Nancy Qian
James J. O'Connor Professor of Managerial Economics & Decision Sciences
(Center) Co-Director, Global Poverty Research Lab (GPRL)
Nancy Qian is the James J. O’Connor Professor of Economics at the Kellogg School of Management MEDS department. Professor Qian holds a Ph.D. in Economics from the Massachusetts Institute of Technology and was a Harvard Academy post-doctoral fellow at the Weatherhead Center for International Studies at Harvard University. She was an Associate Professor at the Department of Economics at Yale University prior to Kellogg.
Professor Qian’s research provides rigorous empirical evidence for the detailed processes of the root determinants of economic development: geography, demography, human capital (e.g., health, work experience), institutions and culture. She does this by investigating theoretically motivated questions with creative strategies and large data sets from modern and historical contexts around the world. Amongst other honors, she was named a Fellow of the Econometrics Society and received the Alfred P. Sloan Fellowship, as well as grants from the National Science Foundation and the Russel Sage Foundation. She is one of the most highly cited economists of her generation.
She is passionate about using research to address real-world problems and using higher education to encourage the personal and intellectual developments of students. At Northwestern, she has taught classes for full-time and part-time MBAs, EMBAs (awarded "Best Core Teacher"), Executive Education and Ph.D. students.
She co-directs the Global Poverty Research Lab, for which she founded the China Cluster. She also founded China Econ Lab, an independent organization aiming to promote high quality analysis of the Chinese economy.
Her work has been covered in media outlets such as NPR, New York Times, WSJ, FT, BBC. She regularly engages with high-level policymakers and business leaders about geo-political risk and the global economy, especially with respect to China. She contributes opinion editorials and is writing her first book, which has the working title “Inglorious Nations: The Rise, Fall and Reinvention of Large Civilizations”.
Outside of work, she enjoys cooking, reading, sports, travel and spending time with her family and friends.
- Development Economics
- Political Economy
- Historical Development
- Economic Development
- Political Economy
- Economies of the Population
- Development Economics
- Empirical Methods
- Interdisciplinary Perspectives on Population
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Doctor of Philosophy, 2005, Economics, Massachusetts Institute of Technology
Bachelor of Arts, 2001, Economics, Government, Japanese and Mathematics, University of Texas at Austin, High Honors -
Associate Professor, Economics, Yale University, 2013-present
Visiting Scholar, Economics, Stern School of Business, New York University, 2016-present
Visiting Scholar, Economics, Booth Business School, University of Chicago, 2015-present
Visiting Scholar, Economics, Stern School of Business, New York University, 2014-present
Affiliate, Council on East Asian Studies, Yale University, 2014-present
Affiliate, Leitner Center for Political Economy, Yale University, 2014-present
Assistant Professor, Economics, Yale University, 2009-2013
Visiting Scholar, Industrial Relations Section, Princeton University, 2011-2012
Visiting Scholar, Booth Business School, University of Chicago, 2009-present
Visiting Scholar, Economics, Harvard University, 2007-2009
Harvard Academy Scholar, Harvard University, 2007-2009
Assistant Professor, Economics, Brown University, 2005
Affiliate, Populations Studies and Training Center, Brown University, 2005-2009 -
Fellow of the Econometric Society, Econometric Society
CEPR Kiel Institute Conference on Geopolitics and Economics Keynote
Columbia University NT Wang Lecture
Fellow of the Econometric Society, Econometrics Society
Keynote: IEB SOLE Summer Workshop on Political Economy
Keynote: University of Lund Anne Rude Workshop on Culture, Institutions and Development
Keynote: University of Chicago and BFI Economic History and Historical Political Economy of Russia
Keynote: University of International Business and Economics for The Third Beijing Interna-tional Trade and Investment Symposium: Trade Institutions and Development
Keynote: Shanghai Lixin University of Accounting and Finance
Keynote: Peking University CCER Summer Institute -
Associate Editor, Economica, 2015
Associate Editor, The Journal of European Economics, 2013
Associate Editor, The Journal of Development Economics, 2010
Editorial Board, Review of International Organizations, 2017
Editorial Board, American Economic Journal – Applied, 2017
Editorial Board, VOX China, 2017
Political Economy IV: Topics in Development Economics (MECS-540-4)
This course introduces PhD students to three important topics within development economics and political economy, reviewing the frontier of the literature, the latest questions, methods most prevalently used, and the evidence thus far. The class focuses on empirical methods and their connection with theory. The course goal is assisting students as they transition into the research phase of their career.
Statistical Decision Analysis (MECNX-434-0)
Global Initiatives in Management (GIM) (INTLX-473-0)
All FT GIM classes will hold a final, mandatory class session. Please refer to each class's syllabi for the date and time.
Global Initiatives in Management (GIM) is an international experiential learning course designed to provide students with an introduction to the unique business opportunities, management practices and market dynamics of a specific region or global industry. The course combines in-class lectures, reading discussions and case studies during the winter quarter with ten days of international field research over spring break. Immersed in the culture and language of their host countries, students will have the opportunity to meet with local business and government leaders, conduct interviews and collect data for their group research projects, and experience some of the unique social and cultural facets of the region. Final presentations and written research reports are due in spring quarter after completion of the overseas portion of the class. Each class section is taught by a faculty member with deep knowledge of the region or industry and supported by an advisor from the Kellogg staff who assists students in planning the field experience. Students are financially responsible for their travel costs, and financial aid is available to those who qualify.
Big Data Advanced Analytics Workshop (MECN-935-0)
Inference with big data is central to business today, where evidenced-based decisions are highly valued. Doing this is difficult because real world situations are often complex and fast-paced, and data can be simultaneously "big" and yet imperfect. In the real world, one has to analyze data for different types of decisions and situations and is rarely in the position of choosing his/her ideal data or setting. This means that the quality of the data and the method with which one can make inferences vary greatly across contexts. Moreover, handling big data, where one cannot visualize the entire dataset and visually identify problems, requires knowledge of advanced regression modeling and post-estimation techniques. Business leaders in such situations need to extract useful insights from data with advanced statistical modelling, and to communicate these insights in a non-technical and intuitive way so that others can understand.
This class addresses these needs by teaching advanced statistical modelling with big data, and practicing communicating these ideas at all levels of technicality (or non-technicality). It takes a practical view of statistics and data analysis with large datasets and provides students with a range of advanced state-of-the-art statistical and basic machine learning tools to address economic questions. Two unique cases were developed especially for this class. One of the cases is an "open-ended" project in which students will be required to apply the tools they learn to build a statistical model for analysis and then design business strategy based on the evidence. Each case reflects a highly complex real-world situations and evolve across lectures in stages so that students learn advanced analytical skills in a concrete context-relevant setting. This class will benefit students who want to think creatively about how to apply the results of rigorous data analysis to economic decisions.
This course is case-focused and most of the analysis will be conducted in groups in class. Using a fun and hands-on approach, students build on the foundational tools they obtained in the Business Analytics courses and learn advanced applications by working with big data projects in a lab-like setting in class. Students will analyze the data using STATA, interpret the results, assess their credibility and applicability to the economic questions which motivated the analysis, and present evidence-driven business decisions in class. There are no exams. Prerequisite: Business Analytics II (DECS 431) (see syllabus).
Global Initiatives in Mgmt GIM (INTL-473-20)
Spring Session
Global Initiatives in Management (GIM) (INTL-473-0)
All FT GIM classes will hold a final, mandatory class session. Please refer to each class's syllabi for the date and time.
Global Initiatives in Management (GIM) is an international experiential learning course designed to provide students with an introduction to the unique business opportunities, management practices and market dynamics of a specific region or global industry. The course combines in-class lectures, reading discussions and case studies during the winter quarter with ten days of international field research over spring break. Immersed in the culture and language of their host countries, students will have the opportunity to meet with local business and government leaders, conduct interviews and collect data for their group research projects, and experience some of the unique social and cultural facets of the region. Final presentations and written research reports are due in spring quarter after completion of the overseas portion of the class. Each class section is taught by a faculty member with deep knowledge of the region or industry and supported by an advisor from the Kellogg staff who assists students in planning the field experience. Students are financially responsible for their travel costs, and financial aid is available to those who qualify.
