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Computational and Robustness Reproducibility of "UN Peacekeeping and Democratization in Conflict-Affected Countries"

Author

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  • Oswald, Christian
  • Walterskirchen, Julian

Abstract

Blair et al. (2023) examine the effect of UN peacekeeping on democratization in conflict-affected countries. They use fixed effects and instrumental variable estimators and find evidence that "UN missions with democracy promotion mandates are strongly positively correlated with the quality of democracy in host countries but that the magnitude of the relationship is larger for civilian than for uniformed personnel, stronger when peacekeepers engage rather than bypass host governments when implementing reforms, driven in particular by UN election administration and oversight, and more robust during periods of peace than during periods of civil war". Since the authors provide an impressive list of robustness checks, we focus on computational and robustness reproducibility. We replicate the findings using the Stata code provided in the replication material and reproduce all main analyses in R. We add year fixed effects to country fixed effects, cluster standard errors, use fixed and random panel regression estimators and ordered Beta regression estimators. We furthermore reproduce instrumental variable estimators with two different packages. We find that the original findings were reproducible and robust.

Suggested Citation

  • Oswald, Christian & Walterskirchen, Julian, 2024. "Computational and Robustness Reproducibility of "UN Peacekeeping and Democratization in Conflict-Affected Countries"," I4R Discussion Paper Series 138, The Institute for Replication (I4R).
  • Handle: RePEc:zbw:i4rdps:138
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    File URL: https://www.econstor.eu/bitstream/10419/301427/1/I4R-DP138.pdf
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    References listed on IDEAS

    as
    1. Brodeur, Abel & Mikola, Derek & Cook, Nikolai & Brailey, Thomas & Briggs, Ryan & de Gendre, Alexandra & Dupraz, Yannick & Fiala, Lenka & Gabani, Jacopo & Gauriot, Romain & Haddad, Joanne & McWay, Ryan, 2024. "Mass Reproducibility and Replicability: A New Hope," I4R Discussion Paper Series 107, The Institute for Replication (I4R).
    2. Leifeld, Philip, 2013. "texreg: Conversion of Statistical Model Output in R to LATEX and HTML Tables," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 55(i08).
    3. Flavio Monti & Francesco Ferretti & Niccolò Fattorini, 2024. "Intrinsic and extrinsic factors modulating vigilance and foraging in two gregarious foragers," Behavioral Ecology, International Society for Behavioral Ecology, vol. 35(1), pages 1367-1379.
    4. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    5. Oswald, Christian & Walterskirchen, Julian & Häffner, Sonja & Binetti, Marco & Dworschak, Christoph, 2023. "Replication of The Morning After: Report from the Nottingham Replication Games," I4R Discussion Paper Series 45, The Institute for Replication (I4R).
    6. Blair, Robert A. & Di Salvatore, Jessica & Smidt, Hannah M., 2023. "UN Peacekeeping and Democratization in Conflict-Affected Countries," American Political Science Review, Cambridge University Press, vol. 117(4), pages 1308-1326, November.
    7. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    8. Abadie, Alberto & Gu, Jiaying & Shen, Shu, 2024. "Instrumental variable estimation with first-stage heterogeneity," Journal of Econometrics, Elsevier, vol. 240(2).
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