Migrants and brokers
The relationships between low-skilled labor migrants and local employment brokers help shape migrants' experiences and outcomes. Exactly how, though, remains poorly understood. As a result, researchers, policy-makers, and activists have yet to settle on how best to protect migrants (and brokers) from exploitative situations. For example, providing information directly to migrants and brokers may help them guard against unscrupulous practices in the migration industry -- but also potentially lead to unintended negative consequences.
With our project, we aimed to understand the intended and unintended consequences of providing information to migrants and brokers in the labor recruitment context. Specifically, we asked: What is the nature of the migrant and broker relationship? What kinds of information about both this relationship and migration opportunities help migrants achieve better migration outcomes? How do brokers respond to better-informed migrants?
To answer these questions, we used Ethica Data's research platform to implement a digitally networked field experiment in a high out-migration city in Pakistan. Through Ethica Data's participant app, we first mapped the relationships between migrants and brokers. Then, migrants participating in our study received information about brokers in their neighborhood and current employment opportunities. Brokers, in turn, received information about migrants becoming better informed. Finally, we administered short questionnaires using the Ethica Data's participant app to measure how this information influences participants' experience with the labor recruitment process as it unfolds.
Sample size: ~500 subjects
- WIFI signals in the surrounding environment
- The phone calls statistics
- Text messages statistics
- Location information
Daniel Karell, Ph.D. Assistant Professor Division of Social Science New York University Abu Dhabi
Rabia Malik, Ph.D. Assistant Professor Mushtaq Gurmani School of Humanities and Social Sciences Lahore University of Management Sciences (LUMS)