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Michael Leung

Personal Details

First Name:Michael
Middle Name:
Last Name:Leung
Suffix:
RePEc Short-ID:ple912
[This author has chosen not to make the email address public]
http://mpleung.github.io

Affiliation

Economics Department
University of California-Santa Cruz (UCSC)

Santa Cruz, California (United States)
http://econ.ucsc.edu/
RePEc:edi:ecucsus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Michael P. Leung, 2024. "Causal Interpretation of Estimands Defined by Exposure Mappings," Papers 2403.08183, arXiv.org, revised Mar 2024.
  2. Michael P. Leung, 2023. "Cluster-Randomized Trials with Cross-Cluster Interference," Papers 2310.18836, arXiv.org, revised Nov 2024.
  3. Michael P. Leung & Pantelis Loupos, 2022. "Graph Neural Networks for Causal Inference Under Network Confounding," Papers 2211.07823, arXiv.org, revised Mar 2024.
  4. Michael P. Leung, 2021. "Rate-Optimal Cluster-Randomized Designs for Spatial Interference," Papers 2111.04219, arXiv.org, revised Sep 2022.
  5. Michael P. Leung, 2021. "Network Cluster-Robust Inference," Papers 2103.01470, arXiv.org, revised Feb 2023.
  6. Michael P. Leung, 2020. "Dependence-Robust Inference Using Resampled Statistics," Papers 2002.02097, arXiv.org, revised Aug 2021.
  7. Hossein Alidaee & Eric Auerbach & Michael P. Leung, 2020. "Recovering Network Structure from Aggregated Relational Data using Penalized Regression," Papers 2001.06052, arXiv.org.
  8. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2021.
  9. Michael P. Leung, 2019. "Inference in Models of Discrete Choice with Social Interactions Using Network Data," Papers 1911.07106, arXiv.org.
  10. Michael P. Leung & Hyungsik Roger Moon, 2019. "Normal Approximation in Large Network Models," Papers 1904.11060, arXiv.org, revised Oct 2024.

Articles

  1. Michael P Leung, 2024. "Discussion of ‘Causal inference with misspecified exposure mappings: separating definitions and assumptions’," Biometrika, Biometrika Trust, vol. 111(1), pages 17-20.
  2. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
  3. Michael P. Leung, 2022. "Dependence‐robust inference using resampled statistics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 270-285, March.
  4. Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
  5. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
  6. 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.
  7. Han Hong & Michael P Leung & Jessie Li, 2020. "Inference on finite-population treatment effects under limited overlap," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 32-47.
  8. Michael P. Leung, 2020. "Equilibrium computation in discrete network games," Quantitative Economics, Econometric Society, vol. 11(4), pages 1325-1347, November.
  9. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.
  10. Leung, Michael P., 2015. "Two-step estimation of network-formation models with incomplete information," Journal of Econometrics, Elsevier, vol. 188(1), pages 182-195.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Michael P. Leung, 2021. "Rate-Optimal Cluster-Randomized Designs for Spatial Interference," Papers 2111.04219, arXiv.org, revised Sep 2022.

    Cited by:

    1. Jinglong Zhao, 2024. "Experimental Design For Causal Inference Through An Optimization Lens," Papers 2408.09607, arXiv.org, revised Aug 2024.
    2. Michael P. Leung, 2023. "Cluster-Randomized Trials with Cross-Cluster Interference," Papers 2310.18836, arXiv.org, revised Nov 2024.
    3. Cruces, Guillermo & Tortarolo, Dario & Vazquez-Bare, Gonzalo, 2024. "Design of Partial Population Experiments with an Application to Spillovers in Tax Compliance," IZA Discussion Papers 17256, Institute of Labor Economics (IZA).
    4. Ke Sun & Linglong Kong & Hongtu Zhu & Chengchun Shi, 2024. "Optimal Treatment Allocation Strategies for A/B Testing in Partially Observable Time Series Experiments," Papers 2408.05342, arXiv.org, revised Oct 2024.
    5. Christopher Harshaw & Fredrik Savje & Yitan Wang, 2022. "A Design-Based Riesz Representation Framework for Randomized Experiments," Papers 2210.08698, arXiv.org, revised Oct 2022.
    6. Evan Munro & David Jones & Jennifer Brennan & Roland Nelet & Vahab Mirrokni & Jean Pouget-Abadie, 2023. "Causal Estimation of User Learning in Personalized Systems," Papers 2306.00485, arXiv.org.

  2. Michael P. Leung, 2021. "Network Cluster-Robust Inference," Papers 2103.01470, arXiv.org, revised Feb 2023.

    Cited by:

    1. Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023. "Causal clustering: design of cluster experiments under network interference," Papers 2310.14983, arXiv.org, revised Jan 2024.
    2. Ruoxuan Xiong & Alex Chin & Sean J. Taylor, 2024. "Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs," Papers 2406.06768, arXiv.org.
    3. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.

  3. Michael P. Leung, 2020. "Dependence-Robust Inference Using Resampled Statistics," Papers 2002.02097, arXiv.org, revised Aug 2021.

    Cited by:

    1. Kojevnikov, Denis & Song, Kyungchul, 2023. "Some impossibility results for inference with cluster dependence with large clusters," Other publications TiSEM 80b8e4ed-54bc-4a34-883f-f, Tilburg University, School of Economics and Management.
    2. Kojevnikov, Denis & Song, Kyungchul, 2023. "Some impossibility results for inference with cluster dependence with large clusters," Journal of Econometrics, Elsevier, vol. 237(2).

  4. Hossein Alidaee & Eric Auerbach & Michael P. Leung, 2020. "Recovering Network Structure from Aggregated Relational Data using Penalized Regression," Papers 2001.06052, arXiv.org.

    Cited by:

    1. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Sep 2024.
    2. Mohamed Mostagir & James Siderius, 2023. "Social Inequality and the Spread of Misinformation," Management Science, INFORMS, vol. 69(2), pages 968-995, February.
    3. Candelaria, Luis E. & Ura, Takuya, 2023. "Identification and inference of network formation games with misclassified links," Journal of Econometrics, Elsevier, vol. 235(2), pages 862-891.
    4. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    5. Hong, Shengjie & Su, Liangjun & Jiang, Tao, 2023. "Profile GMM estimation of panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 235(2), pages 927-948.
    6. Shujie Ma & Liangjun Su & Yichong Zhang, 2020. "Detecting Latent Communities in Network Formation Models," Papers 2005.03226, arXiv.org, revised Mar 2021.
    7. Alejandro Sanchez-Becerra, 2022. "The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment," Papers 2209.14391, arXiv.org.
    8. Steven Wilkins Reeves & Shane Lubold & Arun G. Chandrasekhar & Tyler H. McCormick, 2024. "Model-Based Inference and Experimental Design for Interference Using Partial Network Data," Papers 2406.11940, arXiv.org.

  5. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2021.

    Cited by:

    1. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    2. Michael P. Leung, 2021. "Rate-Optimal Cluster-Randomized Designs for Spatial Interference," Papers 2111.04219, arXiv.org, revised Sep 2022.
    3. Yike Wang & Chris Gu & Taisuke Otsu, 2024. "Graph Neural Networks: Theory for Estimation with Application on Network Heterogeneity," Papers 2401.16275, arXiv.org.
    4. Haoge Chang, 2023. "Design-based Estimation Theory for Complex Experiments," Papers 2311.06891, arXiv.org.
    5. Jinglong Zhao, 2024. "Experimental Design For Causal Inference Through An Optimization Lens," Papers 2408.09607, arXiv.org, revised Aug 2024.
    6. Michael P. Leung, 2021. "Network Cluster-Robust Inference," Papers 2103.01470, arXiv.org, revised Feb 2023.
    7. Ruonan Xu & Jeffrey M. Wooldridge, 2022. "A Design-Based Approach to Spatial Correlation," Papers 2211.14354, arXiv.org.
    8. Bora Kim, 2020. "Analysis of Randomized Experiments with Network Interference and Noncompliance," Papers 2012.13710, arXiv.org.
    9. Han, Kevin & Basse, Guillaume & Bojinov, Iavor, 2024. "Population interference in panel experiments," Journal of Econometrics, Elsevier, vol. 238(1).
    10. Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023. "Causal clustering: design of cluster experiments under network interference," Papers 2310.14983, arXiv.org, revised Jan 2024.
    11. Tadao Hoshino & Takahide Yanagi, 2023. "Randomization Test for the Specification of Interference Structure," Papers 2301.05580, arXiv.org, revised Dec 2023.
    12. Ruonan Xu, 2023. "Difference-in-Differences with Interference," Papers 2306.12003, arXiv.org, revised May 2024.
    13. Stefan Faridani & Paul Niehaus, 2022. "Linear estimation of average global effects," Papers 2209.14181, arXiv.org, revised Sep 2023.
    14. Tadao Hoshino & Takahide Yanagi, 2021. "Causal Inference with Noncompliance and Unknown Interference," Papers 2108.07455, arXiv.org, revised Oct 2023.
    15. Fredrik Savje, 2021. "Causal inference with misspecified exposure mappings: separating definitions and assumptions," Papers 2103.06471, arXiv.org, revised Mar 2023.
    16. Christopher Harshaw & Fredrik Savje & Yitan Wang, 2022. "A Design-Based Riesz Representation Framework for Randomized Experiments," Papers 2210.08698, arXiv.org, revised Oct 2022.
    17. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    18. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    19. Eric Auerbach & Max Tabord-Meehan, 2021. "The Local Approach to Causal Inference under Network Interference," Papers 2105.03810, arXiv.org, revised Jun 2023.
    20. Gonzalo Vazquez-Bare, 2020. "Causal Spillover Effects Using Instrumental Variables," Papers 2003.06023, arXiv.org, revised Dec 2021.
    21. Yuchen Hu & Stefan Wager, 2022. "Switchback Experiments under Geometric Mixing," Papers 2209.00197, arXiv.org, revised Apr 2024.
    22. Alejandro Sanchez-Becerra, 2022. "The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment," Papers 2209.14391, arXiv.org.
    23. Michael P. Leung & Pantelis Loupos, 2022. "Graph Neural Networks for Causal Inference Under Network Confounding," Papers 2211.07823, arXiv.org, revised Mar 2024.

  6. Michael P. Leung, 2019. "Inference in Models of Discrete Choice with Social Interactions Using Network Data," Papers 1911.07106, arXiv.org.

    Cited by:

    1. Bramoullé, Yann & Boucher, Vincent, 2020. "Binary Outcomes and Linear Interactions," CEPR Discussion Papers 15505, C.E.P.R. Discussion Papers.
    2. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
    3. Kojevnikov, Denis & Marmer, Vadim & Song, Kyungchul, 2021. "Limit theorems for network dependent random variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 882-908.
    4. Kiran Tomlinson & Austin R. Benson, 2022. "Graph-Based Methods for Discrete Choice," Papers 2205.11365, arXiv.org, revised Nov 2023.
    5. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jul 2022.
    6. Michael P. Leung, 2020. "Equilibrium computation in discrete network games," Quantitative Economics, Econometric Society, vol. 11(4), pages 1325-1347, November.

  7. Michael P. Leung & Hyungsik Roger Moon, 2019. "Normal Approximation in Large Network Models," Papers 1904.11060, arXiv.org, revised Oct 2024.

    Cited by:

    1. Shuyang Sheng & Xiaoting Sun, 2023. "Social Interactions with Endogenous Group Formation," Papers 2306.01544, arXiv.org.
    2. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    3. Anton Badev, 2021. "Nash Equilibria on (Un)Stable Networks," Econometrica, Econometric Society, vol. 89(3), pages 1179-1206, May.
    4. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
    5. Nathan Canen & Ko Sugiura, 2022. "Inference in Linear Dyadic Data Models with Network Spillovers," Papers 2203.03497, arXiv.org, revised Jun 2023.
    6. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.
    7. Michael P. Leung, 2022. "Dependence‐robust inference using resampled statistics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 270-285, March.
    8. 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.
    9. 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.

Articles

  1. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
    See citations under working paper version above.
  2. Michael P. Leung, 2022. "Dependence‐robust inference using resampled statistics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 270-285, March.
    See citations under working paper version above.
  3. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
    See citations under working paper version above.
  4. 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.

    Cited by:

    1. Yi Zhang & Kosuke Imai, 2023. "Individualized Policy Evaluation and Learning under Clustered Network Interference," Papers 2311.02467, arXiv.org, revised Feb 2024.
    2. Kojevnikov, Denis & Song, Kyungchul, 2023. "Some impossibility results for inference with cluster dependence with large clusters," Other publications TiSEM 80b8e4ed-54bc-4a34-883f-f, Tilburg University, School of Economics and Management.
    3. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    4. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    5. 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).
    6. Luofeng Liao & Yuan Gao & Christian Kroer, 2022. "Statistical Inference for Fisher Market Equilibrium," Papers 2209.15422, arXiv.org.
    7. Mikhail Mamonov & Anna Pestova & Steven Ongena, 2023. "“Crime and Punishment”? How Banks Anticipate and Propagate Global Financial Sanctions," CERGE-EI Working Papers wp753, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    8. Luofeng Liao & Christian Kroer, 2024. "Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions," Papers 2406.15522, arXiv.org, revised Aug 2024.
    9. Michael P. Leung, 2022. "Causal Inference Under Approximate Neighborhood Interference," Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
    10. Kojevnikov, Denis & Marmer, Vadim & Song, Kyungchul, 2021. "Limit theorems for network dependent random variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 882-908.
    11. Evan Munro & Xu Kuang & Stefan Wager, 2021. "Treatment Effects in Market Equilibrium," Papers 2109.11647, arXiv.org, revised Jun 2024.
    12. Julius Owusu, 2023. "Randomization Inference of Heterogeneous Treatment Effects under Network Interference," Papers 2308.00202, arXiv.org, revised Jan 2024.
    13. Bora Kim, 2020. "Analysis of Randomized Experiments with Network Interference and Noncompliance," Papers 2012.13710, arXiv.org.
    14. Han, Kevin & Basse, Guillaume & Bojinov, Iavor, 2024. "Population interference in panel experiments," Journal of Econometrics, Elsevier, vol. 238(1).
    15. Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023. "Causal clustering: design of cluster experiments under network interference," Papers 2310.14983, arXiv.org, revised Jan 2024.
    16. Tadao Hoshino & Takahide Yanagi, 2023. "Randomization Test for the Specification of Interference Structure," Papers 2301.05580, arXiv.org, revised Dec 2023.
    17. Koen Jochmans, 2020. "Peer effects and endogenous social interactions," Papers 2008.07886, arXiv.org.
    18. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    19. Schwartz, Jacob & Song, Kyungchul, 2024. "The law of large numbers for large stable matchings," Journal of Econometrics, Elsevier, vol. 241(1).
    20. Kojevnikov, Denis & Song, Kyungchul, 2023. "Some impossibility results for inference with cluster dependence with large clusters," Journal of Econometrics, Elsevier, vol. 237(2).
    21. Michael P. Leung, 2022. "Dependence‐robust inference using resampled statistics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 270-285, March.
    22. Luofeng Liao & Christian Kroer, 2023. "Statistical Inference and A/B Testing for First-Price Pacing Equilibria," Papers 2301.02276, arXiv.org, revised Jun 2023.
    23. Clemens Possnig & Andreea Rotu{a}rescu & Kyungchul Song, 2022. "Estimating Dynamic Spillover Effects along Multiple Networks in a Linear Panel Model," Papers 2211.08995, arXiv.org.
    24. Christopher Harshaw & Fredrik Savje & Yitan Wang, 2022. "A Design-Based Riesz Representation Framework for Randomized Experiments," Papers 2210.08698, arXiv.org, revised Oct 2022.
    25. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
    26. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    27. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    28. Eric Auerbach & Max Tabord-Meehan, 2021. "The Local Approach to Causal Inference under Network Interference," Papers 2105.03810, arXiv.org, revised Jun 2023.
    29. Tadao Hoshino, 2023. "Causal Interpretation of Linear Social Interaction Models with Endogenous Networks," Papers 2308.04276, arXiv.org, revised Oct 2023.
    30. 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).
    31. Gonzalo Vazquez-Bare, 2020. "Causal Spillover Effects Using Instrumental Variables," Papers 2003.06023, arXiv.org, revised Dec 2021.
    32. Yuchen Hu & Shuangning Li & Stefan Wager, 2021. "Average Direct and Indirect Causal Effects under Interference," Papers 2104.03802, arXiv.org, revised Jan 2022.

  5. Han Hong & Michael P Leung & Jessie Li, 2020. "Inference on finite-population treatment effects under limited overlap," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 32-47.

    Cited by:

    1. Chen, Xiaohong & Liu, Ying & Ma, Shujie & Zhang, Zheng, 2024. "Causal inference of general treatment effects using neural networks with a diverging number of confounders," Journal of Econometrics, Elsevier, vol. 238(1).
    2. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    3. Heiler, Phillip & Knaus, Michael C., 2022. "Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments," IZA Discussion Papers 15580, Institute of Labor Economics (IZA).
    4. George Gui & Harikesh Nair & Fengshi Niu, 2021. "Auction Throttling and Causal Inference of Online Advertising Effects," Papers 2112.15155, arXiv.org, revised Feb 2022.
    5. Pengzhou Wu & Kenji Fukumizu, 2021. "$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap," Papers 2110.05225, arXiv.org.

  6. Michael P. Leung, 2020. "Equilibrium computation in discrete network games," Quantitative Economics, Econometric Society, vol. 11(4), pages 1325-1347, November.

    Cited by:

    1. Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
    2. Herings, P. Jean-Jacques & Zhan, Yang, 2021. "The computation of pairwise stable networks," Research Memorandum 004, Maastricht University, Graduate School of Business and Economics (GSBE).

  7. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.

    Cited by:

    1. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large Bayesian game with heterogeneous beliefs," Journal of Econometrics, Elsevier, vol. 237(1).
    2. Kojevnikov, Denis & Marmer, Vadim & Song, Kyungchul, 2021. "Limit theorems for network dependent random variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 882-908.
    3. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    4. Shuyang Sheng, 2020. "A Structural Econometric Analysis of Network Formation Games Through Subnetworks," Econometrica, Econometric Society, vol. 88(5), pages 1829-1858, September.
    5. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large bayesian game with heterogeneous beliefs," Other publications TiSEM aca0631e-4f8a-45c7-af3a-4, Tilburg University, School of Economics and Management.
    6. Yiran Chen & Hanming Fang, 2017. "Inferring the Ideological Affiliations of Political Committees via Financial Contributions Networks," NBER Working Papers 24130, National Bureau of Economic Research, Inc.
    7. Gualdani, Cristina, 2021. "An econometric model of network formation with an application to board interlocks between firms," Journal of Econometrics, Elsevier, vol. 224(2), pages 345-370.
    8. Boucher, Vincent, 2020. "Equilibrium homophily in networks," European Economic Review, Elsevier, vol. 123(C).
    9. Bryan S. Graham, 2019. "Network Data," CeMMAP working papers CWP71/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Cristina Gualdani, 2021. "An Econometric Model of Network Formation with an Application to Board Interlocks between Firms," Post-Print hal-03548907, HAL.
    11. Michael P. Leung, 2022. "Dependence‐robust inference using resampled statistics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 270-285, March.
    12. Gao, Wayne Yuan, 2020. "Nonparametric identification in index models of link formation," Journal of Econometrics, Elsevier, vol. 215(2), pages 399-413.
    13. Konrad Menzel, 2021. "Bootstrap With Cluster‐Dependence in Two or More Dimensions," Econometrica, Econometric Society, vol. 89(5), pages 2143-2188, September.
    14. Alejandro Sanchez-Becerra, 2022. "The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment," Papers 2209.14391, arXiv.org.

  8. Leung, Michael P., 2015. "Two-step estimation of network-formation models with incomplete information," Journal of Econometrics, Elsevier, vol. 188(1), pages 182-195.

    Cited by:

    1. Luis E. Candelaria, 2020. "A Semiparametric Network Formation Model with Unobserved Linear Heterogeneity," Papers 2007.05403, arXiv.org, revised Aug 2020.
    2. HOSHINO Tadao & SHIMAMOTO Daichi & TODO Yasuyuki, 2017. "Accounting for Heterogeneity in Network Formation Behavior: An application to Vietnamese SMEs," Discussion papers 17023, Research Institute of Economy, Trade and Industry (RIETI).
    3. Shuyang Sheng & Xiaoting Sun, 2023. "Social Interactions with Endogenous Group Formation," Papers 2306.01544, arXiv.org.
    4. Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
    5. Wei Cheng, 2022. "Productivity spillovers in endogenous coauthor networks," Empirical Economics, Springer, vol. 63(6), pages 3159-3183, December.
    6. Candelaria, Luis E. & Ura, Takuya, 2020. "Identification and Inference of Network Formation Games with Misclassified Links," The Warwick Economics Research Paper Series (TWERPS) 1258, University of Warwick, Department of Economics.
    7. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    8. Anton Badev, 2021. "Nash Equilibria on (Un)Stable Networks," Econometrica, Econometric Society, vol. 89(3), pages 1179-1206, May.
    9. Andreas Dzemski, 2019. "An Empirical Model of Dyadic Link Formation in a Network with Unobserved Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 763-776, December.
    10. Dasaratha, Krishna, 2020. "Distributions of centrality on networks," Games and Economic Behavior, Elsevier, vol. 122(C), pages 1-27.
    11. Candelaria, Luis E. & Ura, Takuya, 2023. "Identification and inference of network formation games with misclassified links," Journal of Econometrics, Elsevier, vol. 235(2), pages 862-891.
    12. Geert Ridder & Shuyang Sheng, 2020. "Two-Step Estimation of a Strategic Network Formation Model with Clustering," Papers 2001.03838, arXiv.org, revised Nov 2022.
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Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Distinct Works, Weighted by Number of Authors and Recursive Impact Factors
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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 11 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (9) 2019-04-29 2019-12-02 2019-12-02 2020-02-03 2020-03-02 2021-12-06 2022-12-19 2023-12-11 2024-04-22. Author is listed
  2. NEP-NET: Network Economics (4) 2019-12-02 2020-02-03 2021-03-15 2022-12-19. Author is listed
  3. NEP-URE: Urban and Real Estate Economics (3) 2019-12-02 2019-12-02 2023-05-29. Author is listed
  4. NEP-DES: Economic Design (2) 2023-05-29 2023-12-11
  5. NEP-BIG: Big Data (1) 2022-12-19
  6. NEP-DCM: Discrete Choice Models (1) 2019-12-02
  7. NEP-EXP: Experimental Economics (1) 2023-05-29
  8. NEP-INV: Investment (1) 2024-04-22

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