The specialization in Data Analytics and Quantitative Analysis (DAQA) provides opportunities to pursue advanced work in computational and data analytics, econometrics and quantitative analysis and to apply these techniques to a broad array of policy and management issues.
Cristian Pop-Eleches, Professor of International and Public Affairs
Specialization Director
cp2124@columbia.edu
Marie Gugnishev
Specialization Coordinator
mg4441@columbia.edu
Cristian Pop-Eleches, Professor of International and Public Affairs; Director of the Data Analytics and Quantitative Analysis Specialization
Douglas Almond, Professor of International and Public Affairs
Flavio Bartmann, Adjunct Professor of International and Public Affairs
Daniel Björkegren, Assistant Professor of International and Public Affairs
Sandra E. Black, Professor of Economics and of International and Public Affairs
Nelson Colon, Lecturer of International and Public Affairs (part-time)
Aidan Feldman, Lecturer of International and Public Affairs (part-time)
Poranee 'Pam' Kingpetcharat, Lecturer of International and Public Affairs (part-time)
Rebecca Krisel, Lecturer of International and Public Affairs (part-time)
Emmanuel Letouze, Adjunct Associate Professor of International and Public Affairs
Sameer Maskey, Adjunct Associate Professor of International and Public Affairs
Tamar Mitts, Assistant Professor of International and Public Affairs
Suresh Naidu, Professor of International and Public Affairs
Sharyn O'Halloran, George Blumenthal Professor; Professor of International and Public Affairs (on leave)
Nuria Oliver, Adjunct Professor of International and Public Affairs
Stephanie Rosoff, Lecturer of International and Public Affairs (part-time)
Harold Stolper, Lecturer in the Discipline of International and Public Affairs
Ebonya Washington, Professor of International and Public Affairs
Douglas Williamson, Adjunct Associate Professor of International and Public Affairs
Alan Yang, Senior Lecturer in the Discipline of International and Public Affairs
Mike Zhu, Adjunct Assistant Professor of International and Public Affairs
The Data Analytics & Quantitative Analysis (DAQA) Specialization requires 9 points, consisting of one required three-point course, and six-points in either quantitative analysis or data analytics electives.
In addition to these requirements, DAQA students are required to complete the SIPA U6400 / SIPA U6401 sequence of economics in the MIA and MPA core and SIPA U6500 Quantitative Analysis I for International and Public Affairs to qualify for the DAQA Specialization. Additionally, students must earn a minimum grade of B- in SIPA U6400 and SIPA U6500. It is strongly recommended that students complete SIPA U6500 during their first semester.
Questions should be directed to Marie Gugnishev, Coordinator of the DAQA Specialization, at mg4441@columbia.edu.
SIPA U6400 Microeconomic Analysis for International and Public Affairs*
SIPA U6401 Macroeconomic Analysis for International and Public Affairs
SIPA U6500 Quantitative Analysis I for International and Public Affairs*
*Minimum grade requirement of B-
SIPA U6501 Quantitative Analysis II for International and Public Affairs
3 Credits of an Advanced Course
3 Credits of electives approved by the Specialization Director
Due to International Economic Policy requiring SIPA U6501 as a core course, students in this concentration must instead take an additional DAQA elective course to fulfill specialization requirements for a total of 9 credits in DAQA electives:
3 credits in an Advanced Course
6 credits in electives approved by the Specialization Director
Continuing DAQA students can choose any course from the Advanced Course and SIPA Electives course lists respectively to their Data Analytics or Quantitative Analytics Focus Area to fulfill their credit requirements.
| Code | Title | Points |
|---|---|---|
| Points | ||
| SIPA U6501 | Quantitative Analysis II for International and Public Affairs | 3.00 |
| Code | Title | Points |
|---|---|---|
| Points | ||
Advanced Courses | ||
| INAF U6599 | Quant III: Labor Economics For Policy Students | 3.00 |
| INAF U6604 | Applied Econometrics | 3.00 |
| INAF U6608 | Economics of Education Policy | 3.00 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| INAF U8145 | Advanced Economic Development for International Affairs | 3.00 |
| INAF U8305 | Conducting Empirical Research in Economics | 3.00 |
| INAF U8360 | Economic Measurement of Discrimination | 3.00 |
| PEPM U6640 | Macroeconometrics | 3.00 |
| PUAF U8516 | Time Series Analysis | 3.00 |
| SIPA U8500 | Quantitative Methods in Program Evaluation and Policy Research | 3.00 |
SIPA Electives | ||
| INAF U6016 | Cost-Benefit Analysis | 3.00 |
| INAF U6098 | Financial Risk Management and Public Policy | 3.00 |
| INAF U6301 | Corporate Finance | 3.00 |
| INAF U6326 | Renewable Energy Project Finance Modeling | 3.00 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3.00 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.50 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3.00 |
| INAF U6514 | Text as Data | 3.00 |
| INAF U6858 | Economics of US Social Policy | 1.50 |
| INAF U6889 | Impact Measurement ＆ Evaluation for Sustainable Development | 3.00 |
| INAF U6891 | Impact Evaluations in Practice | 1.50 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3.00 |
| INAF U8195 | Behavioral Development Economics | 3.00 |
| PEPM U6640 | Macroeconometrics | 3.00 |
Non-SIPA Courses | ||
| Courses offered at affiliate Columbia Schools. Please see Cross-Registration instructions to register. Courses not listed must be approved by the DAQA Director. Enrollment is not guaranteed. | ||
| ACTU K5841 | Data Science in Finance and Insurance | 3.00 |
| QMSS GR5073Q | Machine Learning for the Social Sciences | 3.00 |
| Code | Title | Points |
|---|---|---|
| Points | ||
Advanced Courses | ||
| INAF U6006 | Computing in Context | 3.00 |
| INAF U6506 | Data Science ＆ Public Policy | 3.00 |
| INAF U6514 | Text as Data | 3.00 |
| INAF U6600 | Testing Models of Public Policy Making | 3.00 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| PUAF U8516 | Time Series Analysis | 3.00 |
SIPA Electives | ||
| INAF U6004 | Application Development for Social Impact | 1.50 |
| INAF U6005 | Generative AI | 1.50 |
| INAF U6009 | Artificial Intelligence in Public Policy | 1.50 |
| INAF U6098 | Financial Risk Management and Public Policy | 3.00 |
| INAF U6272 | Introduction to Data Analytics for Public Policy, Administration, and Management | 1.50 |
| INAF U6274 | Introduction to Database Design, Management, and Security | 1.50 |
| INAF U6275 | Geographic Information Systems and Analysis | 3.00 |
| INAF U6502 | Into to Text Analysis in Python | 3.00 |
| INAF U6504 | Python for Public Policy | 1.50 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3.00 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.50 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3.00 |
| INAF U6593 | R for Public Policy | 1.50 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3.00 |
| INAF U6958 | Gender Data for Gender Equality | 1.50 |
Non-SIPA Courses | ||
| Courses offered at affiliate Columbia Schools. Please see Cross-Registration instructions to register. Courses not listed must be approved by the DAQA Director. Enrollment is not guaranteed. | ||
| ACTU K5841 | Data Science in Finance and Insurance | 3.00 |
| QMSS GR5073Q | Machine Learning for the Social Sciences | 3.00 |
Matriculated students in this program can view their degree audit report on Stellic.
MIA or MPA students who successfully complete their specialization in Data Analytics and Quantitative Analysis and their concentration in Economic and Political Development, Energy & Environment, or International Finance & Economic Policy, along with their MIA or MPA degree requirements, will have completed their SIPA degree program in a government-approved STEM field.
Students can opt to change their Concentration or Specialization via the Concentration Specialization Declaration Change Form. Requests are reviewed and approved by SIPA Student Affairs advisors. If there is an issue with the request, your advisor will contact you. Otherwise, if approved, the new Concentration/Specialization will appear on your record in SSOL and Stellic.
Students in the Data Analytics & Quantitative Analysis specialization who have also declared their concentration in International Finance and Economic Policy (IFEP), Economic and Political Development (EPD), or Energy & Environment (E&E) CANNOT double-count courses between their concentration and specialization.
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