printer friendly pagePOLISCI 355: The Political Economy of American Elections
This class will survey classic and contemporary research into the political economy of American elections, including core topics such as ideological positioning and representation, the incumbency advantage, democratic accountability, and campaign finance. Students will be asked to carry out replications of published papers and to work on a research paper of their own. This class is aimed at Ph.D. students interested in the study of American politics. Prerequisites are econometrics and causal inference, intro grad micro, and formal theory, as offered in the Econ, Polisci, or GSB grad programs.
Terms: Aut
| Units: 3
Instructors:
Hall, A. (PI)
POLISCI 355A: Data Science for Politics (POLISCI 150A)
Data science is quickly changing the way we understand and and engage in the political process. In this course we will develop fundamental techniques of data science and apply them to large political datasets on elections, campaign finance, lobbying, and more. The objective is to give students the skills to carry out cutting edge quantitative political studies in both academia and the private sector. Students with technical backgrounds looking to study politics quantitatively are encouraged to enroll.
Terms: Aut
| Units: 3-5
POLISCI 355B: Machine Learning for Social Scientists (POLISCI 150B)
Machine learning - the use of algorithms to classify, predict, sort, learn and discover from data - has exploded in use across academic fields, industry, government, and the non-profit sector. This course provides an introduction to machine learning for social scientists. We will introduce state of the art machine learning tools, show how to use those tools in the programming language R, and demonstrate why a social science focus is essential to effectively apply machine learning techniques in social, political, and policy contexts. Applications of the methods will include forecasting social phenomena, evaluating the use of algorithms in public policy, and the analysis of social media and text data. Prerequisite:
POLISCI 150A/355A.
Terms: Win
| Units: 3-5
Instructors:
Bonica, A. (PI)
;
Studen, N. (TA)
POLISCI 355C: Causal Inference for Social Science (POLISCI 150C)
Causal inference methods have revolutionized the way we use data, statistics, and research design to move from correlation to causation and rigorously learn about the impact of some potential cause (e.g., a new policy or intervention) on some outcome (e.g., election results, levels of violence, poverty). This course provides an introduction that teaches students the toolkit of modern causal inference methods as they are now widely used across academic fields, government, industry, and non-profits. Topics include experiments, matching, regression, sensitivity analysis, difference-in-differences, panel methods, instrumental variable estimation, and regression discontinuity designs. We will illustrate and apply the methods with examples drawn from various fields including policy evaluation, political science, public health, economics, business, and sociology. Prerequisite:
POLISCI 150A.
Last offered: Spring 2024
POLISCI 355R: Mastering Regression (POLISCI 150R)
This course provides an undergraduate-level introduction to regression models, along with the basic principles of probability and statistics which are essential for understanding how regression works. Regression models are routinely used in political science, policy research, and other disciplines in social science. The principles learned in this course also provide a foundation for the general understanding of quantitative political methodology. If you ever want to collect quantitative data, analyze data, critically read an article which presents a data analysis, or think about the relationship between theory and the real world, then this course will be helpful for you. You can only learn statistics by doing statistics. In recognition of this fact, the homework for this course will be extensive. In addition to the lectures and weekly homework assignments, there will be required and optional readings to enhance your understanding of the materials. You will find it helpful to read these not only once, but multiple times (before, during, and after the corresponding homework).
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