change in number of observations from 611 to 869, and potentially indicates that the available data was too limiting. Despite the lessening statistical significance, the variable is still significant to the 5% level; therefore, this change is not of concern to these authors. The control variables in this study warrant discussion as well. The following variables are in line with the literature explored in section 3 and 4: GDP per capita (log), population (log), refugees (ln), minimum standards, minimal protection progress, and minimal progress in preventing human trafficking. We are surprised to find that information flows have the opposite effect of what Cho’s baseline specification suggests. She argues that increased availability of information ought to increase the awareness of human trafficking, and thereby prevent the possibility of exploitation; however, our results suggest the opposite. This may be explained by the fact that human trafficking in context of the intervention by United Nations personnel, is often sourced within the country (SOURCE). While Cho (2012) indicates that information flows are a negative pull factor they are a positive push factor, and could potentially explain the unexpected results. We are also surprised to find that cumulative intensity, democracy, domestic laws, and tourism have the opposite effect as one might expect. When viewed in context the regression results presented by Cho (2012), the effect of democracy is not entirely surprising. She finds the effect of democracy to vary depending on what dataset she uses; therefore no clear conclusion can be made as to the effect of democracy on human trafficking inflows. We then turn to domestic laws, which our results indicate has a positive relationship to human trafficking. It is surprising that anti-trafficking laws might
change in number of observations from 611 to 869, and potentially indicates that the available data was too limiting. Despite the lessening statistical significance, the variable is still significant to the 5% level; therefore, this change is not of concern to these authors. The control variables in this study warrant discussion as well. The following variables are in line with the literature explored in section 3 and 4: GDP per capita (log), population (log), refugees (ln), minimum standards, minimal protection progress, and minimal progress in preventing human trafficking. We are surprised to find that information flows have the opposite effect of what Cho’s baseline specification suggests. She argues that increased availability of information ought to increase the awareness of human trafficking, and thereby prevent the possibility of exploitation; however, our results suggest the opposite. This may be explained by the fact that human trafficking in context of the intervention by United Nations personnel, is often sourced within the country (SOURCE). While Cho (2012) indicates that information flows are a negative pull factor they are a positive push factor, and could potentially explain the unexpected results. We are also surprised to find that cumulative intensity, democracy, domestic laws, and tourism have the opposite effect as one might expect. When viewed in context the regression results presented by Cho (2012), the effect of democracy is not entirely surprising. She finds the effect of democracy to vary depending on what dataset she uses; therefore no clear conclusion can be made as to the effect of democracy on human trafficking inflows. We then turn to domestic laws, which our results indicate has a positive relationship to human trafficking. It is surprising that anti-trafficking laws might