Workshop: Tips for Success in Publishing in Peer Review Journals: An Editor's Perspective Presentation by Prof. Gilbert Gee Prof. Gee Dr. Gee is currently the Editor of the Journal of Health and Social Behavior. He has also been a guest editor for Child Development, Asian American and Pacific Islander Nexus Journal, and the Asian American Journal of Psychology.
The Reversal of the Gender Gap in Education and Family Dynamics in Europe
Although men tended to receive more education than women in the past, the gender gap in education has reversed in recent decades in most Western and many non-Western countries. In this talk, I will discuss the main results of a major research project that aimed to investigate the implications of the reversal of the gender gap in advanced education for family life across European countries. I highlight the results about union formation and assortative mating, discuss our findings about union stability as well as about husbands’ and wives’ relative earnings. Finally, I present some first results from research about implications for fertility behavior. To conclude, I will reflect on implications for conventional theories used in family sociology and demography.
Organizer: Ilan Meyer February 22, 2019 UCLA Faculty Center The target audience for the Workshop is students, post-docs, and early investigators. Participants will learn about the NIH structure and grant processes, meet NIH Program Officers and extramural researchers who have been successful at obtaining NIH funding, and network with others interested in SGM-related health research.
Covariate screening in high dimensional data: applications to forecasting and text data
High dimensional (HD) data, where the number of covariates and/or meaningful covariate interactions might exceed the number of observations, is increasing used in prediction in the social sciences. An important question for the researcher is how to select the most predictive covariates among all the available covariates. Common covariate selection approaches use ad hoc rules to remove noise covariates, or select covariates through the criterion of statistical significance or by using machine learning techniques. These can suffer from lack of objectivity, choosing some but not all predictive covariates, and failing reasonable standards of consistency that are expected to hold in most high-dimensional social science data. The literature is scarce in statistics that can be used to directly evaluate covariate predictivity. We address these issues by proposing a variable screening step prior to traditional statistical modeling, in which we screen covariates for their predictivity. We propose the influence (I) statistic to evaluate covariates in the screening stage, showing that the statistic is directly related to predictivity and can help screen out noisy covariates and discover meaningful covariate interactions. We illustrate how our screening approach can removing noisy phrases from U.S. Congressional speeches and rank important ones to measure partisanship. We also show improvements to out-of-sample forecasting in a state failure application. Our approach is applicable via an open-source software package.
Individual and Neighborhood Vulnerability over the Latin American Immigrant Health Experience
The state of Latino health seemingly defies the way in which the historical disadvantages faced by people of color in the United States get under the skin, and how place matters in reflecting or further reproducing these disparities. Hispanics –especially foreign-born individuals with lower socioeconomic statuses– have more favorable health than other race/ethnic groups –notably, U.S.-born non-Hispanic whites– in a limited but very important set of health outcomes such as cardiovascular function, some cancers and mortality across much of the life course.
In this talk, I discuss the mechanisms/phenomena driving the Hispanic immigrant health advantage, which is likely tied to processes of self-selection as well as to protection and resilience likely operating particularly well in heavily-concentrated Latino neighborhoods and enclaves. Throughout, I present my empirical research aimed at disentangling self-selection processes from the protection that immigrants might draw from fellow neighborhood and/or community members. I further discuss these findings in the context of how immigrants adapt in the longer term: these advantages and resilience eventually erode as immigrants spend more time in the United States –as well as across immigrant generations– through a series of processes by which immigrant and Latino vulnerability become somatized.
I conclude by speculating on the likely future of Latino and immigrant health, discussing how the resilience and vulnerability of Latino immigrants might evolve given recent major shifts U.S. immigration and social policies and practices, and due to important changes in the dynamics of migration between Mesoamerica and the United States.
Title: Grad Student Panel Discussing the Causal Toolkit Location: February 27, 2019, 2:00-3:30 PM 4240 Public Affairs Building CCPR Seminar Room Content: Focusing on the uses of the causal toolkit, several grad students will share a-ha moments and lessons learned from their own applied research. The target audience are grad students and researchers who wish […]
Lan Liu, University of Minnesota at Twin Cities "Parsimonious Regressions for Repeated Measure Analysis" Abstract: Longitudinal data with repeated measures frequently arises in various disciplines. The standard methods typically impose a mean outcome model as a function of individual features, time and their interactions. However, the validity of the estimators relies on the correct specifications […]
Immigrants’ Economic Assimilation: Evidence from Matched Administrative Records
Immigrants’ ability to succeed in the labor market and achieve economic parity with natives has significant long-term implications for their well-being and that of their children. In this talk I will present findings from two studies examining immigrants’ economic assimilation using a dataset that links respondents of the Survey of Income and Program Participation (SIPP) to their individual tax records. The first study examines the lifetime earnings trajectories of immigrants and measures the extent and speed with which they are able to reduce the earnings gap with natives. Findings from this study address key debates regarding ethnoracial and cohort differences in immigrants’ earnings trajectories. First, we find a racially differentiated pattern of earnings assimilation: black and Hispanic immigrants are less able to catch up with native whites’ earnings compared to white and Asian immigrants, but they are almost able to reach earnings parity with natives of their same race and ethnicity. Second, contrary to previous studies we find no evidence that recent immigrant cohorts are experiencing lower earnings growth. The second study examines immigrants’ job instability. We find that foreign-born men, particularly those who are undocumented, were at higher risk of losing their job and becoming involuntarily underemployed during the Great Recession even after controlling for demographic factors and job characteristics.
Immigrants’ Economic Assimilation: Evidence from Matched Administrative Records
Immigrants’ ability to succeed in the labor market and achieve economic parity with natives has significant long-term implications for their well-being and that of their children. In this talk I will present findings from two studies examining immigrants’ economic assimilation using a dataset that links respondents of the Survey of Income and Program Participation (SIPP) to their individual tax records. The first study examines the lifetime earnings trajectories of immigrants and measures the extent and speed with which they are able to reduce the earnings gap with natives. Findings from this study address key debates regarding ethnoracial and cohort differences in immigrants’ earnings trajectories. First, we find a racially differentiated pattern of earnings assimilation: black and Hispanic immigrants are less able to catch up with native whites’ earnings compared to white and Asian immigrants, but they are almost able to reach earnings parity with natives of their same race and ethnicity. Second, contrary to previous studies we find no evidence that recent immigrant cohorts are experiencing lower earnings growth. The second study examines immigrants’ job instability. We find that foreign-born men, particularly those who are undocumented, were at higher risk of losing their job and becoming involuntarily underemployed during the Great Recession even after controlling for demographic factors and job characteristics.
Small steps with Big Data: Using Machine Learning in Resource Economics
This talk looks at how recent developments in Big Data and Machine Learning are being used in conjunction with randomized controlled trials and large population level program evaluations to design, implement and measure efforts to change consumer behavior. We will explore the role played by very detailed consumption data (often at 15 minute intervals), as well as recent techniques such as deep learning to help us better understand individual and population behaviors, and which insights from behavioral sciences are effective at changing behaviors in areas such as energy conservation and efficiency.
Eloise Kaizar, Ohio State University Randomized controlled trials are often thought to provide definitive evidence on the magnitude of treatment effects. But because treatment modifiers may have a different distribution in a real world population than among trial participants, trial results may not directly reflect the average treatment effect that would follow real world adoption […]
Population Vulnerability and Spatial Analytics
There has been a transition from population studies that were relatively data poor to the present day where digital data is plentiful on many fronts. The “Smart City” is fed by sources of information coming from all directions, where sensors observe things about the movement of vehicles and people, infrastructure conditions, air quality, weather, etc. The challenge is to make use of this digital data, and this is precisely the value added offered by a range of big data spatial analytics. This paper examines aspects of population vulnerability, focusing on particular types of risks and hazards in urban areas.
Luskin School of Public Affairs and the California Center for Population Research Presents:Lunch Seminar with CEGA-EASST Fellows. Please RSVP here. March 14, 2019 12:30-1:30pm, Public Affairs Building Room 4240 Muthoni Ng'ang'a, PhD Candidate University of Nairobi "The Impact of Matching Female Lead Farmers to Female Small-holder Farmers on Agricultural Technology Adoption: Evidence from Kenya" In […]
Prep School for Poor Kids: The Long-Run Impacts of Head Start on Human Capital and Economic Self-Sufficiency
This paper evaluates the long-run effects of Head Start using large-scale, restricted 2000-2013 Census-ACS data linked to date and place of birth in the SSA’s Numident file. Using the county-level rollout of Head Start between 1965 and 1980 and state age-eligibility cutoffs for school entry, we find that participation in Head Start is associated with increases in adult human capital and economic self-sufficiency, including a 0.29-year increase in schooling, a 2.1-percent increase in high-school completion, an 8.7-percent increase in college enrollment, and a 19-percent increase in college completion. These estimates imply sizable, longterm returns to investing in large-scale preschool programs.
Live Births and Fertility amidst the Zika Virus Epidemic in Brazil
Abstract: In late 2015, the Brazilian Ministry of Health classified the increase in congenital malformations associated with the Zika Virus (ZIKV) a public health emergency. The risk of ZIKV-related congenital syndrome posed an exogenous threat to reproductive outcomes that could result in declining numbers of live births and potentially fertility. Using 2014-2016 monthly microdata on live births from the Brazilian Information System on Live Births, in this talk I examine live births and fertility trends amidst the ZIKV epidemic in Brazil. Findings suggest a decline in live births that is stratified across socioeconomic status and geographic lines, especially nine months after the call for pregnancy postponement. While declines in total fertility rates were small, fertility trends estimated by age and socioeconomic status suggest important differences in how Zika might have impacted Brazil’s fertility structure. Further findings using monthly data by municipality suggest that the epidemic resulted in a significant decline in fertility even when controlling for characteristics of the municipality. The findings highlight the importance of understanding how exposure to the risk of a health threat directed at fetuses has led to declines in fertility.
Please join us to hear our residents interesting research and give feedback for their upcoming PAA presentations. Presenters: Amanda Gonzalez, "Do You Need to Pay for Quality Care? Exploring Associations Between Bribes and Out-of-Pocket Expenditures on Quality of Labor and Delivery Care in High Volume Public Health Facilities in Uttar Pradesh, India" Mary Robbins, "A […]
Understanding China's Low Fertility in a Gender and Development Approach
Without a surge of new born babies after the Chinese government relaxed the 40-year-long strict one-child family planning policy in 2013 and 2015, the focus of debates regarding China’s declining fertility has shifted from policy to economic and social forces. Different from the mainstream demographers in China, we propose a gender and development approach to understand low fertility in post-reform China. During China's transition from the socialist planned economy to market economy, the old danwei system collapsed and the public and private spheres are increasingly separating, resulting in women's intensified work-family conflicts. Emphasizing on women's dual roles regarding material production and social reproduction, we argue that sustainable fertility, gender equality and economic development can either create a virtuous circle or be trapped in a vicious circle.
With a certain degree of gender equality in both the labor market and the private families, adult women can fully exert their talents at work which can both contribute to economic growth, and also empower them at home. This can help them realize their fertility desires. With unsatisfying or uneven gender equality in the two spheres, either some Chinese women can be pushed out of the labor market to have a second child, or young women may choose to focus on personal development, and postpone or forgo marriage/fertility. We also propose a multi-party-participation social mechanism to address the long term low fertility in China, encouraging individual men and women, family, business and government to all share the duty of social reproduction.
Leveraging big data to assess health effects of changes in physical and social environments, and policy and program implementation
In the era of big data there are opportunities to answer policy-relevant health questions in ways that are timely and cost-efficient. This talk will describe coordination of health data resources for health monitoring and to address questions about the health effects of policies in California. Examples of health effect assessments, including those related to gun shows and the Mental Health Services Act (MHSA), will be presented.
Workshop: UCLA IRB Application Process Presentation by Moore Rhys Assistant Director, Education and Quality, Office of the Human Research Protection Program, UCLA This workshop will provide an overview of the UCLA IRB application process and related policies and procedures. Learning goals for this workshop include: 1) Understanding when IRB review is required and when it […]
Estimating Heterogeneous Treatment Effects and Optimal Treatment Assignment Policies
This talk will review recently developed methods for estimating conditional average treatment effects and optimal treatment assignment policies in experimental and observational studies, including settings with unconfoundedness or instrumental variables. Multi-armed bandits for learning treatment assignment policies will also be considered.
Co-sponsored with the Center for Social Statistics
