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Maxwell Dylan Kellogg

Personal Details

First Name:Maxwell
Middle Name:Dylan
Last Name:Kellogg
Suffix:
RePEc Short-ID:pke421
[This author has chosen not to make the email address public]
https://sites.google.com/view/maxkellogg

Affiliation

Økonomisk institutt
Universitetet i Oslo

Oslo, Norway
http://www.oekonomi.uio.no/
RePEc:edi:souiono (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Maxwell Kellogg & Magne Mogstad & Guillaume Pouliot & Alexander Torgovitsky, 2020. "Combining Matching and Synthetic Control to Trade off Biases from Extrapolation and Interpolation," NBER Working Papers 26624, National Bureau of Economic Research, Inc.

Articles

  1. Maxwell Kellogg & Magne Mogstad & Guillaume A. Pouliot & Alexander Torgovitsky, 2021. "Combining Matching and Synthetic Control to Tradeoff Biases From Extrapolation and Interpolation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1804-1816, October.

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. Maxwell Kellogg & Magne Mogstad & Guillaume Pouliot & Alexander Torgovitsky, 2020. "Combining Matching and Synthetic Control to Trade off Biases from Extrapolation and Interpolation," NBER Working Papers 26624, National Bureau of Economic Research, Inc.

    Cited by:

    1. Billy Ferguson & Brad Ross, 2020. "Assessing the Sensitivity of Synthetic Control Treatment Effect Estimates to Misspecification Error," Papers 2012.15367, arXiv.org, revised Feb 2021.
    2. Michael Pollmann, 2020. "Causal Inference for Spatial Treatments," Papers 2011.00373, arXiv.org, revised Jan 2023.
    3. Jonne Lehtimäki & David Sondermann, 2022. "Baldwin versus Cecchini revisited: the growth impact of the European Single Market," Empirical Economics, Springer, vol. 63(2), pages 603-635, August.
    4. Robert Clark & Christopher Anthony Fabiilli & Laura Lasio, 2021. "Collusion in the US Generic Drug Industry," Working Paper 1474, Economics Department, Queen's University.
    5. Roberta Di Stefano & Giovanni Mellace, 2020. "The inclusive synthetic control method," Working Papers 21/20, Sapienza University of Rome, DISS.
    6. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.
    7. Brantly Callaway & Tong Li, 2021. "Policy Evaluation during a Pandemic," Papers 2105.06927, arXiv.org, revised Oct 2022.
    8. Sondermann, David & Lehtimäki, Jonne, 2020. "Baldwin vs. Cecchini revisited: the growth impact of the European Single Market," Working Paper Series 2392, European Central Bank.
    9. Hollingsworth, Alex & Wing, Coady, 2020. "Tactics for design and inference in synthetic control studies: An applied example using high-dimensional data," SocArXiv fc9xt, Center for Open Science.

Articles

  1. Maxwell Kellogg & Magne Mogstad & Guillaume A. Pouliot & Alexander Torgovitsky, 2021. "Combining Matching and Synthetic Control to Tradeoff Biases From Extrapolation and Interpolation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1804-1816, October.

    Cited by:

    1. Omid M. Ardakani & N. Kundan Kishor & Suyong Song, 2024. "Does membership of the EMU matter for economic and financial outcomes?," Contemporary Economic Policy, Western Economic Association International, vol. 42(3), pages 416-447, July.
    2. Rong J. B. Zhu, 2023. "Synthetic Regressing Control Method," Papers 2306.02584, arXiv.org, revised Oct 2023.
    3. Guillaume Allaire Pouliot & Zhen Xie, 2022. "Degrees of Freedom and Information Criteria for the Synthetic Control Method," Papers 2207.02943, arXiv.org.
    4. Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.
    5. Marco Francesconi & Jonathan James, 2022. "Alcohol Price Floors and Externalities: The Case of Fatal Road Crashes," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(4), pages 1118-1156, September.
    6. Brantly Callaway & Sonia Karami, 2020. "Treatment Effects in Interactive Fixed Effects Models with a Small Number of Time Periods," Papers 2006.15780, arXiv.org, revised Feb 2022.
    7. Zongwu Cai & Ying Fang & Ming Lin & Zixuan Wu, 2023. "A Quasi Synthetic Control Method for Nonlinear Models With High-Dimensional Covariates," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202305, University of Kansas, Department of Economics, revised Aug 2023.
    8. Bogatyrev, Konstantin & Stoetzer, Lukas, 2024. "Synthetic Control Methods for Proportions," OSF Preprints brhd3, Center for Open Science.
    9. Roberta Di Stefano & Giovanni Mellace, 2020. "The inclusive synthetic control method," Working Papers 21/20, Sapienza University of Rome, DISS.
    10. Guido W. Imbens & Davide Viviano, 2023. "Identification and Inference for Synthetic Controls with Confounding," Papers 2312.00955, arXiv.org.
    11. Sandro Heiniger, 2024. "Data-driven model selection within the matrix completion method for causal panel data models," Papers 2402.01069, arXiv.org.
    12. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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 (1) 2020-01-20. Author is listed

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