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Measuring anti-trafficking policies: How do they spread across countries?

According to the US Department of State, there are more than 12 million victims of human trafficking worldwide. This column presents a new index to measure the spread of anti-trafficking policies. It suggests they mainly diffuse across contiguous countries and main trading partners, due to externality effects, and also via political and cultural similarities, due to learning and emulation.

In the last few decades, human trafficking has become a growing phenomenon worldwide. The illicit trade in human beings across borders violates the human rights of victims, threatens national security, and deteriorates the health of the affected economies and societies by increasing the size of the shadow economy and organised criminal activities (Belser 2005). Although the exact magnitudes and dimensions of the problem are unknown, available statistics suggest that human trafficking is one of the most serious transnational crimes in the 21st century. According to the US Department of State, there are more than 12 million victims of human trafficking worldwide. Interpol estimates that human trafficking is a multi-billion-dollar business, amounting to the third largest transnational crime following drug and arms trafficking.

Human trafficking can be seen as one of the dark sides of globalisation. As advancements in technology and transportation connect countries more closely regardless of geographical distances, illicit flows of human beings have also become a global phenomenon. Anecdotal evidence suggests that traffickers recruit victims worldwide and transfer them from one country to another, often across continents.

Tracking trafficking

Given the growing significance of international human trafficking, it is no surprise that the international community has adopted several measures, including the UN Convention against Transnational Organised Crime and its Protocol to Prevent, Suppress and Punish Trafficking in Persons, especially Women and Children.

Accordingly, social scientists have started to turn their attention towards policies enacted to combat human trafficking. But one of the problems scholars face is the lack of reliable data on countries’ anti-trafficking policies which can be compared over time and between countries. Existing measures fail to recognise the different levels of compliance in the three main policy dimensions: prosecution, protection, and prevention.

Separating the three dimensions is important. Theory and evidence indicate that better protection policy may encourage potential victims to risk illegal migration, which could lead them to fall prey to traffickers. Human trafficking inflows might therefore increase as a consequence, contradicting the objectives of prosecution and prevention policies (Akee et al. 2010). In recent research (Cho et al. 2011), we develop novel indices of anti-trafficking policies around the world, for up to 177 countries over the 2000-2009 period.

In addition to our overall “3P” anti-trafficking policy index, we measure government policies with respect to the three main dimensions of anti-trafficking policies: prosecution, prevention, and protection.

  • The sub-index on “prosecution policy” measures the level of judicial efforts and law enforcement to punish and prosecute traffickers and other related offenders.
  • The second sub-index, “protection policy” assesses the level of government efforts to protect and assist the victims of human trafficking.
  • The third dimension of anti-trafficking policies, “prevention policy”, evaluates the level of government efforts to prevent human trafficking (such as border control, information sharing, and international cooperation).

Figure1. Compliance with anti-trafficking policies (global sample): 2000-2009

Figure 1 shows that the level of compliance in all of the three dimensions improved for the last 10 years. In particular, compliance with prosecution policy was on average highest for all years and experienced the most significant improvement during the period. The worldwide average score of 2.90 in 2000 increased to 4.26 in 2009. This suggests that most countries in the sample have adopted and implemented anti-trafficking law, distinguishing the crime clearly from violation of immigration law or labour exploitation in their legal system. The average prevention policy score, meanwhile, increased from 2.53 in 2000 to 3.67 in 2009, reflecting improvements in border control and collaborative actions fighting human trafficking across countries.

Yet our index suggests that governmental efforts to protect victims of human trafficking remain far weaker than their efforts to criminalise traffickers and prevent the crime taking place. The worldwide average score of protection policy is lowest for all years, e.g., 2.26 in 2000 and 2.97 in 2009, and has shown the slowest improvement over time.

Moreover, this is not restricted to developing countries. For instance, the UK imprisoned trafficking victims for violating immigration law, an action against the mandate of the protocol, and therefore received a score of only 2 (reflecting inadequate compliance) in the past two years. At the same time, however, the UK demonstrated full compliance with prevention and prosecution. This descriptive outcome of our index indicates that, in terms of compliance with anti-trafficking policy, countries take the “justice and prevention” aspect of the crime more seriously than the human rights aspect.

Figure 2. Compliance with anti-trafficking policies across regions and time

 

Figure 2 shows the development of the 3P index across regions over time. As can be seen, with the exception of the Middle East/North Africa and South Asia, there are clear improvements in compliance with anti-trafficking policies over time. It is in these regions, together with sub-Saharan Africa, where the overall level of the anti-trafficking policy index is lowest in 2009. It is also remarkable that the 3P index showed high values in the Western Europe and other industrialised countries group, while the remaining groups converged to this higher level over the 2000-2009 period.

The spread of anti-trafficking policies

There are many reasons why one would expect spatial dependence in anti-trafficking policies.

1.      Pressure. The major destination countries of internationally trafficked persons are likely to exert pressure onto countries which function as major sources of transit and/or origin for people trafficked into these major destinations. Major destination countries will be averse to illegal migration into their territories (as international trafficking always is) and will resent the increase in other transnational criminal activities (such as drug and arms trafficking) that typically accompany human trafficking (Bartilow 2010).

Moreover, human trafficking creates a shadow economy of illegal labour markets and businesses with estimated annual profits of some $1 billion in industrialised countries (Belser 2005) – money which is not taxed and is likely to be used for illegal activities.

Yet, the effectiveness of policies undertaken in destination countries will be undermined if other countries, particularly relevant transit and origin countries, do not follow suit. The strictest anti-trafficking policies in destination countries may be ineffective if countries of origin and transit have lax policies in place. Hence, successful anti-trafficking policies in destination countries depend on a ratcheting up of policies in origin and transit countries, as well as major destination countries exerting pressure on laggards.

2.      Externalities. Externalities are rampant in this policy area (Simmons and Llyod 2010). Anti-trafficking policies enacted by one country create significant externalities that other countries cannot simply ignore. Stricter policies in one destination country will deflect some of the flows of trafficked persons into other destination countries, while stricter policies in one origin or transit country will prompt transnational trafficking networks to increasingly resort to other origin or transit countries.

Just as with international drug-trafficking, unless policies can address the underlying supply and demand factors driving international trafficking (which they typically cannot), stricter anti-trafficking policies in one country will merely deflect the problem onto other countries with weaker policies in place, such that there is an incentive to ratchet policies upwards over time. In other words, by predicting externality effects of such transnational crime, countries will be able to update their anti-trafficking measures, following relevant policy changes of other countries that share certain characteristics, such as geographic proximity and economic similarity.

3.      Uncertainty. Lastly, anti-trafficking policies are being set in a relatively new arena of public policies, with some countries, such as the US and a few countries in Western Europe, running ahead of others. Laggards will be uncertain as to which policies to choose on their own, and will therefore look for cues (or information) in the policies of other countries.

Importantly, countries will not simply wish to follow the top leaders in North America and Western Europe. These are all major destination countries and following their lead may not produce positive outcomes in other countries – mostly origin and transit countries of trafficking victims – because the root causes of the problem and the groups targeted differ from those of the leading countries as does their cultural and political setting.

In dealing with uncertainty regarding policy design and its outcomes, the more competently governed lagging countries will want to actively learn from leaders in their reference groups – i.e., from culturally, politically, or geographically proximate countries who are also early adopters of relevant policies (Elkins and Simmons 2005), while other laggards may simply wish to emulate or mimic policies from other reference countries without any major learning effect.

Empirical evidence of spatial dependence

Using our sample of anti-trafficking policies in 177 countries between 2000 and 2009, we have tested our hypotheses of spatial dependence in policies. Our results show no evidence for anti-trafficking policies diffusing via pressure exerted by destination countries onto their major transit or origin countries. Indeed, our results suggest that anti-trafficking policies are an area where destination countries seem unwilling –or unable – to pressure the countries where the majority of victims of human trafficking come from or are channelled through.

But our results do present consistent evidence for externality effects (with the exception of protection policies for which we would not expect such an effect since better victim protection policies do not deflect flows onto others – in fact the opposite may even be the case). We thus find that stricter prosecution and prevention policies in contiguous countries, or sometimes in major trading partners, are followed by stricter domestic policies as well.

The most likely explanation is simple. Stricter policies create negative externalities on neighbouring countries and trading partners, exacerbating their problems in dealing with human trafficking as a result. Contiguity and trade might also partially capture learning or emulation channels of diffusion. In fact, we find robust evidence that countries look towards those with similar political views, as proxied by our connectivity variable of voting similarity on key issues in the UN General Assembly. This is also the case for countries sharing similar cultural values, as proxied by our connectivity variable measuring “civilisational belonging”.

Conclusion

We find robust evidence that countries do not operate in isolation when deciding on anti-trafficking policies, being affected by the prior choices of other countries on which their policy choices spatially depend.

We hope that our index on anti-trafficking policies can be used to further shed light on the determinants and consequences of trafficking policies. Scholars may wish to use the aggregate index if they are interested in overall policies, but we strongly recommend that future research analyses the different dimensions of overall policies separately and in greater detail than we are able to do here. For example, protection policies mainly protect victims, while prosecution policies mainly target the perpetrators. Why countries choose to pursue one type of policy rather than the other deserves closer scrutiny.

The authors cordially acknowledge the generous funding provided for this project by the European Commission (Directorate-General Justice, Freedom and Security, Prevention of and Fight against Crime Action Grant).

References

Akee, Randall, Arjun Bedi, Arnab K Basu, and Nancy H Chau (2010), “Transnational Trafficking, Law Enforcement and Victim Protection: A Middleman’s Perspective”, mimeo, Department of Economics, Cornell University.

Bartilow, Horace (2010), “Gender Representation and International Compliance Against Human Trafficking”, mimeo.

Belser, Patrick (2005), “Forced Labour and Human Trafficking: Estimating the Profits”, Working Paper (Declaration/WP/42/2005), International Labour Office. Geneva.

Cho, Seo-Young, Axel Dreher, and Eric Neumayer (2011), “The Spread of Anti-trafficking Policies – Evidence from a New Index”, Cege Discussion Paper 119, Georg-August-University of Goettingen, Germany.

Elkins, Zachary and Beth Simmons (2005), “On Waves, Clusters, and Diffusion: A Conceptual Framework”, The Annals of American Academy. AAPSS 598: 33-51.

Simmons, Beth and Paulette Lloyd (2010), “Subjective Frames and Rational Choice: Transnational Crime and the Case of Human Trafficking”, mimeo. Government Department, Harvard University.

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