# Economics (Ec) Graduate Courses (2020-21)

Ec 101.
Selected Topics in Economics.
Units to be determined by arrangement with the instructor:
offered by announcement.
Topics to be determined by instructor.
Instructors: Staff, visiting lecturers.

Ec 105.
Firms, Competition, and Industrial Organization.
9 units (3-0-6):
first term.
Prerequisites: Ec 11 or equivalent.
A study of how technology affects issues of market structure and how market structure affects observable economic outcomes, such as prices, profits, advertising, and research and development expenditures. Emphasis will be on how the analytic tools developed in the course can be used to examine particular industries-especially those related to internet commerce-in detail. Each student is expected to write one substantial paper.
Instructor: Shum.

Ec 109.
Frontiers in Behavioral Economics.
9 units (3-0-6):
second term.
Prerequisites: Ec 11.
This course will study topics in behavioral economics demonstrating departures from the classic economics assumptions of rationality and pure self-interest. We will study evidence of these departures, models that have been designed to capture these preferences, and applications of these models to important economic questions. Topics will include biases and heuristics, risk preferences, self-control, strategic uncertainty, and social preferences, among others. The course will be based in readings from both classic and modern research. Methodologically, the course will combine both theoretical and empirical evidence of the mentioned above topics.
Instructor: Nielsen.

Ec/ACM/CS 112.
Bayesian Statistics.
9 units (3-0-6):
second term.
Prerequisites: Ma 3, ACM/EE/IDS 116 or equivalent.
This course provides an introduction to Bayesian Statistics and its applications to data analysis in various fields. Topics include: discrete models, regression models, hierarchical models, model comparison, and MCMC methods. The course combines an introduction to basic theory with a hands-on emphasis on learning how to use these methods in practice so that students can apply them in their own work. Previous familiarity with frequentist statistics is useful but not required.
Instructor: Rangel.

Ec 117.
Matching Markets.
9 units (3-0-6):
third term.
We will tackle the fundamental question of how to allocate resources and organize exchange in the absence of prices. Examples includes finding a partner, allocating students to schools, and matching donors to patients in the context of organ transplantations. While the main focus will be on formal models, we will also reason about the practical implications of the theory.
Instructor: Pomatto.

BEM/Ec/ESE 119.
Environmental Economics.
9 units (3-0-6):
first term.
Prerequisites: Ec 11 or equivalent.
This course provides a survey from the perspective of economics of public policy issues regarding the management of natural resources and the protection of environmental quality. The course covers both conceptual topics and recent and current applications. Included are principles of environmental and resource economics, management of nonrenewable and renewable resources, and environmental policy with the focus on air pollution problems, both local problems (smog) and global problems (climate change). Not offered 2020-21.

Ec 121 ab.
Theory of Value.
9 units (3-0-6):
first, second terms.
Prerequisites: Ec 11 and Ma 1 b (may be taken concurrently).
A study of consumer preference, the structure and conduct of markets, factor pricing, measures of economic efficiency, and the interdependence of markets in reaching a general equilibrium.
Instructors: Border, Saito.

Ec 122.
Econometrics.
9 units (3-0-6):
first term.
Prerequisites: Ma 3.
The application of statistical techniques to the analysis of economic data.
Instructor: Sherman.

Ec 123.
Analysis of Consumer Choices.
9 units (3-0-6):
second term.
Prerequisites: Ec 122 or permission of the instructor.
This course uses econometric tools to analyze choices made by people among a finite set of alternatives. Discrete choice models have been used to understand consumer behavior in many domains - shopping between brands (Toyota vs. BMW), where to go to college (Caltech or MIT), choosing between modes of transportation (car, metro, Uber, or bicycle), etc. Models studied include logit, nested logit, probit, and mixed logit, etc. Simulation techniques that allow estimation of otherwise intractable models will also be discussed.
Instructor: Xin.

Ec/PS 124.
Identification Problems in the Social Sciences.
9 units (3- 0-6):
second term.
Prerequisites: Ec 122.
Statistical inference in the social sciences is a difficult enterprise whereby we combine data and assumptions to draw conclusions about the world we live in. We then make decisions, for better or for worse, based on these conclusions. A simultaneously intoxicating and sobering thought! Strong assumptions about the data generating process can lead to strong but often less than credible (perhaps incredible?) conclusions about our world. Weaker assumptions can lead to weaker but more credible conclusions. This course explores the range of inferences that are possible when we entertain a range of assumptions about how data is generated. We explore these ideas in the context of a number of applications of interest to social scientists. Not offered 2020-21.

IDS/Ec/PS 126.
Applied Data Analysis.
9 units (3-0-6):
first term.
Prerequisites: Math 3/103 or ACM/EE/IDS 116, Ec 122 or IDS/ACM/CS 157 or Ma 112 a.
Fundamentally, this course is about making arguments with numbers and data. Data analysis for its own sake is often quite boring, but becomes crucial when it supports claims about the world. A convincing data analysis starts with the collection and cleaning of data, a thoughtful and reproducible statistical analysis of it, and the graphical presentation of the results. This course will provide students with the necessary practical skills, chiefly revolving around statistical computing, to conduct their own data analysis. This course is not an introduction to statistics or computer science. I assume that students are familiar with at least basic probability and statistical concepts up to and including regression.
Instructor: Katz.

Ec 129.
Economic History of the United States.
9 units (3-0-6):
second term.
Prerequisites: Ec 11.
An examination of certain analytical and quantitative tools and their application to American economic development. Each student is expected to write two substantial papers-drafts will be read by instructor and revised by students. Not offered 2020-21.

Ec 130.
Economic History of Europe from the Middle Ages to the Twentieth Century.
9 units (3-0-6):
third term.
Prerequisites: Ec 11.
Employs the theoretical and quantitative techniques of economics to help explore and explain the development of the European cultural area between 1000 and 1980. Topics include the rise of commerce, the demographic transition, the Industrial Revolution, and changes in inequality, international trade, social spending, property rights, and capital markets. Each student is expected to write nine weekly essays and a term paper. Not offered 2020-21.

Ec 135.
Economics of Uncertainty and Information.
9 units (3-0-6):
first term.
Prerequisites: Ec 11.
An analysis of the effects of uncertainty and information on economic decisions. Included among the topics are individual and group decision making under uncertainty, expected utility maximization, insurance, financial markets and speculation, product quality and advertisement, and the value of information.
Instructor: Agranov.

Ec 136.
Behavioral Decision Theory.
9 units (3-0-6):
third term.
Prerequisites: Ma 3. Ec 121 is recommended as background, but is not a prerequisite.
This course is an intermediate-level class on individual-level theory. The method used posits precise assumptions about general behavior (axioms) then finds equivalent ways to model them in mathematically convenient terms. We will cover both the traditional "rational'' approach, and more recent "behavioral'' models that incorporate psychological principles, in domains of intertemporal choice, random (stochastic) choice, menu choice, and revealed preferences. Students are expected to understand rigorous mathematical proofs. The class also includes serious discussion of the value of experimental evidence motivating new theories.
Instructor: Sprenger.

Ec 140.
Economic Progress.
9 units (3-0-6):
second term.
Prerequisites: Ec 11; Ec 122 recommended.
This course examines the contemporary literature on economic growth and development from both a theoretical and historical/empirical perspective. Topics include a historical overview of economic progress and the lack thereof; simple capital accumulation models; equilibrium/ planning models of accumulation; endogenous growth models; empirical tests of convergence; the measurement and role of technological advancement; and the role of trade, institutions, property rights, human capital, and culture.
Instructor: Hoffman.

CS/Ec 149.
Algorithmic Economics.
9 units (3-0-6):
second term.
This course will equip students to engage with active research at the intersection of social and information sciences, including: algorithmic game theory and mechanism design; auctions; matching markets; and learning in games.
Instructor: Echenique.

Ec/PS 160 abc.
Laboratory Experiments in the Social Sciences.
9 units (3-3-3):
first, second, third terms.
Section a required for sections b and c. An examination of recent work in laboratory testing in the social sciences with particular reference to work done in social psychology, economics, and political science. Students are required to design and conduct experiments.
Instructor: Plott.

PS/Ec 172.
Game Theory.
9 units (3-0-6):
third term.
Prerequisites: Ec 11 or PS 12.
This course is an introduction to non-cooperative game theory, with applications to political science and economics. It covers the theories of normal-form games and extensive-form games, and introduces solutions concepts that are relevant for situations of complete and incomplete information. The basic theory of repeated games is introduced. Applications are to auction theory and asymmetric information in trading models, cheap talk and voting rules in congress, among many others.
Instructor: Tamuz.

Ec 181 ab.
Convex Analysis and Economic Theory.
9 units (3-0-6):
first, second terms.
Prerequisites: Ma 1. Ec 121 a is recommended.
Introduction to the use of convex analysis in economic theory. Includes separating hyperplane theorems, continuity and differentiability properties of convex and concave functions, support functions, subdifferentials, Fenchel conjugates, saddlepoint theorem, theorems of the alternative, polyhedra, linear programming, and duality in graphs. Introduction to discrete convex analysis and matroids. Emphasis is on the finite-dimensional case, but infinite-dimensional spaces will be discussed. Applications to core convergence, cost and production functions, mathematical finance, decision theory, incentive design, and game theory.
Instructor: Border.

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The online version of the Caltech Catalog is provided as a convenience; however, the printed version is the only authoritative source of information about course offerings, option requirements, graduation requirements, and other important topics.