Peter Brownell is an associate social scientist at RAND Corporation. Prior to joining RAND, he was a visiting research fellow at the Center for U.S.–Mexican Studies and a guest scholar at the Center for Comparative Immigration Studies, both at University of California, San Diego. His primary research interest has been on immigrants and immigration, with a particular focus on migration between Mexico and the United States. Past projects have addressed Mexican immigrants’ wages in the United States, the role of U.S. policy in structuring immigrants’ labor market outcomes and decisions regarding migration and settlement, the effects of the recent recession on return migration flows to Mexico, and other topics concerning Hispanic immigration to the United States. He holds a Ph.D. in sociology from the University of California, Berkeley.
Stephen E. Fienberg is Maurice Falk university professor of statistics and social science in the Department of Statistics, the Machine Learning Department, and the Heinz College at Carnegie Mellon University. His principal research interests lie in the development of statistical methodology, especially for problems involving categorical variables. His recent research has focused on approaches appropriate for disclosure limitation in multidimensional tables and their relationship with bounds for table entries; estimating the size of populations, especially in the context of census taking; and Bayesian approaches to the analysis of contingency tables. He is an elected member of the American Academy of Arts and Sciences, the National Academy of Sciences, and the Royal Society of Canada. He is a member of the Editorial Board of the Proceedings of the National Academy of Sciences. He has a Ph.D. in statistics from Harvard University.
Mark S. Handcock is a professor of statistics at the University of California, Los Angeles, where he is also an affiliate of the California Center for Population Research. He previously taught at the University of Washington, Pennsylvania State University, and New York University. His work focuses on the development of statistical models for the analysis of social network data, spatial processes, and longitudinal data arising in labor economics. His research involves methodological development motivated largely by questions from the social sciences and demography. Recent research has focused on survey sampling techniques and missing data methods, especially for network data. He also works in the fields of distributional comparisons, environmental statistics, spatial statistics, and inference for stochastic processes. He served as associate editor of Annals of Applied Statistics, Journal of the American Statistical Association, and is a fellow of the American Statistical