IDEAS home Printed from https://ideas.repec.org/f/pwe297.html
   My authors  Follow this author

Matthew D Webb

Personal Details

First Name:Matthew
Middle Name:D
Last Name:Webb
Suffix:
RePEc Short-ID:pwe297
[This author has chosen not to make the email address public]
https://sites.google.com/site/matthewdwebb/
Twitter: @mattdwebb
Terminal Degree:2013 Economics Department; Queen's University (from RePEc Genealogy)

Affiliation

Department of Economics
Carleton University

Ottawa, Canada
http://www.carleton.ca/economics/
RePEc:edi:decarca (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Software Chapters

Working papers

  1. Sunny Karim & Matthew D. Webb & Nichole Austin & Erin Strumpf, 2024. "Difference-in-Differences with Unpoolable Data," Papers 2403.15910, arXiv.org.
  2. Ardyn Nordstrom & Morgan Nordstrom & Matthew D. Webb, 2024. "Using Images as Covariates: Measuring Curb Appeal with Deep Learning," Papers 2403.19915, arXiv.org.
  3. Chen, Shi & Gangji, Areez & Karim, Sunny & McCanny, Anthony & Webb, Matthew D., 2024. "The Many Misspellings of Albuquerque: A Comment on 'Sorting or Steering: The Effects of Housing Discrimination on Neighborhood Choice'," I4R Discussion Paper Series 108, The Institute for Replication (I4R).
  4. Sunny Karim & Matthew Webb & Nicole Austin & Erin Strumpf, 2023. "Difference in differences with unpoolable data," Canadian Stata Conference 2023 03, Stata Users Group.
  5. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2023. "Testing for the appropriate level of clustering in linear regression models," Papers 2301.04522, arXiv.org, revised Mar 2023.
  6. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2023. "Fast and Reliable Jackknife and Bootstrap Methods for Cluster-Robust Inference," Papers 2301.04527, arXiv.org, revised Feb 2023.
  7. Matthew Webb, 2023. "Jackknife methods for improved cluster–robust inference," Canadian Stata Conference 2023 01, Stata Users Group.
  8. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," Papers 2205.03285, arXiv.org.
  9. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2022. "Leverage, Influence, and the Jackknife in Clustered Regression Models: Reliable Inference Using summclust," Papers 2205.03288, arXiv.org, revised Nov 2023.
  10. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
  11. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2020. "Wild Bootstrap and Asymptotic Inference with Multiway Clustering," CREATES Research Papers 2020-06, Department of Economics and Business Economics, Aarhus University.
  12. Matthew D. Webb, 2019. "Finish It and It’s Free: An Evaluation of College Graduation Subsidies," Carleton Economic Papers 19-08, Carleton University, Department of Economics.
  13. James G. MacKinnon & Matthew D. Webb, 2018. "Wild Bootstrap Randomization Inference For Few Treated Clusters," Working Paper 1404, Economics Department, Queen's University.
  14. Warman, Casey & Webb, Matthew D. & Worswick, Christopher, 2018. "Immigrant Category of Admission and the Earnings of Adults and Children: How far does the Apple Fall?," GLO Discussion Paper Series 196, Global Labor Organization (GLO).
  15. James G. MacKinnon & Morten Ørregaard Nielsen & David Roodman & Matthew D. Webb, 2018. "Fast and Wild: Bootstrap Inference in Stata Using boottest," CREATES Research Papers 2018-34, Department of Economics and Business Economics, Aarhus University.
  16. James G. MacKinnon & Matthew D. Webb, 2017. "The Wild Bootstrap For Few (treated) Clusters," Working Paper 1364, Economics Department, Queen's University.
  17. Brennan S. Thompson & Matthew D. Webb, 2017. "A simple, graphical approach to comparing multiple treatment," Canadian Stata Users' Group Meetings 2017 01, Stata Users Group.
  18. James G. MacKinnon & Matthew D. Webb, 2017. "Pitfalls When Estimating Treatment Effects Using Clustered Data," Working Paper 1387, Economics Department, Queen's University.
  19. James G. MacKinnon & Matthew D. Webb & Morten Ø. Nielsen, 2017. "Bootstrap And Asymptotic Inference With Multiway Clustering," Working Paper 1386, Economics Department, Queen's University.
  20. James G. MacKinnon & Matthew D. Webb, 2017. "The multiway cluster wild bootstrap," Canadian Stata Users' Group Meetings 2017 06, Stata Users Group.
  21. David B. Johnson & Matthew D. Webb, 2017. "An Experimental Test of the No Safety Schools Theorem," Carleton Economic Papers 17-10, Carleton University, Department of Economics.
  22. Webb, Matthew D. & Warman, Casey & Sweetman, Arthur, 2016. "Targeting Tax Relief at Youth Employment," IZA Discussion Papers 10182, Institute of Labor Economics (IZA).
  23. James G. MacKinnon & Matthew D. Webb, 2016. "Randomization Inference for Difference-in-Differences with Few Treated Clusters," Carleton Economic Papers 16-11, Carleton University, Department of Economics.
  24. Casey Warman & Christopher Worswick & Matthew Webb, 2016. "Immigrant Category of Admission of the Parents and Outcomes of the Children: How far does the Apple Fall?," RF Berlin - CReAM Discussion Paper Series 1618, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
  25. James G. MacKinnon & Matthew D. Webb, 2016. "The Subcluster Wild Bootstrap for Few (Treated) Clusters," Carleton Economic Papers 16-13, Carleton University, Department of Economics.
  26. David B. Johnson & Matthew D. Webb, 2016. "Decision Making with Risky, Rival Outcomes: Theory and Evidence," Carleton Economic Papers 16-12, Carleton University, Department of Economics.
  27. James G. MacKinnon & Matthew D. Webb, 2015. "Wild Bootstrap Inference For Wildly Different Cluster Sizes," Working Paper 1314, Economics Department, Queen's University.
  28. Matthew D. Webb, 2014. "Reworking Wild Bootstrap Based Inference For Clustered Errors," Working Paper 1315, Economics Department, Queen's University.
  29. Arthur Sweetman & Matthew D. Webb & Casey Warman, 2014. "How Targeted Is Targeted Tax Relief? Evidence From The Unemployment Insurance Youth Hires Program," Working Paper 1298, Economics Department, Queen's University.
    repec:ags:quedwp:274713 is not listed on IDEAS
    repec:ags:quedwp:274639 is not listed on IDEAS
    repec:ags:quedwp:274730 is not listed on IDEAS
  30. Matthew Webb, "undated". "One Sided Matching: Choice Selection With Rival Uncertain Outcomes," Working Papers 2015-11, Department of Economics, University of Calgary, revised 08 Jul 2015.

    repec:ags:quedwp:274618 is not listed on IDEAS
    repec:ags:quedwp:274640 is not listed on IDEAS
    repec:ags:quedwp:274712 is not listed on IDEAS
    repec:ags:quedwp:274690 is not listed on IDEAS
    repec:ags:quedwp:274681 is not listed on IDEAS

Articles

  1. Mikola, Derek & Webb, Matthew D., 2023. "Finish it and it is free: An evaluation of college graduation subsidies," Economics of Education Review, Elsevier, vol. 93(C).
  2. Matthew D. Webb, 2023. "Reworking wild bootstrap‐based inference for clustered errors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(3), pages 839-858, August.
  3. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
  4. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Testing for the appropriate level of clustering in linear regression models," Journal of Econometrics, Elsevier, vol. 235(2), pages 2027-2056.
  5. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
  6. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Fast and reliable jackknife and bootstrap methods for cluster‐robust inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 671-694, August.
  7. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2021. "Wild Bootstrap and Asymptotic Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 505-519, March.
  8. MacKinnon, James G. & Webb, Matthew D., 2020. "Randomization inference for difference-in-differences with few treated clusters," Journal of Econometrics, Elsevier, vol. 218(2), pages 435-450.
  9. Casey Warman & Matthew D. Webb & Christopher Worswick, 2019. "Immigrant category of admission and the earnings of adults and children: how far does the apple fall?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 32(1), pages 53-112, January.
  10. Brennan S Thompson & Matthew D Webb, 2019. "A simple, graphical approach to comparing multiple treatments," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 188-205.
  11. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LP, vol. 19(1), pages 4-60, March.
  12. James G. MacKinnon & Matthew D. Webb, 2018. "The wild bootstrap for few (treated) clusters," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 114-135, June.
  13. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
  14. Matthew D. Webb & Arthur Sweetman & Casey Warman, 2016. "Targeting Tax Relief at Youth Employment," Canadian Public Policy, University of Toronto Press, vol. 42(4), pages 415-430, December.

Software components

  1. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2022. "SUMMCLUST: Stata module to compute cluster level measures of leverage, influence, and a cluster jackknife variance estimator," Statistical Software Components S459072, Boston College Department of Economics, revised 05 Jul 2023.

Chapters

  1. James G. MacKinnon & Matthew D. Webb, 2019. "Wild Bootstrap Randomization Inference for Few Treated Clusters," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 61-85, Emerald Group Publishing Limited.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Citations, Discounted by Citation Age
  2. Number of Citations, Weighted by Simple Impact Factor, Discounted by Citation Age
  3. Number of Citations, Weighted by Recursive Impact Factor, Discounted by Citation Age
  4. Number of Citations, Weighted by Number of Authors, Discounted by Citation Age
  5. Number of Citations, Weighted by Number of Authors and Simple Impact Factors, Discounted by Citation Age
  6. Number of Citations, Weighted by Number of Authors and Recursive Impact Factors, Discounted by Citation Age
  7. Number of Abstract Views in RePEc Services over the past 12 months
  8. Number of Downloads through RePEc Services over the past 12 months
  9. Number of Abstract Views in RePEc Services over the past 12 months, Weighted by Number of Authors
  10. Number of Downloads through RePEc Services over the past 12 months, Weighted by Number of Authors
  11. Breadth of citations across fields
  12. Wu-Index

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 29 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 (15) 2013-08-23 2013-08-31 2016-02-23 2016-07-16 2016-09-11 2017-08-27 2017-10-08 2018-04-02 2019-04-08 2019-08-26 2020-04-27 2021-04-12 2022-03-28 2022-04-18 2022-06-27. Author is listed
  2. NEP-ORE: Operations Research (8) 2017-08-27 2017-09-24 2019-04-08 2019-08-26 2020-04-27 2020-07-20 2021-04-12 2022-04-18. Author is listed
  3. NEP-EXP: Experimental Economics (3) 2015-07-18 2016-09-18 2017-09-17
  4. NEP-SOG: Sociology of Economics (3) 2016-09-18 2016-09-18 2016-09-18
  5. NEP-UPT: Utility Models and Prospect Theory (3) 2015-07-18 2016-09-18 2017-09-17
  6. NEP-CBE: Cognitive and Behavioural Economics (2) 2015-07-18 2016-09-18
  7. NEP-EDU: Education (2) 2018-05-07 2019-10-07
  8. NEP-ETS: Econometric Time Series (2) 2019-04-08 2019-08-26
  9. NEP-LAB: Labour Economics (2) 2016-09-04 2016-10-30
  10. NEP-MIG: Economics of Human Migration (2) 2016-10-30 2018-05-07
  11. NEP-DCM: Discrete Choice Models (1) 2022-07-11
  12. NEP-DEM: Demographic Economics (1) 2016-10-30
  13. NEP-GER: German Papers (1) 2016-07-16
  14. NEP-GTH: Game Theory (1) 2015-07-18
  15. NEP-HEA: Health Economics (1) 2023-09-18
  16. NEP-IAS: Insurance Economics (1) 2012-10-27
  17. NEP-PBE: Public Economics (1) 2016-09-04

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Matthew D Webb should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.