Pamela Giustinelli

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Pamela Giustinelli, is an Adjunct Research Assistant Professor in the Survey Research Center, Institute for Social Research, at the University of Michigan, Ann Arbor.

Pamela is interested in modeling, empirical, and counterfactual policy analysis of individual and multilateral decision making under uncertainty-ambiguity, especially as it applies to the family and human capital contexts. She is also interested in survey methodology, particularly as it relates to this line of research. Here are some important questions in her research agenda:

  • How do preferences, beliefs, choice sets, and other elements of a choice situation determine what choices people make and also how they make those choices? (That is, the “decision rules,” “decision protocols,” or “modes of interactions” they use.) And how are those elements formed?
  • What information do individuals and groups have or use when making decisions under uncertainty? And what information is or is not shared among decision makers in multilateral settings?
  • What are the implications of the above points for policy?
  • To inform modeling, identification, and prediction of choice behaviors, what components of individuals’ and groups’ decision processes can we sensibly measure in surveys? From whom? And in what formats?

Data science methodology: Survey design for elicitation of components of human decision processes and interactions under uncertainty/ambiguity

Data science applications: Human capital (school choice, labor supply, end-of-life living arrangements)

Pamela Davis-Kean

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Pamela Davis-Kean, PhD, is Professor of Psychology, College of Literature, Science, and the Arts, and Research Professor, Survey Research Center and Research Center for Group Dynamics, Institute for Social Research, at the University of Michigan, Ann Arbor.

Prof. Davis-Kean is the Director of the Population, Neurodevelopment, and Genetics program at the Institute for Social Research. This group examines the complex transactions of brain, biology, and behavior as children and families develop across time. She is interested in both micro (brain and biology) and macro (family and socioeconomic conditions) aspects of development to understand the full developmental story of individuals.  Her primary focus in this area is how stress relates to family socioeconomic status and how that translates to parenting beliefs and behaviors that influence the development of children.

Ji Zhu

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My research interests are in the areas of machine learning, statistical network analysis, analysis of high-dimensional data, and their applications in health sciences, biology, finance and marketing.