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Are Drone Strikes Effective in Afghanistan and Pakistan? On the Dynamics of Violence between the United States and the Taliban

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  • David A Jaeger
  • Zahra Siddique

Abstract

Strikes by unmanned aerial vehicles, or drones, have been the primary weapon used by the USA to combat the Taliban and Al-Qaeda in Afghanistan and Pakistan. This article examines the dynamics of violence involving drone strikes and the Taliban/Al-Qaeda in Afghanistan and Pakistan from 1 January 2007 to 30 September 2011. We find that drone strikes have a stronger impact on Taliban/Al-Qaeda violence in Pakistan than in Afghanistan and that these results are robust to examining different time periods and lag structures. We also examine the impact of successful and unsuccessful drone strikes (which did or did not succeed in targeted killing of a militant leader) on terrorist attacks by the Taliban. We find strong effects of unsuccessful drone strikes on Taliban violence in Pakistan, suggesting important vengeance and deterrent effects.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:cesifo:v:64:y:2018:i:4:p:667-697.
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    File URL: http://hdl.handle.net/10.1093/cesifo/ify011
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    References listed on IDEAS

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    1. David A. Jaeger & M. Daniele Paserman, 2008. "The Cycle of Violence? An Empirical Analysis of Fatalities in the Palestinian-Israeli Conflict," American Economic Review, American Economic Association, vol. 98(4), pages 1591-1604, September.
    2. David A. Jaeger & M. Daniele Paserman, 2006. "Israel, the Palestinian Factions, and the Cycle of Violence," American Economic Review, American Economic Association, vol. 96(2), pages 45-49, May.
    3. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
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    Cited by:

    1. Khusrav Gaibulloev & Todd Sandler, 2023. "Common myths of terrorism," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 271-301, April.
    2. Bevilacqua, Mattia & Morelli, David & Uzan, Paola Sultana Renée, 2021. "Striking the implied volatility of US drone companies," International Review of Financial Analysis, Elsevier, vol. 77(C).
    3. Khusrav Gaibulloev & Gerel Oyun & Javed Younas, 2019. "Terrorism and subjective financial well-being: micro-level evidence from Pakistan," Public Choice, Springer, vol. 178(3), pages 493-512, March.
    4. Bandyopadhyay, Subhayu & Sandler, Todd, 2023. "Politically influenced counterterrorism policy and welfare efficiency," European Journal of Political Economy, Elsevier, vol. 76(C).
    5. Mahmood, Rafat & Jetter, Michael, 2019. "Military Intervention via Drone Strikes," IZA Discussion Papers 12318, Institute of Labor Economics (IZA).
    6. Sophia Hatz, 2020. "Selective or collective? Palestinian perceptions of targeting in house demolition," Conflict Management and Peace Science, Peace Science Society (International), vol. 37(5), pages 515-535, September.
    7. Noury, Abdul G. & Speciale, Biagio, 2016. "Social constraints and women's education: Evidence from Afghanistan under radical religious rule," Journal of Comparative Economics, Elsevier, vol. 44(4), pages 821-841.
    8. 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.

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    More about this item

    Keywords

    time series models; conflict; drones;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions

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