The impact of human rights INGO activities on economic sanctions

Abstract

What impact do human rights international non-governmental organizations (hereafter HROs) have on the initiation of economic sanctions? The extant literatures on sanctions and transnational non-state groups have largely overlooked the role, if any, the activities of these transnational non-state actors have on the use of economic coercion as a popular policy tool. In this study, we argue that HROs could affect sanction decisions through two distinct mechanisms: information production (“shaming and blaming”) and local empowerment (local presence). By bringing poor human rights performers into the international spotlight, we argue that this effect should hold even after accounting for human rights practices in the targeted countries. Using dyadic data on HROs and economic sanctions, we find robust support for our basic argument that HRO activities increase the likelihood of sanction events against repressive regimes. Additionally, much of the empirical support highlights the role of information production, as opposed to local empowerment, in leading to sanction onset. Overall, our findings indicate that HROs are powerful actors in influencing foreign policy decisions between states.

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Fig. 1

Notes

  1. 1.

    We define a non-governmental organization (NGO) as an open-membership, non-profit organization that is not controlled by a government. The focus here is on international NGOs, defined as organizations involved in multiple countries simultaneously, that have a mission statement that reflects human rights outlined in the Universal Declaration of Human Rights (UIA 2008/2009).

  2. 2.

    For a discussion of the negative human rights effects of sanctions, see Malloy (1995), Wood (2008) or Peksen (2009). For a discussion on the negative effects sanctions have on the right to health, see Eisenberg (1997) or Peksen (2011). We note that the theoretical argument in this paper does not hinge on any effect, positive or negative, of sanctions on human rights. Instead, our argument focuses on how the activities of HROs in the promotion of human rights can lead to sanction onset. If the effect of sanctions can be detrimental for human rights, however, our argument and findings may imply a negative externality of the work of HROs that needs more attention from the practitioner community.

  3. 3.

    Smith et al. (1998)’s survey of HROs found variation in HROs support of sanctions to “enforce human rights standards.” On a five-point scale, the average score on whether an organization supported the use of sanctions was a 2.32 (390). Smith et al. (1998) conclude that “very few NGOs supported the use of economic sanctions to advance human rights goals” (395). A good example of the call for stopping sanctions in the name of human rights is the efforts of many HROs to end sanctions in Iraq in the early 2000s. See, for example HRW (2000) or Rowat and Martin (2003). In 2000, the NGO Campaign Against Sanctions, for example, called sanctions “one of the primary causes of the humanitarian disaster suffered by Iraq over the past 13 years” (Rowat and Martin 2003). The INGO International Committee of the Red Cross called on organizations to “mitigate some of the worst effects of sanctions” in 1999 (ICRC 1999).

  4. 4.

    “Naming and shaming” or “shaming and blaming” is typically defined as information gathered and dispersed by HROs about human rights practices within a country (Ron et al. 2005). This information used to draw attention to human rights abuses and increase pressure on targeted states to change their human rights practices (Keck and Sikkink 1998; Murdie and Davis 2012).

  5. 5.

    We acknowledge that this appeasement may have a marginal impact on approval ratings and may not be to the degree to which a leader would impose sanctions in order to avoid losing an election (Drury 2000, 2001; Whang 2011). Drury (2001), for example, explains how sanction decisions may be marginally impacted by approval ratings, with more secure leaders more willing to levy sanctions. More directly, however, Whang (2011) finds that US presidents do receive a domestic benefit after imposing sanctions. If demand by the local population was great enough, a third-party leader might enact sanctions to appear to be doing something against a repressive regime.

  6. 6.

    In fact, most of the documenting of human rights abuses in Burma has been done by HROs (Forsythe 2009).

  7. 7.

    We also repeated the analysis using a monadic data set controlling only for potential target country-specific variables. The dependent variable in the monadic data is the onset of economic sanctions against a target country by any sender country. The results from the monadic data analysis are not substantially different (please see the online appendix at this journal’s webpage).

  8. 8.

    When we further restrict the sample by including only the human rights relevant dyads in which the total trade volume between the dyad countries is greater than zero, our main findings remain unaltered. We also estimated the models using the data for all dyads (i.e., global sample). In the global sample analysis, the results are very similar. For the results, please refer to the online appendix.

  9. 9.

    We also ran separate models for the threat and imposition stages of sanction cases. We find that HRO shaming events are likely to increase the likelihood of both the threat and imposition of sanctions.

  10. 10.

    Main results are consistent to specifications where we extend our dependent variable to include sanctions of any type, even those not taken for human rights reasons.

  11. 11.

    Results are also consistent if the natural log of this measure is used instead of the raw count. We use the raw count here to be consistent with Murdie and Davis (2012).

  12. 12.

    This number of HROs is over double the size of the HROs included in the Murdie and Davis (2012) original dataset, representing a much more encompassing definition of “human rights” than the previous version of the events dataset.

  13. 13.

    Like Murdie and Bhasin (2011), we also try a measure of HRO permanent locations within the targeted state. Results remain consistent.

  14. 14.

    Following the earlier practice (e.g., Poe and Tate 1994; Davenport and Armstrong 2004), for the countries where the State Department data were missing but available in Amnesty International, the missing values were replaced in the State Department indicator by using the index for Amnesty International data. Also, to check the sensitivity of the findings to data specifications, we estimated the models with the Physical Integrity Index (Cingranelli and Richards 2007), another widely used quantitative measure of human rights abuses. The results were similar when we use the alternative measure.

  15. 15.

    Given recent research by Berry et al. (2010, 2011), we run models both with and without the product term to capture any interactive effect. Importantly, following Norton et al. (2004) and Berry et al. (2011), our conclusions as to the non-significant (at the 95% confidence rate) interactive effects occurs both in models with and without the product term, making the question of whether to include a product term a “moot issue, lending greater credibility to the results” (19).

  16. 16.

    Our results are consistent if we follow the approach of Carter and Signorino (2010) and model time, time squared, and time cubed. We also ran additional models controlling for potential target and sender country dummies. The inclusion of these dummy variables had no significant effect on the main findings reported below.

  17. 17.

    We will note that in Table 1, Model 5, the interaction term is statistically significant at the marginal p < .1 level when the interaction term is included. Following Berry et al. (2011), however, this result does not hold at the p < 0.05 level in a supplementary analysis without the product term. Further, following Norton et al. (2004), we find that the interaction is not statistically significant for the vast majority of observations at all baseline probability levels, leading us to conclude that any interactive effect is marginal at best.

  18. 18.

    We use Clarify to generate the post-estimation interpretation of the results (King et al. 2000; Tomz et al. 2001).

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Correspondence to Dursun Peksen.

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Murdie, A., Peksen, D. The impact of human rights INGO activities on economic sanctions. Rev Int Organ 8, 33–53 (2013). https://doi.org/10.1007/s11558-012-9146-9

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Keywords

  • Human rights INGOs
  • Economic sanctions
  • Human rights
  • Political repression
  • Naming and shaming activities
  • International sanctions