Modeling for Determinants of Human Trafficking: An Empirical Analysis

Abstract

This study aims to identify robust push and pull factors of human trafficking. I test for the robustness of 70 push and 63 pull factors suggested in the literature. In doing so, I employ an extreme bound analysis, running more than two million regressions with all possible combinations of variables for up to 153 countries during the period of 1995-2010. My results show that crime prevalence robustly explains human trafficking both in destination and origin countries. Income level also has a robust impact, suggesting that the cause of human trafficking shares that of economic migration. Law enforcement matters more in origin countries than destination countries. Interestingly, a very low level of gender equality may have constraining effects on human trafficking outflow, possibly because gender discrimination limits female mobility that is necessary for the occurrence of human trafficking.

Income Distribution and Human Trafficking Outflows

“…If the relationship with the smuggler ends once the person reaches their destination this is considered human smuggling; however, if the smuggler entraps the person in the destination country and forces them into labor, prostitution, or other atrocities, this is considered human trafficking (Bales et al, 2009). Cho (2015) states human trafficking research is still in its infancy; however, the body of literature exploring the root causes and drivers of human trafficking is growing. The literature has broadly categorized these factors as supply side, or "push" factors, demand side or "pull" factors and as facilitating factors.…”

“…The literature has broadly categorized these factors as supply side, or "push" factors, demand side or "pull" factors and as facilitating factors. In regards to the push or supply factors, past research has found countries that suffer from poverty, crime, corruption, unstable institutions, and/or are plagued with conflict and upheaval tend to be the greatest source of human trafficking victims (Agbu, 2003;Bales, 2007;Cho, 2015;Rao & Presenti, 2012;Surtees, 2008). These countries are often referred to as "origin" countries as individuals seek to migrate out of these areas in search of a better life and in the process fall victim to human traffickers.…”

“…In reference to pull or demand factors, wealth is primary determinant as wealthier countries tend to have a greater demand for low-skilled work and the means to pay the traffickers. Wealthier countries tend to be considered the "destination" countries for most of the human trafficking victims (Cho, 2015). Finally, the presence of corruption and organized crime are facilitating factors as organized criminals tend to have established networks that often utilize corrupt officials.…”

“…The theoretical argument is that when stark differences in income exist, the difference can not only make the poorest resentful of their circumstances, but also raise their expectations regarding better opportunities elsewhere (Cho, 2015;Jac-Kucharski, 2012;Mo, 2014). In other words, awareness that others have a considerably greater standard of living can be a motivating factor to migrate in search of a better life.…”

“…Specifically, using the UNODC (2006) measures of the outflow of human trafficking victims at the country level, Cho (2015) finds that economic inequality, as measured by the Gini index, does not have a significant impact on the outflow of human trafficking. Cho"s (2015) results suggest that countries with greater income inequality, as measured by the Gini coefficient, are no more likely to be the source or originating country from which individuals seek to leave than countries with greater income equality. It is important to note that empirical studies often use the Gini coefficient developed by Corrado Gini in 1912, which measures the income distribution across countries as a measure of income inequality.…”