Understanding Human Trafficking Using Victim-Level Data

Working Paper: CEPR ID: DP13279

Authors: Martina Bjrkman Nyqvist; Maria Kuecken; Eliana La Ferrara; Elsa Artadi

Abstract: Quantitative research on human trafficking is scant due to lack of data. This study makes use of a unique survey we collected on former victims of trafficking and vulnerable women and girls in the Philippines. We start by exploring the correlates of trafficking and show that household composition (in particular the presence of older sisters) and plausibly exogenous measures of health and economic shocks predict thelikelihood of being tracked. We then study the eff ects of trafficking on victims' intertemporal and risk preferences using entropy balancing. We fi nd that trafficking victims are not di fferentially patient, but they are more risk-loving. Our novel data and fi ndings are pertinent to the design of policies intending to prevent trafficking and reintegrate victims.

Keywords: human trafficking; prostitution; philippines; child labor

JEL Codes: D13; D80; J47


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
household composition (older sisters) (J12)likelihood of being trafficked (J82)
economic shocks (F69)likelihood of being trafficked (J82)
trafficking (K42)risk aversion (D81)

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