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Exact p-Values for Network Interference

Citations

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Cited by:

  1. Susan Athey & Michael Luca, 2019. "Economists (and Economics) in Tech Companies," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 209-230, Winter.
  2. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing Attrition Bias in Field Experiments," Working Papers 202218, University of California at Riverside, Department of Economics, revised Oct 2022.
  3. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jul 2022.
  4. 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.
  5. Luofeng Liao & Yuan Gao & Christian Kroer, 2022. "Statistical Inference for Fisher Market Equilibrium," Papers 2209.15422, arXiv.org.
  6. Bet Caeyers & Marcel Fafchamps, 2016. "Exclusion Bias in the Estimation of Peer Effects," NBER Working Papers 22565, National Bureau of Economic Research, Inc.
  7. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
  8. Eckles Dean & Karrer Brian & Ugander Johan, 2017. "Design and Analysis of Experiments in Networks: Reducing Bias from Interference," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-23, March.
  9. Ariel Boyarsky & Hongseok Namkoong & Jean Pouget-Abadie, 2023. "Modeling Interference Using Experiment Roll-out," Papers 2305.10728, arXiv.org, revised Aug 2023.
  10. Björkegren, Daniel & Karaca, Burak Ceyhun, 2022. "Network adoption subsidies: A digital evaluation of a rural mobile phone program in Rwanda," Journal of Development Economics, Elsevier, vol. 154(C).
  11. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
  12. Guido W. Imbens, 2021. "Statistical Significance, p-Values, and the Reporting of Uncertainty," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 157-174, Summer.
  13. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
  14. Guillermo Cruces & Dario Tortarolo & Gonzalo Vazquez-Bare, 2022. "Design of two-stage experiments with an application to spillovers in tax compliance," IFS Working Papers W22/32, Institute for Fiscal Studies.
  15. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
  16. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
  17. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
  18. Evan Munro & Stefan Wager & Kuang Xu, 2021. "Treatment Effects in Market Equilibrium," Papers 2109.11647, arXiv.org, revised Jan 2023.
  19. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
  20. Tadao Hoshino & Takahide Yanagi, 2021. "Causal Inference with Noncompliance and Unknown Interference," Papers 2108.07455, arXiv.org, revised Oct 2023.
  21. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 202010, University of California at Riverside, Department of Economics, revised Mar 2020.
  22. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
  23. Ramesh Johari & Hannah Li & Inessa Liskovich & Gabriel Weintraub, 2020. "Experimental Design in Two-Sided Platforms: An Analysis of Bias," Papers 2002.05670, arXiv.org, revised Sep 2021.
  24. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
  25. Vasiliki Koutra & Steven G. Gilmour & Ben M. Parker & Andrew Mead, 2023. "Design of Agricultural Field Experiments Accounting for both Complex Blocking Structures and Network Effects," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 526-548, September.
  26. Luofeng Liao & Christian Kroer, 2023. "Statistical Inference and A/B Testing for First-Price Pacing Equilibria," Papers 2301.02276, arXiv.org, revised Jun 2023.
  27. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
  28. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
  29. Julius Owusu, 2023. "Randomization Inference of Heterogeneous Treatment Effects under Network Interference," Papers 2308.00202, arXiv.org, revised Jan 2024.
  30. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
  31. Toru Kitagawa & Guanyi Wang, 2020. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP59/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  32. Fredrik Savje, 2021. "Causal inference with misspecified exposure mappings: separating definitions and assumptions," Papers 2103.06471, arXiv.org, revised Mar 2023.
  33. Michael Pollmann, 2020. "Causal Inference for Spatial Treatments," Papers 2011.00373, arXiv.org, revised Jan 2023.
  34. Kosuke Imai & Zhichao Jiang, 2020. "Identification and sensitivity analysis of contagion effects in randomized placebo‐controlled trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1637-1657, October.
  35. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
  36. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
  37. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Dec 2023.
  38. Wooyong Jo & Sarang Sunder & Jeonghye Choi & Minakshi Trivedi, 2020. "Protecting Consumers from Themselves: Assessing Consequences of Usage Restriction Laws on Online Game Usage and Spending," Marketing Science, INFORMS, vol. 39(1), pages 117-133, January.
  39. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
  40. Tadao Hoshino & Takahide Yanagi, 2023. "Randomization Test for the Specification of Interference Structure," Papers 2301.05580, arXiv.org, revised Dec 2023.
  41. John McHale & Jason Harold & Jen-Chung Mei & Akhil Sasidharan & Anil Yadav, 2023. "Stars as catalysts: an event-study analysis of the impact of star-scientist recruitment on local research performance in a small open economy," Journal of Economic Geography, Oxford University Press, vol. 23(2), pages 343-369.
  42. Ramesh Johari & Hannah Li & Inessa Liskovich & Gabriel Y. Weintraub, 2022. "Experimental Design in Two-Sided Platforms: An Analysis of Bias," Management Science, INFORMS, vol. 68(10), pages 7069-7089, October.
  43. Vivek F. Farias & Andrew A. Li & Tianyi Peng & Andrew Zheng, 2022. "Markovian Interference in Experiments," Papers 2206.02371, arXiv.org, revised Jun 2022.
  44. Eric Auerbach & Max Tabord-Meehan, 2021. "The Local Approach to Causal Inference under Network Interference," Papers 2105.03810, arXiv.org, revised Jun 2023.
  45. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
  46. Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Apr 2023.
  47. Anish Agarwal & Sarah H. Cen & Devavrat Shah & Christina Lee Yu, 2022. "Network Synthetic Interventions: A Causal Framework for Panel Data Under Network Interference," Papers 2210.11355, arXiv.org, revised Oct 2023.
  48. Nathan Kallus, 2023. "Treatment Effect Risk: Bounds and Inference," Management Science, INFORMS, vol. 69(8), pages 4579-4590, August.
  49. Iavor Bojinov & David Simchi-Levi & Jinglong Zhao, 2023. "Design and Analysis of Switchback Experiments," Management Science, INFORMS, vol. 69(7), pages 3759-3777, July.
  50. Chabé-Ferret, Sylvain & Reynaud, Arnaud & Tène, Eva, 2021. "Water Quality, Policy Diffusion Effects and Farmers’ Behavior," TSE Working Papers 21-1229, Toulouse School of Economics (TSE).
  51. Toru Kitagawa & Guanyi Wang, 2021. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP28/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  52. 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.
  53. Silvia Noirjean & Marco Mariani & Alessandra Mattei & Fabrizia Mealli, 2020. "Exploiting network information to disentangle spillover effects in a field experiment on teens' museum attendance," Papers 2011.11023, arXiv.org, revised May 2022.
  54. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
  55. Hannah Li & Geng Zhao & Ramesh Johari & Gabriel Y. Weintraub, 2021. "Interference, Bias, and Variance in Two-Sided Marketplace Experimentation: Guidance for Platforms," Papers 2104.12222, arXiv.org.
  56. 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.
  57. Bryan S. Graham, 2019. "Network Data," CeMMAP working papers CWP71/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  58. Xiaokang Luo & Tirthankar Dasgupta & Minge Xie & Regina Y. Liu, 2021. "Leveraging the Fisher randomization test using confidence distributions: Inference, combination and fusion learning," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 777-797, September.
  59. Michael P. Leung & Pantelis Loupos, 2022. "Graph Neural Networks for Causal Inference Under Network Confounding," Papers 2211.07823, arXiv.org, revised Mar 2024.
  60. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.
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