Wednesday
Oct192016

Predebate Discussion with Robert Guttman and Matt Laslo

Friday
Oct142016

Data-driven Campaigning in 2016

The most recent meeting of the Government Analytics Breakfast forum featured Dr. Vanessa Perez, a lecturer with the MS in Government Analytics program and expert on voting and elections.  Dr. Perez's talk, How the 2016 Campaigns Use (and Don't Use) Data, examined the ways in which political campaigns rely on data to shape their mobilization and persuasion strategies.

Dr. Perez began by discussing the types of datasets historically and currently available to parties and campaigns.  Following the implementation of the Help America Vote Act (2002), voter data files have become much cleaner, richer and accessible.  Campaigns can now access individual-level datasets that include (depending on the state) voters' names, addresses, race, party identification and turnout history.  These datasets, merged with widely available consumer data, provide campaigns with tremendous predictive power when identifying existing and potential supporters.

One of the chief uses of data by campaigns is the identification of "persuadables" -- individuals who might be convinced to support the candidate if targeted with the right message.  If the state provides party ID data, campaigns will often target self-identified independents who have voted in prior elections (as the strongest predictor of whether someone will vote in a current election is his/her turnout history).  If the state does not provide party ID data, campaigns will try to identify persuadables using other variables, such as citizens' neighborhood characteristics.

In the 2016 election, both the Trump and Clinton campaigns have embraced data-driven strategies, though in different ways and to different degrees.  While the Clinton campaign has built off the strategy and infrastructure developed by the Obama campaigns, Trump has implemented a "radically different strategy for a radically different candidate."  Rather than targeting habitual voters, the Trump campaign is focused on new voters -- voters who have a high likelihood of supporting Trump but may not have voted consistently (if at all) in the past.  The election results and exit poll data will provide insight into the effectiveness of the candidates' strategies.

Many thanks to Dr. Perez for fascinating and enlightening talk.

You can view the full presentation here.

Tuesday
Oct042016

Frame by Frame Screening Tomorrow

We're delighted to be holding a viewing tomorrow of Frame by Frame, a wonderful documentry about the power of photojournalism in Afghanistan.  One of our very own alum, Baktash Ahadi was an associate producer and translator on the film.  

Born in Kabul in 1981, Baktash and his family had to flee during the Soviet Invasion in 1984. After spending over a year and half in Pakistan between refugee camps and makeshift homes, his family was given asylum in the United States and started their new life in Carlisle, Pennsylvania. Baktash started his career as a Peace Corps Volunteer in Mozambique. He then went into management consulting with Booz Allen Hamilton before serving as a military translator in Afghanistan for three years. His experience not only brought him closer to his roots and but also instilled a sense of responsibility to educate others on the realities on the ground in Afghanistan. Baktash joined FRAME BY FRAME as an ambassador for that same reason — to shed light on the country's complexities through human stories.  

Baktash will have a Q&A at the end of the screening tomorrow, we hope to see you there!

http://www.framebyframethefilm.com/

 

 

Friday
Sep232016

Alexander Rosenthal Shares Insights on The Idea of Europe and Nationalism at the Center

Dr. Rosenthal, JHU Adjunct Faculty, delivered a thoughtful talk about the idea of Europe and the recent resurgence of nationalism Wednesday at the JHU Governmental Studies Center.   Dr. Rosenthal served for many years as the program coordinator for the JHU Governmental Studies Center before moving to Europe.  The room was filled with faculty and former and current students, who engaged Dr. Rosenthal in a very interesting and sustained discussion that lasted well into the evening.  Dr. Rosenthal's power point presentation is attached here

Tuesday
Aug232016

Student Spotlight: Robyn Wallace

Robyn C. Wallace is a student in the MS in Government Analytics program with a concentration in statistical analysis.

I am a scientific data analyst with Northrop Grumman, a major US defense and technology firm.  Through a contract with the company, I work at the Centers for Disease Control and Prevention (CDC) in Atlanta where I work on a variety of programs within the Division of HIV/AIDS Prevention (DHAP) and the National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP).  As an analyst, having the skills to thoughtfully design experiments, analyze large amounts of data, and interpret and leverage data are key factors to successfully solve problems and optimize value within public health programs.  The MS in Government Analytics program is expertly designed to expand my proficiency in the latest analytics technologies, applications, and practices that are actively reshaping the public sector.  

This skills learned in this program are directly applicable to my work as an analyst within CDC’s Population Health Division, Behavioral Risk Factor Branch. Working in this role, while pursuing this degree, has afforded me the platform to apply fundamental techniques learned to a practical setting within the Public Health sector.  A large component of my position involves developing data standards and methodologies for Population Health Surveillance data in tandem with designing and coding statistical models to determine chronic health status at the state and county level. Analyzing health status at the county level is particularly important since state and local governments require sub-state geographically based information in health policy planning and program implementation.  However, most public health data, including the Behavioral Risk Factor Surveillance System (BRFSS), are collected nationally and not designed to produce direct estimates for chronic health conditions at the county level as the sample sizes are too small.  Hence, the estimates at the county level are not reliable or stable.  To mitigate this, the Behavior Risk Factor Branch has designed a methodology, primarily using SAS, to produce accurate chronic health county estimates when aggregated at the state level.  As the lead analyst on this project, I’ve worked to develop BRFSS’ small area estimation method and have recently published a paper in Preventing Chronic Disease on this research.   

With the knowledge gained in the MS program, I plan to expand current modeling techniques within the Behavioral Risk Factor Branch that will offer additional information about national health data outcomes and introduce new software, such as R and Stata, into BRFSS’ functionality.  Owing to the skills learned in courses such as Advanced Quantitative Methods, my goal is to streamline the current small estimation method by utilizing multiple imputation to address survey data incompleteness.  I also plan to explore bootstrapping as a method to address underestimated standard errors, a major concern in the BRFSS small area estimation method resulting from the model not taking into account complex design variables.  Exploring bootstrapping and other methods will set the stage for future papers on small area estimation for the Behavioral Risk Factor Surveillance System.