Undergraduate Courses

  • POL 981S6: Globalization and Politics
    • Preceptor with Faisal Ahmed, Department of Politics, Princeton University (Fall 2020)
    • Course description
      Globalization – broadly defined as the movement of people, money, and goods across national borders – is an increasingly salient topic for citizens, governments/states, and the natural environment. This junior workshop examines the drivers and consequences associated with globalization, with a particular emphasis on the political dimension. Some political drivers include (but are not limited to): partisanship, the process of democratization, international influences (e.g., the United States, World Bank, International Monetary Fund), and interest groups. Some political consequences include (but are not limited to): political polarization, income and political inequality, contentious politics, civil war, democratization, institutional change, authoritarian resilience, and the politics of climate change. Readings in the workshop will focus on research articles that seek to understand the political drivers and effects associated with globalization. We will use these readings as examples of quality research in political science, focusing in particular on the types of research design challenges confronting these studies and the researchers’ effectiveness in addressing those challenges.
  • POL 981S7: Europe and Russia in the World
    • Preceptor with Marzenna James, Department of Politics and School of Public and International Affairs, Princeton University (Fall 2020)
    • Course description
      The workshop will deal with a variety of issues in the area of European and Russian foreign policies, as well as transatlantic cooperation, including the questions: What are the mechanisms of multilateral cooperation between the United States and other global powers with Europe, and between countries within Europe? What are the main political problems in Europe, the European Union, and transatlantic cooperation? What is the importance of Brexit for transatlantic relations and the viability of the European Union as an economic and political unit in international relations? What is the nature of the challenge posed by Russian and Chinese foreign policies vis-à-vis the European Union? The goal of the workshop is to initiate the students into the process of independent research: to understand its underlying logic. The main emphasis will be on the basic methodological foundations upon which the students will design their own research projects.
  • POLS W4871: Chinese Foreign Policy
    • Teaching Fellow with Andrew Nathan, Department of Political Science, Columbia University (Spring 2016)
    • Course description
      The course describes the major elements of Chinese foreign policy today, in the context of their development since 1949. We seek to understand the security-based rationale of policy as well as other factors – organizational, cultural, perceptual, and so on – that influence Chinese foreign policy. We analyze decision-making processes that affect Chinese foreign policy, China’s relations with various countries and regions, Chinese policy toward key functional issues in international affairs, how the rise of China is affecting global power relations, and how other actors are responding. The course pays attention to the application of international relations theories to the problems we study, and also takes an interest in policy issues facing decision-makers in China as well as those facing decision-makers in other countries that deal with China.
  • SPI 600B: Statistics for Policymakers
    • Instructor of Record, Public Policy Junior Summer Institute at Princeton University (Summer 2020)
    • Course description
      What determines economic growth and development? Do large-scale social programs actually achieve their intended impact? Policymakers often use statistics to answer these questions. Importantly, the validity of their conclusions hinges on plausible underlying assumptions and defensible application of statistical methods. The course will introduce basic principles of statistical inference and programming skills for data analysis in R. The goal is to become a critical consumer and analyst of news articles and academic studies that use statistics and provide students with the foundation necessary to analyze data for the Global Systemic Risks (GSR) course.

Ph.D. Courses

  • POL 505: Experimental Political Science
    • Preceptor with Leonard Wantchekon, Department of Politics, Princeton University (Spring 2020)
    • Course description
      The goal of this course introduces students to the theoretical and practical features of experimental political science, particularly natural and field experiments. There is a special emphasis on the importance of distinguishing between policy-based and institution-based interventions, with attention given to the promise of the latter for political economy research. The course is divided into four sections. The first section of the course introduces students to the methodological underpinnings of experimental scholarship, particularly causal inference and the motivation behind randomization. The section focuses on practical application and experimental design, including randomization techniques, sample selection, and power analysis. It also includes a set of readings that address common problems and solutions. The second section focuses on experiments that occur in nature and how to extract causal estimates from these experiments. The third section covers the conceptualization and operationalization of laboratory (and laboratory in the field) experiments, as well as survey experiments. Particular attention will be paid to the issues that arise when evaluating institutions. The final section will cover innovations in experimental methods for evaluating institutions. The course will conclude with student presentations of their research project.
  • POL 572: Quantitative Analysis II
    • Preceptor with Marc Ratkovic, Department of Politics, Princeton University (Spring 2021)
    • Course materials
    • Course description
      Positive political science involves connecting our observations of the social world with causal mechanisms. We are going to focus on a particular problem: to what extent can we used observed data to measure, discover, and test underlying causal claims? The course will include a combination of statistical theory, hands--on data analysis, and causal reasoning. The goal of the course is to produce students who can understand, apply, and ultimately further quantitative political methodology.
  • POL 573 / SOC 595: Quantitative Analysis III
    • Preceptor with Rocío Titiunik, Department of Politics, Princeton University (Fall 2019)
    • Course description
      This course is an advanced graduate-level methods course, meant to be taken after POL 571 and POL 572 or equivalent courses. The course will cover several topics that are not usually covered in the first-year sequence, including asymptotics, hypothesis testing, maximum likelihood estimation, nonparametric estimation, partial identification, and resampling methods. The course will be both theoretical and practical. There will be regular problem sets that will require the empirical analysis of real datasets as well as theoretical exercises, and two exams.
  • Text Analysis
    • Assistant instructor with Will Lowe, Institute for Qualitative and Mixed-Method Research (IQMR) (Summer 2019)
    • Course description
      These modules are about using computers to systematically analyze text, typically as precursor, successor, or complement to a qualitative analysis. We’ll discuss and practice classical dictionary-based content analysis and its newer incarnation topic modeling, consider how to classify large numbers of documents by topic, and show how to project their contents into rhetorical spaces for understanding and visualization. Along the way we’ll scrape texts from the web, and discuss good ways to integrate text analysis into a variety or research designs. We’ll presume a grasp of basic mathematical and statistical concepts and a willingness to follow along with the computational parts. The module mostly uses R and its packages. Expertise in R is not required, although some prior experience may be helpful. If there is interest we can also run a very short introduction to R prior to the course for those who’ve not met it before.

Public Policy Master’s Courses

  • SPI 507B: Quantitative Analysis for Policymakers
    • Tutor with David Lee, School of Public and International Affairs, Princeton University (Fall 2019, Fall 2020)
    • Course description
      Today, more data are available to researchers than ever before. In this course, we’ll cover how to use statistics to harness these data to improve policy analysis. This course will equip you to understand the mathematical foundations of statistics, to understand common types of quantitative analysis, and to apply these tools yourself using the statistical software package Stata. Our overarching goal is application: to give you the means of answering big policy questions, and not get bogged into the weeds of math and notation. We want you to be a discerning consumer of statistical news, and someone who can use the principles of statistics to do your own analysis.
  • SPI 507C: Advanced Quantitative Analysis for Policymakers
    • Tutor with Eduardo Morales, School of Public and International Affairs, Princeton University (Fall 2020)
    • Course description
      Statistical analysis with applications to public policy, begins with an introduction to probability theory followed by discussion of statistical methods for estimating the quantitative effects of changes in policy variables. Regression methods appropriate for the analysis of observational data and data from randomized controlled experiments are stressed. By course end, students are able to do their own empirical analysis using statistical software package & interpret regression results from the professional literature. The course assumes fluency in calculus, which is necessary for rigorous mathematical analysis of probability and statistics.
  • SPI 512B: Macroeconomic Analysis for Policymakers
    • Tutor with Richard Rogerson, School of Public and International Affairs, Princeton University (Spring 2020)
    • Course description
      This course covers the theory of modern macroeconomics in detail. The focus is on the determination of macroeconomic variables - such as output, employment, prices, and the interest rate - in the short, medium, and long run, and addresses a number of policy issues. Discusses several examples of macroeconomic phenomena in the real world. A central theme is to understand the powers and limitations of macroeconomic policy in stabilizing the business cycle and promoting growth.
  • SPI 522: Microeconomic Analysis of Domestic Policy
    • Tutor with Alexandre Mas, School of Public and International Affairs, Princeton University (Fall 2020)
    • Course description
      This course focuses on the role of the government in the economy. The aim is to provide an understanding of the reasons for government intervention in the economy, analyzing the benefits and costs of possible government policies, and the response of economic agents to the government's actions. The course covers education, labor, and tax policy, social insurance programs, public goods, environmental protection, and the interaction between different levels of government.
  • SPI 551B: Microeconomic Analysis for Policymakers
    • Tutor with Amy Craft, School of Public and International Affairs, Princeton University (Fall 2019, Fall 2020)
    • Course description
      The purpose of this course is to develop an understanding of microeconomic tools and learn how to apply them to the analysis of policies. Students need not have taken any other economics courses but they should have a good command over algebra and be familiar with basic calculus concepts, although proficiency in calculus is not necessary.
  • SPI 598 / POP 508: Epidemiology
    • Tutor with Noreen Goldman, School of Public and International Affairs, Princeton University (Spring 2021)
    • Course description
      This course combines a traditional public health course in epidemiology with a policy-oriented course on population health. Conventional topics include measurement of health and survival and impact of associated risk factors; techniques for design, analysis of epidemiologic studies; sources of bias and confounding; and causal inference. We also examine: models of infectious disease with an emphasis on COVID-19, inference and decision making based on large numbers of studies and contradictory information, the science underlying screening procedures, social inequalities in health, and ethical issues in medical research.