estimation of Monotone Treatment Effects in Network Experiments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1147-1155, July.
- Evan Munro & Stefan Wager & Kuang Xu, 2021. "Treatment Effects in Market Equilibrium," Papers 2109.11647, arXiv.org, revised Jan 2023.
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- Julius Owusu, 2023. "Randomization Inference of Heterogeneous Treatment Effects under Network Interference," Papers 2308.00202, arXiv.org, revised Jan 2024.
- Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
- Zhichao Jiang & Kosuke Imai & Anup Malani, 2023. "Statistical inference and power analysis for direct and spillover effects in two‐stage randomized experiments," Biometrics, The International Biometric Society, vol. 79(3), pages 2370-2381, September.
- A. Giffin & B. J. Reich & S. Yang & A. G. Rappold, 2023. "Generalized propensity score approach to causal inference with spatial interference," Biometrics, The International Biometric Society, vol. 79(3), pages 2220-2231, September.
- Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
- Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
- Karlsson, Maria & Lundin, Mathias, 2016. "On statistical methods for labor market evaluation under interference between units," Working Paper Series 2016:24, IFAU - Institute for Evaluation of Labour Market and Education Policy.
- Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Apr 2023.
- Rigdon, Joseph & Hudgens, Michael G., 2015. "Exact confidence intervals in the presence of interference," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 130-135.
- Jizhou Liu, 2023. "Inference for Two-stage Experiments under Covariate-Adaptive Randomization," Papers 2301.09016, arXiv.org, revised Oct 2023.
- Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
- Melanie Prague & Rui Wang & Alisa Stephens & Eric Tchetgen Tchetgen & Victor DeGruttola, 2016. "Accounting for interactions and complex inter‐subject dependency in estimating treatment effect in cluster‐randomized trials with missing outcomes," Biometrics, The International Biometric Society, vol. 72(4), pages 1066-1077, December.
- Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.
- Lan Liu & Eric Tchetgen Tchetgen, 2022. "Regression‐based negative control of homophily in dyadic peer effect analysis," Biometrics, The International Biometric Society, vol. 78(2), pages 668-678, June.
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