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
Alan Yang, Senior Lecturer in the Discipline of International and Public Affairs
Doru Cojoc, Lecturer in the Discipline of International and Public Affairs
Douglas Almond, Professor of International and Public Affairs and Economics
Eric Verhoogen, Professor of International and Public Affairs and Economics
Harold Stolper, Lecturer in the Discipline of International and Public Affairs
Jeffrey Shrader, Assistant Professor of International and Public Affairs
Rodrigo Soares, Lemann Professor of Brazilian Public Policy and International and Public Affairs
Sameer Maskey, Adjunct Associate Professor of International and Public Affairs
Sharyn O'Halloran, George Blumenthal Professor; Professor of International and Public Affairs
Tamar Mitts, 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 focused in either quantitative analysis or data analytics. 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. Additionally, it is strongly recommended that students complete SIPA U6500 Quantitative Analysis I for International and Public Affairs during their first semester.
New incoming students from Fall 2022 and onward must have three of the required six‐points taken from a course (or two 1.5 credit classes) that has SIPA U6501 Quantitative Analysis II for International and Public Affairs as a requirement. These courses are listed as Advanced Courses in the Courses tab.
Continuing SIPA students declaring DAQA can choose any course from the Advanced Course, and SIPA Electives course lists respective to their Data Analytics or Quantitative Analytics Focus Area to fulfill their credit requirements.
Continuing DAQA students can choose any course from the Advanced Course and SIPA Electives course lists respective 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 |
| Code | Title | Points |
|---|---|---|
| Points | ||
Advanced Courses | ||
| INAF U6599 | Quant III: Labor Economics For Policy Students | 3 |
| INAF U6603 | Data Analysis for Policy Research Using STATA | 3 |
| INAF U6604 | Applied Econometrics | 3 |
| INAF U6605 | Impact Evaluation Methods and Applications to Health and Social Policy | 3 |
| INAF U6608 | Economics of Education Policy | 3 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3 |
| INAF U6616 | Empirical Analysis of Energy Markets | 3 |
| INAF U8145 | Advanced Economic Development for International Affairs | 3 |
| INAF U8305 | Conducting Empirical Research in Economics | 3 |
| INAF U8360 | Economic Measurement of Discrimination | 3.00 |
| PEPM U6640 | Macroeconometrics | 3 |
| PUAF U8516 | Time Series Analysis | 3 |
| SIPA U8500 | Quantitative Methods in Program Evaluation and Policy Research | 3 |
SIPA Electives | ||
| INAF U6013 | Cost-Benefit Analysis | 3.00 |
| INAF U6016 | Cost-Benefit Analysis | 3 |
| INAF U6022 | Economics of Finance | 3 |
| INAF U6045 | International Capital Markets | 3 |
| INAF U6098 | Financial Risk Management and Public Policy | 3 |
| INAF U6116 | Infrastructure Cost-Benefit Analysis | 3 |
| INAF U6301 | Corporate Finance | 3.00 |
| INAF U6326 | Renewable Energy Project Finance Modeling | 3 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.5 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3 |
| INAF U6514 | Text as Data | 3 |
| INAF U6600 | Testing Models of Public Policy Making | 3 |
| INAF U6858 | Economics of US Social Policy | 1.50 |
| INAF U6889 | Impact Measurement ＆ Evaluation for Sustainable Development | 3 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3 |
| INAF U6898 | Program Evaluation and Design | 3 |
| INAF U8195 | Behavioral Development Economics | 3.00 |
| PUAF U6033 | Decision Models ＆ Management (or EMPA U6033 or SUMA K5033) | 3 |
| PEPM U6640 | Macroeconometrics | 3 |
| PEPM U6850 | Growth Strategies | 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 |
| QMSS GR5073Q | Machine Learning for the Social Sciences | 3 |
| Code | Title | Points |
|---|---|---|
| Points | ||
Advanced Courses | ||
| INAF U6006 | Computing in Context | 3 |
| INAF U6506 | Data Science ＆ Public Policy | 3 |
| INAF U6514 | Text as Data | 3 |
| INAF U6600 | Testing Models of Public Policy Making | 3 |
| INAF U6614 | Data Analysis for Policy Research Using R | 3.00 |
| PUAF U8516 | Time Series Analysis | 3 |
SIPA Electives | ||
| INAF U6004 | Programming for Social Impact | 1.5 |
| INAF U6005 | Natural Language Processing Applications in Public Policy | 1.5 |
| INAF U6009 | Artificial Intelligence in Public Policy | 1.5 |
| INAF U6098 | Financial Risk Management and Public Policy | 3 |
| INAF U6272 | Introduction to Data Analytics for Public Policy, Administration, and Management | 1.5 |
| INAF U6274 | Introduction to Database Design, Management, and Security | 1.5 |
| INAF U6502 | Into to Text Analysis in Python | 3 |
| INAF U6504 | Python for Public Policy | 1.5 |
| INAF U6508 | Using Big Data to Develop Public Policy | 3 |
| INAF U6511 | Intro to Infographics and Data Visualization | 1.5 |
| INAF U6512 | Data Driven Approaches for Campaigns and Advocacy | 3 |
| INAF U6593 | R for Public Policy | 1.5 |
| INAF U6892 | Monitoring and Evaluation: Driving Evidence-Based Development and Humanitarian Aid | 3 |
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 |
| QMSS GR5073Q | Machine Learning for the Social Sciences | 3 |
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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