ECON 160: Game Theory and Economic Applications
Introduction to game theory and its applications to economics. Topics: strategic and extensive form games, dominant strategies, Nash equilibrium, subgame-perfect equilibrium, and Bayesian equilibrium. The theory is applied to repeated games, oligopoly, auctions, and bargaining with examples from economics and political science. Prerequisites: Working knowledge of calculus and basic probability theory.
Terms: Spr
| Units: 5
| UG Reqs: WAY-FR, WAY-SI
Instructors:
Baltaduonis, R. (PI)
ECON 162: Games Developing Nations Play (POLISCI 247A, POLISCI 347A)
If, as economists argue, development can make everyone in a society better off, why do leaders fail to pursue policies that promote development? The course uses game theoretic approaches from both economics and political science to address this question. Incentive problems are at the heart of explanations for development failure. Specifically, the course focuses on a series of questions central to the development problem: Why do developing countries have weak and often counterproductive political institutions? Why is violence (civil wars, ethnic conflict, military coups) so prevalent in the developing world, and how does it interact with development? Why do developing economies fail to generate high levels of income and wealth? We study how various kinds of development traps arise, preventing development for most countries. We also explain how some countries have overcome such traps. This approach emphasizes the importance of simultaneous economic and political development as two different facets of the same developmental process. No background in game theory is required.
Last offered: Winter 2021
| Units: 3-5
| UG Reqs: WAY-AQR, WAY-SI
ECON 163: Data Science for Social Impact (COMM 140X, DATASCI 154, EARTHSYS 153, MS&E 134, POLISCI 154, PUBLPOL 155, SOC 127)
You have some experience coding in R or Python. You've taken a class or two in basic stats or data science. But what's next? How can you use data science skills to make the world a better place? If you're asking those questions, then "Data Science for Social Impact" is for you. In this class, you'll work in four areas where data are being used to make the world better: health care, education, detecting discrimination, and clean energy technologies. You'll work with data from hospitals, schools, police departments, and electric utilities. You'll apply causal inference, prediction, and optimization techniques to help businesses, governments, and other organizations make better decisions. You'll see the challenges that arise when analyzing real data (for example, when some data are missing, or when the randomized experiment gets implemented wrong). You'll get ideas for an impactful and meaningful senior thesis, summer internship, and future career. Concretely, you'll have weekly problem s
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You have some experience coding in R or Python. You've taken a class or two in basic stats or data science. But what's next? How can you use data science skills to make the world a better place? If you're asking those questions, then "Data Science for Social Impact" is for you. In this class, you'll work in four areas where data are being used to make the world better: health care, education, detecting discrimination, and clean energy technologies. You'll work with data from hospitals, schools, police departments, and electric utilities. You'll apply causal inference, prediction, and optimization techniques to help businesses, governments, and other organizations make better decisions. You'll see the challenges that arise when analyzing real data (for example, when some data are missing, or when the randomized experiment gets implemented wrong). You'll get ideas for an impactful and meaningful senior thesis, summer internship, and future career. Concretely, you'll have weekly problem sets involving data analysis in R or python. You'll learn and apply techniques like fixed effects regression, difference-in-differences, instrumental variables, regularized regression, random forests, causal forests, and optimization. Class sessions will feature active learning, discussions, and small-group case studies. You should only enroll if you expect to attend regularly and complete the problem sets on time. Prerequisites (recommended): Experience programming in R or python, or willingness to learn very quickly on your own. A basic statistics or data science course, such as any of the following:
DATASCI 112,
ECON 102 or 108,
CS 129,
EARTHSYS 140,
HUMBIO 88,
POLISCI 150A,
STATS 60,
SOC 180B, or MS&E 125.
Terms: Spr
| Units: 5
| UG Reqs: WAY-AQR, WAY-SI
Instructors:
Hwang, J. (PI)
;
Hwang, S. (PI)
;
Nobles, M. (PI)
;
Lyu, D. (TA)
;
Scott-Hearn, N. (TA)
ECON 165: International Finance
We will explore models for analyzing a wide variety of issues in open-economy macroeconomics such as the balance of payments; the determination and behavior of exchange rates; the implementation of monetary and fiscal policy under flexible and fixed exchange rate regimes; the macroeconomic gains and/or pains from financial globalization; optimum currency areas; exchange rate crises and debt crises. We will apply our theoretical framework to an examination of important historical episodes and contemporary policy debates; the textbook will be supplemented with readings from academic articles and mainstream news sources. Active class participation is an important part of the course.
Terms: Aut
| Units: 5
| UG Reqs: WAY-SI
ECON 166: International Trade
This course examines the causes and consequences of international trade. Why do countries trade? What determines the goods that a country exports and imports? Do countries as a whole gain or lose from trade? Is a trade deficit or surplus a cause for concern? Do some people or groups within countries gain or lose from trade? What are the arguments for and against protectionist trade policies such as tariffs? Is there a rationale for a World Trade Organization (WTO)? What are the implications of rapid economic growth in emerging markets (e.g., China) for income and welfare in already-developed countries such as the United States? What were the local labor market consequences of the China shock? Should governments use activist trade and industrial policies? What is the future of the global trading system? Prerequisite:
ECON 51 (Public Policy majors may take
PUBLPOL 51 as a substitute for
ECON 51).
Terms: Win
| Units: 5
| UG Reqs: WAY-SI
Instructors:
Redding, S. (PI)
;
O'Neil, F. (TA)
ECON 167G: Game Theory and Social Behavior
Game theory is the formal toolkit for analyzing situations in which payoffs depend not only on your actions (say, which TV series you watch), but also others' (whether your friends are watching the same show). You've probably already heard of some famous games, like the prisoners' dilemma and the costly signaling game. We'll teach you to solve games like these, and more, using tools like Nash equilibrium, subgame perfection, Bayesian Nash equilibrium, and the one-off deviation principle. Game theory has traditionally been applied to understand the behavior of highly deliberate agents, like heads of state, firms in an oligopoly, or participants in an auction. However, we'll apply game theory to social behavior typically considered the realm of psychologists and philosophers, such as why we speak indirectly, in what sense beauty is socially constructed, and where our moral intuitions come from. Nearly each week, students are expected to complete a problem set, to read 2-3 academic papers
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Game theory is the formal toolkit for analyzing situations in which payoffs depend not only on your actions (say, which TV series you watch), but also others' (whether your friends are watching the same show). You've probably already heard of some famous games, like the prisoners' dilemma and the costly signaling game. We'll teach you to solve games like these, and more, using tools like Nash equilibrium, subgame perfection, Bayesian Nash equilibrium, and the one-off deviation principle. Game theory has traditionally been applied to understand the behavior of highly deliberate agents, like heads of state, firms in an oligopoly, or participants in an auction. However, we'll apply game theory to social behavior typically considered the realm of psychologists and philosophers, such as why we speak indirectly, in what sense beauty is socially constructed, and where our moral intuitions come from. Nearly each week, students are expected to complete a problem set, to read 2-3 academic papers, and to complete a 1-2 page response to short essay questions (`prompts') on these readings. All assignments can be completed in groups of two. There will also be a final exam. Prerequisites: Although there are no formal prerequisites for this course, we will make frequent use of probability theory (Bayes' Rule; conditional probabilities), set theory notation, and proofs. Students without a background in these tools have historically found some of the later problem sets to be challenging. TA sessions are not required, but are recommended for students without the necessary math background. Not sure if this class is for you? Take our self assessment, then see how your answers compare with ours. (Assessments and solutions can be found here:
https://economics.stanford.edu/undergraduate/forms)
Last offered: Autumn 2023
| Units: 5
| UG Reqs: WAY-SI
ECON 169: Advanced Topics in Macroeconomics and International Finance
This is an advanced course in macroeconomics and international finance. We both build on and use the analytical foundations from earlier courses to understand key macroeconomic issues, such as the sources of growth and business cycles, the causes of inflation, and the effects of monetary and fiscal policy on the economy as well as global capital flows and the behavior of exchange rates. Each segment will start off with the key theoretical foundation and then we will discuss applying this theory to real-world events. This course will cover different topics than those covered in
ECON 152: Advanced Macroeconomics and
ECON 165: International Finance and would be a great follow up to those courses, but those courses are by no means a prerequisite for this one.
Terms: Spr
| Units: 5
Instructors:
Kehoe, P. (PI)
ECON 175: Environmental Economic Theory (GEP 160)
This class draws on simple economic tools and game theory to provide a coherent framework that can be used to analyze environmental problems as well as political solutions. The models are relevant for both local and international environmental problems. We will analyze environmental problems as market failures, and how these can be corrected with policies, f.ex., taxes or permits. We will model countries' strategic choices of emissions, their investments in technology, international negotiations and bargaining, and alternative designs of agreements. We will also study political economy forces, documented to be important by the political science literature, that prevent good policies from being introduced, and how policies ought to be designed in order to take these political constraints into account.
Last offered: Spring 2025
| Units: 5
| UG Reqs: WAY-FR
ECON 177: Environmental Economics: Models, Data, and Policy Design (GEP 130, GEP 230)
See
allcott.stanford.edu/teaching/EE for the class webpage and promo video. Are you interested in environmental and energy policy? Do you want to improve your data science skills? If so, Environmental Economics is for you. In the first few weeks of class, you'll use data and microeconomic modeling to quantify the harms from pollution, including estimating the social cost of carbon emissions. For the rest of the quarter, you'll use more data and microeconomic modeling to evaluate major environmental policies such as pollution taxes, cap-and-trade programs, and subsidies for clean technologies. You will consider overall benefits and costs as well as distributional equity, which can inform discussions of environmental justice. You will learn and practice useful data science skills, including applied econometrics/causal inference methods (e.g., difference-in-differences, instrumental variables, and regression discontinuity) and equilibrium modeling. The class has weekly problem sets invol
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See
allcott.stanford.edu/teaching/EE for the class webpage and promo video. Are you interested in environmental and energy policy? Do you want to improve your data science skills? If so, Environmental Economics is for you. In the first few weeks of class, you'll use data and microeconomic modeling to quantify the harms from pollution, including estimating the social cost of carbon emissions. For the rest of the quarter, you'll use more data and microeconomic modeling to evaluate major environmental policies such as pollution taxes, cap-and-trade programs, and subsidies for clean technologies. You will consider overall benefits and costs as well as distributional equity, which can inform discussions of environmental justice. You will learn and practice useful data science skills, including applied econometrics/causal inference methods (e.g., difference-in-differences, instrumental variables, and regression discontinuity) and equilibrium modeling. The class has weekly problem sets involving data analysis in R, plus a final paper. Class sessions feature active learning, discussions, and small-group case studies. You should only enroll if you expect to attend regularly and complete the problem sets on time. The final paper is a great way to generate ideas for and get started on a senior thesis.
Terms: Aut
| Units: 4-5
| UG Reqs: WAY-AQR, WAY-SI
ECON 178: Behavioral Economics
The field of behavioral economics draws on insights from other disciplines, especially psychology, to enrich our understanding of economic behavior. In this course, we will discuss how psychological considerations can create behavioral patterns that diverge from the predictions of standard economic models, the implications of those behavioral patterns for market outcomes and public policies, and the ways in which economists incorporate those considerations into their theories. We will also examine how social motives (such as altruism or concerns about fairness, equity, status, or image) impact economic behavior. We will learn about classical findings and leading theories in behavioral economics. The treatment of psychological phenomena in this course involves tools similar to those employed in other economics courses. Prerequisites:
ECON 50 and
ECON 102A.
Econ 51 and 102B are recommended.
Terms: Aut
| Units: 5
| UG Reqs: WAY-SI