Doctoral Dissertation Research From Migrant Social Capital to Community Development: A Relational Account of Migration, Remittance, and Inequality

Princeton University, Princeton NJ

Investigators

Abstract

Paul J. DiMaggio, Sara R. Curran, Filiz Garip Doctoral Dissertation Improvement Grant Doctoral Dissertation Research: From Migrant Social Capital to Community Development: A Relational Account of Migration, Remittances and Inequality This project explores how migrant networks influence migration, remittance and development patterns. While abundant empirical evidence in the migration literature demonstrates how the accumulation of information within migrant networks facilitates the migration process, the consequences of these dynamics for remittance patterns and development outcomes in origin communities remain indeterminate. The objective of this study is to address this gap in the literature and understand the causal mechanisms that link two disparate strands of migration research, namely, migrant networks and community development, by demonstrating how: (1) the structure of migrant networks and the distribution of migrant social capital affect migration and remittance patterns, (2) migration and remittance patterns influence the level and distribution of resources in origin communities, and, (3) cumulative migration and remittance patterns over time generate development outcomes for origin communities. To meet this objective, the investigator proposes a multi-method approach involving quantitative analyses of unique data from Thailand and computational models of the migration process. First, migration and remittance patterns will be linked to migrant networks by analyzing multi-level, longitudinal, geo-referenced data from the Nang Rong surveys collected by University of North Carolina and Mahidol University. This study site offers a unique source of information from nearly 50,000 individuals in 51 origin villages and more than 12,000 migrants in 4 major destinations, and is also situated in a larger context of dramatic economic and social growth in Thailand, where migration out of rural areas to urban destinations forms an increasingly vital component of rural livelihoods. Second, agent-based computational models will be developed to understand the mechanisms connecting migrant networks to remittance and development outcomes. In these models, macro-level migration, remittance and development patterns will be conceptualized as emerging from individual interactions in migrant networks. By varying the structural and relational characteristics of these networks, the investigator will observe the resulting differences in migration, remittance and development patterns, and hence identify the micro-mechanisms within networks that generate differentials in macro-level outcomes. The proposed multi-method analysis will help address several key theoretical, empirical and methodological issues. The study will contribute to development theory by conceptualizing development not only in relation to migration patterns or migrant remittances but also to migrant networks. This approach will help disentangle the mechanisms that generate inequalities in the distribution of resources among households, and in the development levels among villages. Methodologically, this study will be the first to use agent-based models and simulations to study migration, remittance and development patterns. Empirically, it will provide an extensive analysis of the Thai case. Overall, this project will generate policy insights for many regions of the world, where rural to urban migration forms the greatest demographic challenge. Results from this project will be disseminated broadly to several audiences, including academics and policy makers in order to enhance scientific understanding and to inform policy decisions.