IDEAS home Printed from https://ideas.repec.org/a/sae/jocore/v61y2017i7p1537-1564.html
   My bibliography  Save this article

Solving the Problem of Unattributed Political Violence

Author

Listed:
  • Vincent Bauer
  • Keven Ruby
  • Robert Pape

Abstract

High rates of missing perpetrator information in political violence data pose a serious challenge for studies into militant group behavior and the microdynamics of conflict more generally. In this article we introduce multiple imputation (MI) as the best available method for minimizing the impact of missing perpetrator information on quantitative analyses of political violence, a method that can easily be incorporated into most quantitative research designs. MI will produce unbiased attributions when the reasons for missingness are known and can be controlled for using observed variables, rendering responsibility for unclaimed attacks, “missing at random†(MAR) – which we show is a reasonable assumption in the case of political violence based on current theory of militant group claiming. We lay out the logics and steps of MI, identify variables and data sources, and demonstrate that MI produced better results in the case of the Pakistani Taliban’s response to drone strikes.

Suggested Citation

  • Vincent Bauer & Keven Ruby & Robert Pape, 2017. "Solving the Problem of Unattributed Political Violence," Journal of Conflict Resolution, Peace Science Society (International), vol. 61(7), pages 1537-1564, August.
  • Handle: RePEc:sae:jocore:v:61:y:2017:i:7:p:1537-1564
    DOI: 10.1177/0022002715612575
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0022002715612575
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0022002715612575?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Shellman, Stephen M., 2004. "Time Series Intervals and Statistical Inference: The Effects of Temporal Aggregation on Event Data Analysis," Political Analysis, Cambridge University Press, vol. 12(1), pages 97-104, January.
    2. White, Ian R. & Daniel, Rhian & Royston, Patrick, 2010. "Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2267-2275, October.
    3. David A Jaeger & Zahra Siddique, 2018. "Are Drone Strikes Effective in Afghanistan and Pakistan? On the Dynamics of Violence between the United States and the Taliban," CESifo Economic Studies, CESifo Group, vol. 64(4), pages 667-697.
    4. King, Gary & Honaker, James & Joseph, Anne & Scheve, Kenneth, 2001. "Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation," American Political Science Review, Cambridge University Press, vol. 95(1), pages 49-69, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmad R. Alsaber & Jiazhu Pan & Adeeba Al-Hurban, 2021. "Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)," IJERPH, MDPI, vol. 18(3), pages 1-25, February.
    2. Zhong, Hua & Hu, Wuyang & Penn, Jerrod M., 2018. "Application of Multiple Imputation in Dealing with Missing Data in Agricultural Surveys: The Case of BMP Adoption," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(1), January.
    3. Scott Gehlbach & Konstantin Sonin & Ekaterina Zhuravskaya, 2010. "Businessman Candidates," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 718-736, July.
    4. Clayton L. Thyne, 2006. "Cheap Signals with Costly Consequences," Journal of Conflict Resolution, Peace Science Society (International), vol. 50(6), pages 937-961, December.
    5. Matthew Blackwell & James Honaker & Gary King, 2017. "A Unified Approach to Measurement Error and Missing Data: Overview and Applications," Sociological Methods & Research, , vol. 46(3), pages 303-341, August.
    6. Cohen, Joseph N, 2010. "Neoliberalism’s relationship with economic growth in the developing world: Was it the power of the market or the resolution of financial crisis?," MPRA Paper 24527, University Library of Munich, Germany.
    7. Sergei Guriev & Daniel Treisman, 2020. "The Popularity of Authoritarian Leaders: A cross-national investigation," SciencePo Working papers Main hal-03878626, HAL.
    8. Sebastian Barfort & Nikolaj Harmon & Frederik Hjorth & Asmus Leth Olsen, 2015. "Dishonesty and Selection into Public Service in Denmark: Who Runs the World’s Least Corrupt Public Sector?," Discussion Papers 15-12, University of Copenhagen. Department of Economics.
    9. Alessandro Bitetto & Paola Cerchiello & Charilaos Mertzanis, 2021. "A data-driven approach to measuring epidemiological susceptibility risk around the world," DEM Working Papers Series 200, University of Pavia, Department of Economics and Management.
    10. Michael Mousseau, 2012. "The Democratic Peace Unraveled: It’s the Economy," Koç University-TUSIAD Economic Research Forum Working Papers 1207, Koc University-TUSIAD Economic Research Forum.
    11. Marcel Lubbers & Peer Scheepers, 2005. "Political versus Instrumental Euro-scepticism," European Union Politics, , vol. 6(2), pages 223-242, June.
    12. Doidge, James C & Higgins, Daryl J & Delfabbro, Paul & Edwards, Ben & Vassallo, Suzanne & Toumbourou, John W & Segal, Leonie, 2017. "Economic predictors of child maltreatment in an Australian population-based birth cohort," Children and Youth Services Review, Elsevier, vol. 72(C), pages 14-25.
    13. Osterloh, Steffen & Heinemann, Friedrich, 2013. "The political economy of corporate tax harmonization — Why do European politicians (dis)like minimum tax rates?," European Journal of Political Economy, Elsevier, vol. 29(C), pages 18-37.
    14. Zhong, Hua & Hu, Wuyang, 2015. "Farmers’ Willingness to Engage in Best Management Practices: an Application of Multiple Imputation," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196962, Southern Agricultural Economics Association.
    15. Ferrari, Pier Alda & Annoni, Paola & Barbiero, Alessandro & Manzi, Giancarlo, 2011. "An imputation method for categorical variables with application to nonlinear principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2410-2420, July.
    16. Seiler, Christian & Heumann, Christian, 2013. "Microdata imputations and macrodata implications: Evidence from the Ifo Business Survey," Economic Modelling, Elsevier, vol. 35(C), pages 722-733.
    17. Bekkouche, Yasmine & Cagé, Julia & Dewitte, Edgard, 2022. "The heterogeneous price of a vote: Evidence from multiparty systems, 1993–2017," Journal of Public Economics, Elsevier, vol. 206(C).
    18. Haeussler, Carolin & Sauermann, Henry, 2013. "Credit where credit is due? The impact of project contributions and social factors on authorship and inventorship," Research Policy, Elsevier, vol. 42(3), pages 688-703.
    19. Stocké, Volker & Stark, Tobias, 2005. "Stichprobenverzerrung durch Item-Nonresponse in der international vergleichenden Politikwissenschaft," Sonderforschungsbereich 504 Publications 05-43, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    20. José Navarro Pastor, 2003. "Methods for the Analysis of Explanatory Linear Regression Models with Missing Data Not at Random," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(4), pages 363-376, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:jocore:v:61:y:2017:i:7:p:1537-1564. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: http://pss.la.psu.edu/ .

    Please note that corrections may 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.