Economics and Computer Science interact in multiple areas. The traditional linkage has been in Numerical Analysis (or “numerical methods”), a standard Computer Science field that is also important to econometricians who write their own code. The same can be said for database analytics – an increasingly important tool as datasets explode in size. More recently, Machine Learning and Artificial Intelligence have become key tools in empirical work in economics, and the drive to link causal inference (an economists’ obsession) with Machine Learning brings the fields together tightly. At the same time, both Mechanism Design, and resulting matching models, as well as Network Theory have emerged as truly interdisciplinary fields – and faculty from both Duke Computer Science and Duke Economics are working in these areas.
The MSEC program combines the strengths of the Departments of Economics and Computer Science to educate students in these important computational skills linked to economics, and to prepare them for Ph.D. studies or careers in economics, finance, government, and business.
This program is designed to meet the needs of students with varied levels of exposure to either field, but a strong quantitative background is recommended.
What Makes Our Program Different?
We offer courses from multiple disciplines and departments, opportunities for teaching and research, a student population with diverse interests, career paths beyond academia, and more!
The MSEC differences:
- Courses everywhere! In nearly all master’s programs, students take a nearly set curriculum with few if any electives – and such electives that do exist tend to be within a single department. In contrast, MSEC students have few restrictions, and can take courses across the university (subject to advisor approval), both at the master’s and PhD levels. And students do! In addition to CS and Econ courses, students typically take courses in Mathematics, Statistics, Public Policy, Environmental Science, Health Policy/Medical School, and Business courses ranging from quantitative marketing to finance to strategy, and more.
- Research Assistant (RA) opportunities: in most CS and Econ master’s programs, research receives little or no emphasis, and there are no opportunities to work as an RA. Duke is different: master’s students can work as RA’s, and MSEC students are highly sought after for their mix of skills. Research assistant work is important for learning about the research process, strengthening applied skills and tools, and, in many cases, getting joint publications.
- Teaching Assistant (TA) opportunities: in most CS and Econ master’s programs, few if any master’s students have the opportunity to work as a TA. Again, Duke is different: master’s students can work as TA’s, and MSEC students are highly sought after for TA work as well. Being a TA is especially important for those who go on to PhD programs, and above all for international students: being hired as a TA sends a signal that professors have sufficiently high regard for your expository ability that they feel comfortable putting you in front of a class of native speaker undergraduates or MBAs. Moreover, TA work in a graduate course enhances your learning far beyond simply being a student in the class.
- Diversity of student interests: the MSEC student body has interests that range enormously (see the above list of additional departments in which students take coursework) while sharing common core interests as well. Indeed, the MSEC experience allows student to explore a variety of interests before settling down – and a high fraction of MSEC students change their interests during the course of their study.
- Industry vs. PhD: roughly 40% of MSEC students go on to doctoral programs, though many in that group will work for a couple years before doing so. We seek a diverse group, and prepare people for both industry and academe. Within industry, MSEC alumni go into tech, finance, marketing, consulting, research, and government. They also go into large established firms as well as – with the enthusiastic support of their advisors – start-ups. As MSEC is a STEM program, international students are highly recruited into private sector jobs in the US.
- Elite program: MSEC is a tough program – there aren’t that many people who jump at taking graduate coursework in Computer Science and Economics…and often other highly quantitative disciplines as well. But those who do, and who have the requisite background form, well, an elite. MSEC recognizes that, and in turn commits to offering individualized programs and lots of faculty attention. This means keeping the program small, with entry classes in the range of 16-20.
Degree Requirements Summary
- 30 credits in economics and computational science
- At least 12 credits in Economics, with no more than 6 credits from any one of following the three sub-fields:
- ECON 601 Microeconomics
- ECON 605 Advanced Microeconomic Analysis
- ECON 701 Microeconomic Analysis I
- ECON 705 Microeconomic Analysis II
- ECON 602 Macroeconomic Theory
- ECON 606 Advanced Macroeconomics II
- ECON 652 Economic Growth
- ECON 656S International Monetary Economics
- ECON 702 Macroeconomic Analysis I
- ECON 706 Macroeconomic Analysis II
- ECON 608 Introduction to Econometrics
- ECON 612 Time Series Econometrics
- ECON 613 Applied Econometrics in Microeconomics
- ECON 703 Econometrics I
- ECON 707 Econometrics II
- Or approved substitutes.
- At least 12 credits in Computer Science (500-level or higher)
- At least 12 credits in Economics, with no more than 6 credits from any one of following the three sub-fields:
- Internship (optional)
- ONE capstone course, selected from the following options:
- Any graded graduate computer science course (including independent study) with a significant project component may serve as a capstone course.
- An approved economics capstone course
- Completion exercise: The student must pass a final exam administered by the student’s committee covering a portfolio of learning and research activities carried out during their master’s studies. The portfolio must include one of the following two items: a capstone course in either computer science or economics, or a project paper on an approved topic developed via independent study with one or more computer science and/or economics faculty advisors if available. This document is expected to describe a mature project with research content.
- Final exam
- Responsible Conduct of Research (RCR) training during orientation and 1 RCR forum 2-hour course (either GS 711 or GS712)
- (For International Students) English Language Proficiency
The program requires 30 credits in computer science and economics, or related fields, subject to approval by the program's directors of graduate studies. We expect that students will take four semesters to complete all the requirements. Students must receive a grade of B- or better in the 30 degree course credits.
It is the policy of The Graduate School that undergraduate courses (499 or lower) do not count towards the M.A. degree or a student's GPA. Courses that are cross-listed as both undergraduate- and graduate-level courses count towards the M.A. degree and a student's GPA only if they have a separate, more rigorous syllabus for graduate students. It is the student's responsibility to verify that this is the case before enrolling in any cross-listed courses.
You have a vast array of courses from many departments to choose from, and that means working with many different professors. We can’t list them all, but some of the people and teams of interest include:
- The Directors of Graduate Studies, Jeff Chase in Computer Science and Charles Becker in Economics. They are the MSEC students’ primary advisors. Chase specializes in utility computing, network storage and network I/O, distributed systems, operating systems, and large-scale network services. Becker is an applied microeconomist who teaches micro theory for fun, works in economic demography and the long run consequences of war, especially in the former Soviet Union and its neighbors, and uses satellite night light data whenever possible. His US topics include the effects of topography on spatial sorting and the economics of trailer parks.
- The Economics applied micro group is large. Junior faculty in labor, public economics, and social topics such as crime and education, and who tend to work with MSEC students include Bocar Ba, Jason Baron, and Pengpeng Xiao.
- Michael Pollmann (causal inference and machine learning) and Modibo Sidibe (structural econometrics and search theory) merit a separate bullet point since their work is central to many MSEC topics.
- Senior faculty in labor and public economics and who work with MSEC students include Peter Arcidiacono, Patrick Bayer, and Marjorie McElroy. Macroeconomist David Berger also is close to this group – and works with MSEC students…
- …as does micro theorist Huseyin Yildirim. Among the other micro theorists, Rachel Kranton,who focuses on networks, is of particular interest.
- There is also a large group working in economic development. Those most likely to work with MSEC students include Erica Field and Rob Garlick.
- A final group of Econ faculty we must note is the industrial organization group – of particular interest as well to those interested in business topics such as quantitative marketing and strategy. Those who have worked with MSEC students include Allan Collard-Wexler, Jimmy Roberts, and Daniel Yi Xu.
- On the Computer Science side, Cynthia Rudin gets top billing – she teaches and works with more MSEC students than anyone at Duke. She works on machine learning techniques and causality in a vast array of applied and theoretical topics.
- Both Sudeepa Roy and Alex Volfovsky work closely with Cynthia – and with MSEC students.
- Pankaj Agarwal is right up there with Cynthia as well. His fields include Computational and combinatorial geometry, massive data processing, geographic information systems, ecological modeling, computational molecular biology, and robotics. Professor and Department Chair Jun Yang in database systems and architecture (and computational journalism!) is also important for MSEC students.
- Ashwin Machanavajjhala also attracts and works with MSEC students. His fields include Privacy preserving data analysis, fairness in data science and machine learning (ML) workflows, cryptography and secure computation, and combatting misinformation.
- In algorithms, social choice, and database and numerical analysis, Kamesh Munagala has drawn and worked with many MSEC students, while Debmalya Panigrahi in algorithms and Ron Parr in Bayesian networks, reasoning under uncertainty, Markov decision processes, reinforcement learning, and robotics are also key faculty for MSEC students.
- Carlo Tomasi, who teaches computer vision, is an MSEC student favorite.
- Other faculty of interest include Alexander Hartemink (Computational biology, machine learning, Bayesian statistics, systems biology, transcriptional regulation, genomics and epigenomics, graphical models, Bayesian networks, moral AI, computational neurobiology, classification, feature selection: a recent MSEC student TA’d for computational genomics and transformed their interests…from finance!). And Xiaobai Sun, who teaches numerical analysis, is a key (and helpful!) faculty member for MSEC students, especially those with weaker CS backgrounds.
- Finally, though CS is her secondary field, Becky Steorts (who often teaches STA 602, Bayesian stat), cannot go unmentioned, as she has had an enthusiastic MSEC following. Her research interests include computationally scalable approaches to social science applications, where she focuses on recovering high-dimensional objects from degraded data and determining how to recover the underlying structure. Methods used for this are entity resolution, small area estimation, locality sensitive hashing, and privacy-preserving record linkage as applied to medical studies, fmri studies, human rights violations, and estimation of poverty rates in hard-to-reach domains.
Mentoring relationships with faculty are an important element of the graduate education experience. Mentoring is most important for students conducting research or other independent work. The Computer Science and Economics Departments both have mentoring statements that are somewhat applicable, but these are largely aimed at PhD students. Nonetheless, you should review these statements here for CS, and below for Economics (open "Faculty Advisor & M.A. Student Relationship" tab, as much of the commentary is highly appropriate, and will not be repeated here.
Given the limited time (3-4 semesters) of the MSEC program, the deep mentoring relationships that are formed during doctoral study are modified at the master’s level. However, an outstanding feature of the MSEC program relative to most if not all peer programs is that a substantial amount of mentoring exists, as do structures for it.
A mentor works with you to form goals that are right for you and to plan how to achieve them. A mentor also evaluates your work and gives constructive feedback to help you focus your work and be more effective. Your primary mentors are, in approximate order of importance:
- The MSEC Directors of Graduate Study (DGS) in Economics (currently, Charles Becker) and Computer Science (currently, Jeffrey Chase), who serve as your academic advisors;
- Any faculty in Computer Science and Economics for whom you are a research assistant
- Any faculty in Computer Science and Economics for whom you complete a major research assignment in a class that counts as a Capstone Course and that will be included in your portfolio as meeting the capstone requirement.
In addition, the MSEC program has two additional sources of mentoring:
- The MSEC Alumni Mentoring Team, which consists of 10-12 recent alumni both in industry and academe, and who meet periodically to discuss their career trajectories or to be available to offer career advice
- The Economics Master’s Alumni Advisory (MAAB) Board, which plays a similar role, but consists of more senior alumni and is available to all Economics master’s program students.
This document sets out some rules, responsibilities, and expectations for mentoring in the MSEC program. Its purpose is to guide students and faculty toward effective mentoring relationships that are mutually beneficial and free of conflicts. Many mentoring interactions occur in the context of your research efforts, which are formalized in a research milestone assessment for the graduate program, and which involves independent work under the guidance and supervision of the faculty.
Completing the Graduate Program
You may view your graduate program as a sequence of steps or milestones in addition to coursework. In a research milestone you conduct some independent academic work in collaboration with a faculty research advisor and possibly others. You write a paper or program, or organize a research-oriented website, and at oral examination defense you give a presentation about the work and answer questions from your audience. An academic committee of faculty members evaluates the work and certifies successful completion of the milestone. Your advisor guides you in the work, certifies when you are ready to defend the work, suggests other faculty for your committee, and chairs the committee at the defense.
The MSEC program has a single milestone. You are expected to submit a comprehensive portfolio that includes major papers, computer programs, and reports of internships that you completed during your period of study. The portfolio is then reviewed in advance by a faculty committee that meets with you for an oral examination based on your course projects and other research.
Graduate Program Offices
The graduate program office (DGS office in Computer Science; EcoTeach in Economics) is here to assist you as you progress through your program. We handle various administrative details for you to manage your funding, receive credit for your work, and complete your degree. The office also manages an administrative process when you enter the program and when you apply to graduate, and also plays a role in courses, exams, internships, fellowships, and other matters. A designated faculty member from each department serves as Director of Graduate Studies (DGS), and works with a staff assistant (DGSA) and Graduate Program Coordinators.
We ask you to help us help you. In particular, we expect you to know your degree requirements, plan ahead, follow our administrative instructions carefully, meet all relevant deadlines, and be responsive to our communications with you on your department email address. In particular, students who get into trouble with meeting a degree requirement often say that they were unaware of what was expected of them, or that their advisor failed to push them to complete it. It is your responsibility to know the requirements for your graduate program and to work with your advisor to meet them.
You should ask the DGS/EcoTeach office for help when you need it. We can answer your questions and address situations that might arise. If you feel that something is not going well or that you are blocked from your goals, then you should talk to us. We will help make a plan to address the issue and connect you with other resources in the University as needed.
Your communications with the DGS/EcoTeach office are confidential, except that we are mandated to request help from a University office for certain equity issues and risks, such as situations involving harassment or a risk of violence.
In particular, you should contact the DGS/EcoTeach office to help you if you feel that you are treated unfairly or unprofessionally, that others are not meeting their responsibilities to you, that expectations set for you are unclear or unreasonable, or that you are encountering a hostile work environment or other unhealthy or unsafe conditions. If you prefer, you may instead contact other offices or resources at Duke for help. For example, you may connect at any time certain Duke University resources for wellness or counseling, or the Office of Institutional Equity, or the Graduate School (TGS), or the Computer Science Department Chair. These offices and others publish web pages and other outreach to help you find them and understand what services and confidentiality they provide.
The Graduate School (TGS) outlines responsibilities of faculty members and students in mentoring roles and in all of their various roles and interactions. That document also summarizes responsibilities of the graduate program and TGS, and a process for appeal of grievances to the Chair and Dean if the DGS is unable to resolve the situation.
To summarize using language from that document, faculty are expected to: respect your interests/goals; assist you in pursuing/achieving them; provide clear expectations on your responsibilities as a student and expectations for the work you undertake with them; evaluate your progress and performance in a timely, regular, and constructive fashion; avoid assigning any duty or activity that is outside your interest or responsibility; be fair, impartial, and professional in all dealings with you; avoid conflicts of interest; and ensure a collegial learning environment of mutual respect and collaboration.
Naturally, you share the faculty's responsibility by taking the lead for your own success, communicating your needs clearly, being appropriately professional, honorable, and respectful in your dealings with others, and doing your part to promote a collegial and respectful learning environment for everyone.
In an academic environment, students and faculty are free to choose how to meet their goals and responsibilities to one another. When you interact with faculty in any of their roles, you must be mindful that they balance their time spent with you against their other responsibilities, goals, and interests. They choose how much of their time to allocate for you. Their choices are based in part on the significance of their responsibilities to you in a specific role. For example, your advisor for a research project may delegate some of their mentoring responsibility to guide your work and monitor your progress to other members of the research group. Committee members may take a more or less active role depending on the nature of the project and milestone.
You in turn are responsible to make efficient use of the faculty time that you request, and to talk to the DGS office (in Computer Science) or EcoTeach office (in Economics) if you feel that you are not getting sufficient attention.
Faculty advisors assigned to MA students are responsible for assisting them in discovering and participating in appropriate channels of scholarly, professional, and disciplinary exchange; and for helping students develop the professional research, teaching, and networking skills that are required for a variety of career options, both within and outside academia. By doing this, advisors play a crucial role in the development and success of our graduate students, engaging with the next generation of researchers and scholars.
The advisor-advisee relationship is a cooperative partnership that should be based on mutual respect and acceptance of responsibilities. In this document, we describe the main responsibilities of advisors and students, as well as the channels available to resolve problems that can appear in this relationship.
Responsibilities for MA Advisors
An effective academic advisor has the following responsibilities:
- Have basic knowledge of MA program requirements and the Graduate School policies regarding academic milestones.
- Listen to and support an advisee’s scholarly and professional goals.
- Help the advisee develop a timeline for completing academic requirements and meeting professional goals. Take reasonable measures to ensure that this timeline is met.
- Communicate clearly and frequently with an advisee about expectations and responsibilities.
- Meet with an advisee to review progress, challenges, and goals. Advisors should meet with their students at least once a semester, prior to registration. They should have at least one additional meeting with incoming students at the start of their first semester.
- Encourage openness about any challenges or difficulties that impact the graduate student experience and work with the advisee to resolve any challenges.
- Act as a liaison between the student and the Director of Graduate Studies and the department.
- Be aware of institutional resources that can provide support to advisees in times of academic, professional, and personal challenges and whom you, as an advisor, may consult for further guidance.
- Notify the Director of Graduate Studies if you know or suspect that your advisee is facing significant academic or personal challenges.
Responsibilities for Students
To be an effective advisee, students have the following responsibilities:
- Become familiar with the graduate program requirements and the Graduate School policies regarding academic milestones.
- Work with your advisor to develop a timeline for completing academic requirements and meeting professional goals.
- Devote an appropriate amount of time and energy toward achieving academic excellence and earning the advanced degree in a timely fashion.
- Take the initiative. Be proactive in finding answers to questions and in planning your future steps.
- Meet with their advisors once a semester, before registration. First-year students should also meet with their advisors at the start of their first semester.
- Be honest with your advisors. Alert them about any difficulties you may have about program requirements, normal progress, and performance expectations.
- Be willing to be mentored and open to feedback. Listen and respond appropriately to recommendations from advisors.
- Be mindful of time constraints and other demands imposed on faculty members and program staff.
As with any other relationship, the advisor-advisee partnership may fail to function as expected. There may be multiple reasons for this. For example, the advisor or the advisee may repeatedly fail to satisfy the responsibilities described earlier; or the advisor and advisee may have a personal conflict that cannot be easily resolved.
These situations should be discussed first with the Director of Graduate Studies, and subsequently, and only if necessary, the Chair of the department. These department representatives will assist in mediating existing problems.
If the departmental efforts to resolve these problems are unsuccessful, students and faculty can refer to the Associate Dean or the Dean of the Graduate School for a formal resolution.
This degree program classifies as STEM (CIP Code 45.0603: Econometrics and Quantitative Economics), and students in this program can apply for a 24-month STEM extension of F-1 Optional Practical Training (OPT).