"Meeting the Challenge of Homelessness"

Ending homelessness and serving the needs of our most vulnerable individuals and families is possible, but it requires sustained effort. Culhane will kick off the week by reviewing the national situation, including progress and continued hurdles. He will also describe unique challenges for cities like LA where many homeless are unsheltered.

"The Promise of Integrated Data Systems for Social Science Research"

Abstract: Integrated Data Systems (IDS) linking administrative, public agency data hold great promise for rapid and low-cost implementation and evaluation of homeless initiatives. Culhane will review the legal, ethical, scientific and economic challenges of interagency data sharing, as well as systematic efforts including policy reform and inter-agency collaboration to overcome these challenges. Finally, he will review important new IDS initiatives in LA County and California.

"The Role of Parental Wealth & Income in Financing Children's College Attendance & Its Consequences"

Abstract: This paper examines the influence of parental wealth and income on their children's college attendance and parents' financial support for it and whether the latter affects the subsequent levels of indebtedness of parents and their children. We use data from the PSID, especially data in the 2013 Rosters and Transfers Module on the incidence and amounts of parents' financial support for their children's college. To instrument for the potential endogeneity of parental housing wealth and income on these decisions, we use changes in parents' local housing and labor market conditions. We find that increases in both parents' housing wealth and income increase the likelihood of their children attending college through the effect of parents' financial support. This parental financing of college leads to parents carrying more debt, but their children having no greater student loan debt after graduation. We also find that parental financing of their child's college education significantly increases the probability that the child actually graduates from college.

The Trouble with Pink and Blue, Gender expression, stigma, and health among U.S. children and adolescents

Abstract: Dr. Gordon will offer a conceptual model for understanding gender expression and health and illustrate this model with examples from recent research on gender nonconformity, school-based violence and bullying, and selected health outcomes in samples of U.S. high school students and young adults.

FP3.0: Increasing the uptake of Long-Acting Reversible Contraceptives (LARCs) among adolescent females and young women in Cameroon

In sub-Saharan Africa, 25% of teenagers have started childbearing (ICF, 2015). While young women describe many of these births as planned and intentional, women under the age of 20 also have the greatest percentage of mistimed/unintended pregnancies compared to all other age groups. For example, in Cameroon, more than 30% of the births to this group were unwanted or wanted later (DHS 2011). Low age at first birth has a significant impact on the spacing of births and timing of future pregnancies. It may also reduce accumulation of human capital for both the mother and the child.

Co-sponsored with the UCLA Luskin Senior Fellows Speaker Series 

Social Science in the Age of Genomics

The cost of genetic information has been dropping at a rate faster than that of Moore's law in microcomputing.  As a result, the science of genetic prediction has improved by leaps and bounds in recent years, and with it has emerged a novel field: sociogenomics.  Sociogenomics seeks to integrate genetic and environmental information to obtain a more robust, complete picture of the causes of human behavior.  This talk will highlight some recent examples of sociogenomic research, touching upon issues such as adolescent peer effects, racial discrimination, assortative mating, and fertility patterns.  The talk will conclude by discussing the social and policy implications of genetic prediction.   

Co-sponsored with the Public Policy and Applied Social Science Seminar Series 

Making Sense of Sensitivity: Extending Omitted Variable Bias

We extend the omitted variable bias framework with a suite of tools for sensitivity analysis in regression models that: (i) does not require assumptions about the treatment assignment nor the nature of confounders; (ii) naturally handles multiple confounders, possibly acting non-linearly; (iii) exploits expert knowledge to bound sensitivity parameters; and, (iv) can be easily computed using only standard regression results. In particular, we introduce two novel sensitivity measures suited for routine reporting. The robustness value describes the minimum strength of association unobserved confounding would need to have, both with the treatment and the outcome, to change the research conclusions. The partial R2 of the treatment with the outcome shows how strongly confounders explaining all the residual outcome variation would have to be associated with the treatment to eliminate the estimated effect. Next, we offer graphical tools for elaborating on problematic confounders, examining the sensitivity of point estimates, t-values, as well as “extreme scenarios”. Finally, we describe problems with a common “benchmarking” practice and introduce a novel procedure to instead formally bound the strength of confounders based on comparison to observed covariates. We apply these methods to a running example that estimates the effect of exposure to violence on attitudes toward peace.