Multiple Systems Estimation and Human Trafficking

Abstract

Multiple Sytems Estimation (MSE) is a statistical method which uses overlap between samples to make inference about the size of the larger population. In 2019, the National Academies convened a panel to assess statistical methods for quantifying the prevalence of human trafficking. The problem is complicated by many factors. Besides the unrealistic assumptions behind the standard capture-recapture model, which are inherited by vanilla MSE, human trafficking has special features. The main message is that there has been a lot of good statistical work on MSE, making the tool far more robust to the biases and complexities of practical applications.

Additional information

Notes on contributors

David Banks

David Banks earned his master’s in applied mathematics from Virginia Tech, followed by a PhD in statistics. He won an NSF postdoctoral research fellowship in the mathematical sciences at the University of California, Berkeley. In 1986, he was a visiting assistant lecturer at the University of Cambridge, and then joined the Department of Statistics at Carnegie Mellon in 1987. He went to the National Institute of Standards and Technology 10 years later, then served as chief statistician of the U.S. Department of Transportation, and joined the U.S. Food and Drug Administration in 2002. In 2003, he returned to academia at Duke University.

Emmanuel Mokel

Emmanuel Mokel is a senior at Duke University, studying mathematics and statistical science, with interests in applications to biotech, genetics, and more.