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CSDE Welcomes Four New UW & External Affiliates!

CSDE’s Executive Committee is pleased to introduce four of our new UW Faculty & External Affiliates:

  • Afra MashhadiAssistant Professor, Computing & Software Systems, UW Bothell. Dr. Mashhadi is a research scientist in the domain of Ubiquitous Computing. She is interested in developing mathematical and computational models that leverage the proliferation of sensors and breakthroughs in machine learning to (1) understand societies and social phenomena at different spatial scales and (2) model social dynamics of human behavior.
  • Leo MoralesProfessor, Division of General Internal Medicine; Adjunct Professor, Health Services, UW Seattle. Dr. Morales’s research has focused on measurement of patient reported outcomes in diverse populations, and minority health and health disparities including immigrant and Latino Health. He serves as Chief Diversity Officer for the School of Medicine.
  • Rebecca RebbeAssistant Professor, School of Social Work, University of Southern California. Dr. Rebbe’s research examines the measurement of and community responses to child maltreatment. She has training using demographic methods and specializes in using population-based linked administrative datasets to better understand child maltreatment.
  • Eric Waithaka–Assistant Professor, Department of Social Work, George Mason University. Dr. Waithanka’s research focuses on intergenerational social and economic mobility during young adults’ transitions to adulthood, with a particular focus on the role of family capital (resources & processes) and public policies influence on young adults’ life outcomes.

CSDE Affiliates Knox and Jones-Smith Awarded Grant from the Royalty Research Fund!

CSDE Affiliates Mellisa Knox and Jessica Jones-Smith have recently been awarded a research grant from the UW RRF as co-PIs. Taxes on sweetened beverages have become an important policy response to growing obesity rates and the prevalence of type 2 diabetes in the U.S. and other nations. Since 2015, eight U.S. cities have implemented these taxes, but so far direct evidence of their impacts on household purchasing behavior is scarce. Of particular interest to many researchers and policy makers is the response of low-income consumers to these taxes, both because they have higher sweetened beverage consumption on average and because of concerns that sweetened beverage taxes are regressive. This project will investigate the income-stratified household response to sweetened beverage taxes using a data set containing the purchasing behavior of approximately 500 households in the cities of Seattle, San Francisco, Oakland, and Philadelphia, all of which have recently introduced beverage taxes. Knox and Jones-Smith’s analysis will combine this household-level data with proprietary data on beverage and retailer characteristics specific to the context of these taxes. Whereas previous literature in this area has used household responses to general price fluctuations to simulate household responses to sweetened beverage taxes, this novel data set will enable the PIs to detect household responses to these taxes directly. Direct measurement of the consumer response to these taxes is important if, as has been shown with other consumption taxes, consumers respond differently to them than to idiosyncratic price fluctuations. By improving understanding of household behavior around sweetened beverage taxes, Knox and Jones-Smith’s findings have the potential to improve sweetened beverage tax policy and promote population health.

Wilson & Wakefield Analyze Summary and Birth History Data through Modeling Advancements in New Research

Katie Wilson (UW Biostatistics) and CSDE Affiliate and Executive Committee Member Jon Wakefield recently published their methodological research in Demographic Research. Their work is motivated by the tension between demand for high-quality subnational estimates of under-5 mortality and data limitations in lower- and middle-income countries. In the paper, Wilson & Wakefield describe a computationally efficient, model-based approach that allows summary birth history and full birth history data to be combined into analyses of under-5 mortality in a natural way.