1. Human Trafficking Legislation Across the States: The Determinants of Legislative Comprehensiveness Vanessa Bouche & Dana Wittmer The Ohio State University Department of Political Science

2. Motivation for Research Why have some states adopted human trafficking legislation and others have not? Why have some states adopted more comprehensive human trafficking legislation than others? State investment Civil Penalties Criminalization

3. Hypothesis 1: Descriptive Representation The greater the percentage of women in the House and Senate, the more likely a state is to have comprehensive human trafficking legislation. Rationale: Human trafficking has been framed as a women’s issue Legislator interviews suggested female legislators were more committed to the issue than their male counterparts

4. Hypothesis 2: Party Neutrality Party Neutrality Hypothesis: a) The greater percentage of Democrats in the House and Senate, the more likely a state is to have state investment; b) The greater percentage of Democrats in the House and Senate, the less likely a state is to have criminalization; c) The percentage of Democrats in the House and Senate will have no impact of overall legislative comprehensiveness. Rationale Democratic support for social programs, Republicans tougher on crime; these combined lead to more comprehensive legislation Legislator interviews suggested this was a “bipartisan” issue where people that would otherwise be on different sides came together to create a “broad-based coalition”

5. Hypothesis 3: Policy Diffusion The higher the proportion of neighboring states that passed human trafficking criminalization legislation, the more likely a state is to have comprehensive human trafficking legislation. Rationale: Spatial and temporal impact of policies spreading Legislator interviews shed light on the importance of networking across state lines, and “other states were adopting at great speed so it became necessary not to fall behind.”

6. Empirical Method: Dependent Variables State investment (Table 1) Victim Assistance Task Force Training Reports State Investment Dummy Civil Penalties (Table 2) Restitution Asset Forfeiture Civil Action Affirmative Defense Civil Penalties Dummy Criminalization (Table 3) Maximum years sex trafficking minor Maximum years sex trafficking adult Criminalization Dummy Comprehensiveness (0=nothing; 3=everything)

7. Empirical Method: Independent Variables Variables of interest Gender composition of House & Senate Party composition of House & Senate Policy Diffusion (% neighboring states adopting legislation) Control variables Surplus, illegal immigrants per capita, violent crime per capita, population, professional/part- time legislature

9. Results: Table 1 Descriptive Representation: More females in the House and Senate leads to more state investment for human trafficking Women set at max in House yields predicted probability of 17% for adopting victim assistance legislation (compared with 2% at mean) Women set at max in House & Senate yields predicted probability of 74% for creation of task force, versus 2% at mean Women set at max in the House & Senate yields a predicted probability of 81% to commission a report versus only 6% when at mean Party Neutrality Signs reversed in House & Senate Not significant in Model 5 Policy Diffusion: highly significant across all models

11. Results: Table 2 Descriptive Representation Directionality and significance mixed across all models Party Neutrality Negative in Senate, positive in House with mixed statistical significance Opposite coefficients may be evidence of party neutrality Policy Diffusion: highly significant across all models Illegal immigrants Negative in State Investment models, positive in Civil Penalties models States don’t want their money going to illegal immigrants, but are willing to give access to courts to recover damages from trafficker so less dependent on state resources

13. Results: Table 3 Criminalization Descriptive Representation Nothing significant in Models 1 & 2, but directionality consistently positive Party Neutrality Directionality and significance not consistent Proof of neutrality? Policy Diffusion: highly significant across all models

14. Results: Table 3 Legislative Comprehensiveness Descriptive Representation States with more women in the House & Senate are significantly more likely to adopt more comprehensive human trafficking legislation Party Neutrality Opposite and significant coefficients in the House and Senate indicates the bipartisan nature of the issue and the need for bargaining and compromise to pass the most comprehensive legislation Policy Diffusion More comprehensive legislation is passed over time and as more states adopt some legislation

15. Where do we go from here? Other variables Female & partisan breakdown of authorship and sponsorship of legislation Number of federal prosecutions and convictions for human trafficking in the state Other questions Is the legislation effective? Why has this issue been framed as a gendered issue and what are the implications?